<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.3 20070202//EN" "journalpublishing.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" article-type="research-article" dtd-version="2.3" xml:lang="EN">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Sustain. Food Syst.</journal-id>
<journal-title>Frontiers in Sustainable Food Systems</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Sustain. Food Syst.</abbrev-journal-title>
<issn pub-type="epub">2571-581X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fsufs.2025.1506842</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Sustainable Food Systems</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Farmers&#x2019; willingness to adopt daylily forage technology in Northern Shanxi of China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Hou</surname>
<given-names>Xiangjuan</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Qidong</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jiang</surname>
<given-names>Qishen</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1784972/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zheng</surname>
<given-names>Minna</given-names>
</name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Chunyan</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yin</surname>
<given-names>Yanting</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Gao</surname>
<given-names>Changyu</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Cunzhen</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Hou</surname>
<given-names>Xiangyang</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1741151/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/resources/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>College of Agricultural Economics and Management, Shanxi Agricultural University</institution>, <addr-line>Taigu</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>College of Grassland Science, Shanxi Agricultural University</institution>, <addr-line>Taigu</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Key Laboratory of Efficient Forage Production Mode, Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University</institution>, <addr-line>Taigu</addr-line>, <country>China</country></aff>
<aff id="aff4"><sup>4</sup><institution>High Latitude Crops Institute, Shanxi Agricultural University</institution>, <addr-line>Datong</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001">
<p>Edited by: Anuradha Singh, Michigan State University, United States</p>
</fn>
<fn fn-type="edited-by" id="fn0002">
<p>Reviewed by: Arpan Bhowmik, Indian Council of Agricultural Research (ICAR), India</p>
<p>Zhiqiang Wang, Beijing Normal University, China</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Xiangyang Hou, <email>houxy16@vip.126.com</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>22</day>
<month>08</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>9</volume>
<elocation-id>1506842</elocation-id>
<history>
<date date-type="received">
<day>31</day>
<month>10</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>21</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Hou, Li, Jiang, Zheng, Li, Yin, Gao, Liu and Hou.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Hou, Li, Jiang, Zheng, Li, Yin, Gao, Liu and Hou</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Introduction</title>
<p>The transformation of the food structure is accelerating in China, and the shortage of feed grains is the main limiting factor. Traditional feed production and feeding modes no longer meet the requirements for high-quality livestock and poultry breeding. Therefore, China&#x2019;s forage industry must fully utilize its resource endowment advantages. This study explores two aspects: first, the research on the impact of personal, family, planting, and other characteristics on farmers&#x2019; willingness to adopt the forage utilization technology of stems and leaves of <italic>Hemerocallis citrina</italic> Baroni (Hc-FUT); and second, the influence of behavioral attitudes, subjective norms, and perceived behavioral control on farmers&#x2019; willingness to adopt Hc-FUT, based on the Theory of Planned Behavior (TPB).</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>Data were obtained from 225 farmers in the Yunzhou District, Datong City, Shanxi Province, China. A logistic regression model was used to examine the impact of the four characteristics on farmers&#x2019; willingness to adopt Hc-FUT, and a structural equation model was used to examine farmers&#x2019; willingness to use Hc-FUT based on TPB. SPSS 27 and AMOS 26were used for analysis.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>The results show that farmers who used Hc stems and leaves to feed livestock were more willing to adopt Hc-FUT. Greater government support and increased usage of the technology positively correlated with a higher willingness among farmers to adopt it. Both subjective norms and perceived behavioral control had a significant positive impact on adoption intention, whereas subjective norms also positively impacted behavioral attitudes.</p>
</sec>
</abstract>
<kwd-group>
<kwd>daylily</kwd>
<kwd>forage utilization</kwd>
<kwd>willingness to adopt</kwd>
<kwd>TPB theory</kwd>
<kwd>SEM model</kwd>
</kwd-group>
<counts>
<fig-count count="1"/>
<table-count count="9"/>
<equation-count count="6"/>
<ref-count count="57"/>
<page-count count="12"/>
<word-count count="8664"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Agricultural and Food Economics</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec4">
<label>1</label>
<title>Introduction</title>
<p>Food security is crucial for human survival, yet global food security remains a critical and complex challenge, with one-third of the population experiencing severe food insecurity (<xref ref-type="bibr" rid="ref46">World Health Organization, 2022</xref>), contributing to the third global food crisis in 50&#x202F;years (<xref ref-type="bibr" rid="ref9">Clapp, 2023</xref>).</p>
<p>China has prioritized grain security as a strategic cornerstone since the founding of the People&#x2019;s Republic, achieving basic self-sufficiency through decades of targeted policies (<xref ref-type="bibr" rid="ref47">Wu, 2023</xref>). However, the nation now faces unique challenges in reconciling its historical achievements with emerging socioeconomic demands. As socialism with Chinese characteristics enters a new era, shifting consumption patterns&#x2014;marked by declining staple grain intake and rising meat demand&#x2014;have exposed structural contradictions in the agricultural system. This transition has intensified the &#x201C;human-livestock grain competition&#x201D; dilemma (<xref ref-type="bibr" rid="ref16">Hazra, 2014</xref>), particularly under resource constraints: China is still in the primary stage of developing its forage industry, and the severe shortage of land and water resources is seriously affecting its development (<xref ref-type="bibr" rid="ref19">Hou, 2022</xref>). The main issue in grain security in China is the security of feed grains (<xref ref-type="bibr" rid="ref52">Zhang, 2023</xref>; <xref ref-type="bibr" rid="ref48">Wu, 2024</xref>), and the country faces a 50-million-ton deficit in high-quality forage (<xref ref-type="bibr" rid="ref8">Chen et al., 2023</xref>). The &#x201C;greater food concept&#x201D; proposed by the Party Central Committee leverages China&#x2019;s resource endowment through innovative approaches: integrating crop-livestock systems, promoting circular agriculture, and advancing biotechnology for alternative protein sources. This pathway aligns with both ecological civilization objectives and the population&#x2019;s evolving dietary demands, demonstrating how China&#x2019;s unique developmental stage creates laboratory conditions for redefining global food security paradigms. Current research indicates that China&#x2019;s agricultural by-products (e.g., crop straw, vegetable residues, and soybean dregs) demonstrate significant potential for feed utilization. Taking corn straw in Shanxi Province as an example, elevating the feed conversion rate to above 50% could generate economic benefits exceeding 18 billion yuan. However, prevalent technical challenges&#x2014;including high conversion costs, insufficient industrial chain integration, and lack of large-scale application mechanisms&#x2014;remain core bottlenecks restricting the efficient utilization of these agricultural by-products (<xref ref-type="bibr" rid="ref51">Yin and Yang, 2025</xref>; <xref ref-type="bibr" rid="ref6">Cai et al., 2011</xref>; <xref ref-type="bibr" rid="ref43">Tang, 2024</xref>; <xref ref-type="bibr" rid="ref32">Qi and Zhou, 2023</xref>).</p>
<p><italic>Hemerocallis citrina</italic> Baroni (Hc) is native to central-northern China and has become a raw material for food and medicine because of its high nutritional value (<xref ref-type="bibr" rid="ref14">Guo et al., 2022</xref>; <xref ref-type="bibr" rid="ref42">Sun et al., 2024</xref>). Hc is distributed in various regions south of the Qinling Mountains, as well as in the Hebei, Shandong, and Shanxi provinces. In 2021, the Hc planting area in Datong City, Shanxi Province reached 17,667 hm<sup>2</sup>, the total output value of the entire Hc industry chain reached 4.2 billion yuan RMB. Hc is accompanied by a large number of stems and leaves after harvesting, and due to the lack of scientifically effective and economically viable processing and utilization technologies, most of the stems and leaves are treated as trash to casually discard or burned or easily used, resulting in wastage of resources and environmental pollution (<xref ref-type="bibr" rid="ref57">Zhao et al., 2021</xref>). Reusing the stems and leaves of Hc as forage can not only alleviate the shortage of forage but also promote the healthy development of the Hc industry, protecting the ecological environment of agricultural and rural areas. Although the nutritional components of <italic>Hemerocallis citrina</italic> are predominantly concentrated in its flowers, the stems and leaves also contain abundant flavonoid metabolites. Notably, the leaves exhibit particularly diverse compositions and significant functional properties, demonstrating potential applications in antioxidant, anti-inflammatory, and antibacterial activities. (<xref ref-type="bibr" rid="ref41">Shiao et al., 1962</xref>; <xref ref-type="bibr" rid="ref34">Rodriguez-Enriquez and Grant-Downton, 2013</xref>; <xref ref-type="bibr" rid="ref21">Karak, 2019</xref>; <xref ref-type="bibr" rid="ref27">Lv and Guo, 2023</xref>). The utilization of Hc stems and leaves as forage is mainly based on their biological characteristics and product functions through a series of technological treatments and other forage combinations. Transforming them into forage resources that can be safely consumed and have high nutritional value is meaningful for livestock. This technology has achieved notable progress, demonstrating significant applicability in ruminant (beef cattle and Tan sheep) farming when co-ensiled with silage corn. Studies confirm that feed incorporating daylily stems and leaves complies with forage standards. Through optimized blending at a 2:3 ratio, it effectively reduces fiber components by 18&#x2013;23% while improving palatability and digestibility. The formulation enhances lactic acid accumulation, suppresses proliferation of harmful microorganisms like <italic>Clostridium butyricum</italic>, and maintains stable pH levels within the ideal 4.13&#x2013;4.51 range throughout the preservation period (<xref ref-type="bibr" rid="ref28">Mei et al., 2021</xref>; <xref ref-type="bibr" rid="ref53">Zhang et al., 2023</xref>; <xref ref-type="bibr" rid="ref58">Zheng et al., 2024</xref>). The Shanxi Province&#x2019;s forage industry technology team has accumulated certain technological expertise in the field of Hc stem and leaf forage utilization, aiming to turn the waste of Hc into treasured and recycled resources. Although the technology has good prospects, there is still a significant gap in terms of promotion and application.</p>
<p>The Theory of Planned Behavior (TPB), proposed by <xref ref-type="bibr" rid="ref3">Ajzen (1991)</xref>, is one of the most representative and widely applied theories for studying farmers&#x2019; technology adoption behavior and intention. In practical applications, TPB has been used to study the intention of college students to consume green food (<xref ref-type="bibr" rid="ref17">He and Sui, 2024</xref>) and to explore the impact of digital literacy on farmers&#x2019; pro-environmental behavior (<xref ref-type="bibr" rid="ref26">Lu et al., 2024</xref>). Scholars have also used TPB to study farmers&#x2019; adoption behavior regarding agricultural technology, such as water-saving technology, green manure technology, green control technology, and sustainable agriculture technology, etc. (<xref ref-type="bibr" rid="ref1">Adnan et al., 2019</xref>; <xref ref-type="bibr" rid="ref49">Xiang and Guo, 2023</xref>; <xref ref-type="bibr" rid="ref37">Sarkar et al., 2022</xref>). It is a powerful tool for predicting behavior and intention (<xref ref-type="bibr" rid="ref33">Rahmaninkoshkaki and Zarei, 2018</xref>). Thus, it is also an advantageous tool for analyzing farmers&#x2019; intention to adopt Hc-FUT.</p>
<p>Scientifically and effectively exploring the rational utilization and promotion of Hc stems and leaves will contribute to expanding income channels in the Hc industry, realizing a low-carbon green cycle, and supporting the country in achieving the &#x201C;dual carbon&#x201D; goal. This is a new proposition for promoting farmer income growth and rural ecological revitalization, especially for the Hc-planting areas in Datong City, Shanxi Province, and throughout the country. To further promote the use of Hc-FUT, we conducted field research to investigate the willingness of 225 households in Datong City to adopt Hc-FUT and the core factors affecting farmers&#x2019; willingness to adopt it. Finally, policy recommendations were proposed based on the problems encountered during the promotion process. This study aims to promote the sustainable development of the Hc industry along a &#x201C;green, efficient, and circular&#x201D; path, increase the supply of forage, and protect China&#x2019;s food safety in multiple ways.</p>
</sec>
<sec id="sec5">
<label>2</label>
<title>Theoretical introduction and research hypotheses</title>
<sec id="sec6">
<label>2.1</label>
<title>Theoretical introduction</title>
<p>TPB states that an individual&#x2019;s behavior (B) is largely influenced by their intention (I) to perform the behavior, which, in turn, is influenced by their behavioral attitude (BA), subjective norms (SN), and perceived behavioral control (PBC). Among these, behavioral attitude refers to the degree to which an individual likes or dislikes the execution of the behavior; Subjective norms refer to the social pressure that individuals feel when performing the behavior, manifested specifically as the influence of others or groups on decision-makers; Perceived behavioral control refers to the degree of difficulty an individual feels when performing a certain behavior, reflecting both their prior experience and anticipated difficulties. TPB also posits that subjective norms shape behavioral attitudes through the internalization of social pressures or group values (<xref ref-type="bibr" rid="ref3">Ajzen, 1991</xref>; <xref ref-type="bibr" rid="ref31">Pan and Wang, 2018</xref>). <xref ref-type="bibr" rid="ref10">Conner and Armitage (1998)</xref> further extended this framework by proposing that perceived behavioral control (PBC) not only directly influences behavioral intentions but also reinforces positive evaluations of behavioral outcomes (attitudes) through enhanced behavioral confidence. This theory primarily considers both internal and external factors, examining the connections between individuals, society, and the environment, and analyzing the transformation process of ideological concepts and behaviors in the actual decision-making process of individuals. This helps us understand how people change their behavior patterns (<xref ref-type="bibr" rid="ref12">Daxini et al., 2019</xref>; <xref ref-type="bibr" rid="ref20">Hyland et al., 2018</xref>; <xref ref-type="bibr" rid="ref38">Senger et al., 2017</xref>).</p>
</sec>
<sec id="sec7">
<label>2.2</label>
<title>Research hypotheses</title>
<p>Based on the analysis of TPB, farmers&#x2019; intention to adopt Hc-FUT is affected by their attitude, subjective norms, and perceived behavioral control, subjective norms and perceived behavioral control can positively influence behavioral attitudes. According to the survey results of farmers in Yunzhou District, Datong City (<xref ref-type="table" rid="tab1">Table 1</xref>), only 36.4% of farmers had heard of Hc-FUT, and most farmers were unfamiliar with this technology, so farmers&#x2019; attitudes toward agricultural technologies are likely shaped by a combination of external and internal factors, including government policies, social advocacy, self-efficacy, and resource availability. Empirical studies corroborate this multidimensional influence: <xref ref-type="bibr" rid="ref31">Pan and Wang (2018)</xref> demonstrated in eco-tourism research that subjective norms indirectly enhance environmental behavioral intentions through their effect on specific environmental attitudes. Similarly, <xref ref-type="bibr" rid="ref44">Wang et al. (2023)</xref> revealed in a study on farmers&#x2019; biopesticide adoption that both subjective norms and perceived behavioral control (e.g., perceived efficacy and ease of implementation) exert significant positive impacts on behavioral attitudes. Therefore, we can reasonably infer that the attitude toward adopting this technology will be influenced by one&#x2019;s cognition, conditions, and the surrounding environment. Thus, behavioral attitudes may be affected by subjective norms and perceived behavioral control. Based on this, we propose the following hypotheses:</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Farmers&#x2019; views and opinions of the Hc-FUT.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Investigate question</th>
<th align="center" valign="top" colspan="2">&#x201C;Yes&#x201D;</th>
<th align="center" valign="top" colspan="2">&#x201C;No&#x201D;</th>
<th align="center" valign="top" colspan="3">Reason, number, and proportion of &#x201C;No&#x201D;</th>
</tr>
<tr>
<th align="center" valign="top">Number of people</th>
<th align="center" valign="top">Proportion</th>
<th align="center" valign="top">Number of people</th>
<th align="center" valign="top">Proportion</th>
<th align="center" valign="top">Reason</th>
<th align="center" valign="top">Number of people</th>
<th align="center" valign="top">Proportion</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="5">Can the stems and leaves of Hc be utilized as forage?</td>
<td align="center" valign="middle" rowspan="5">118</td>
<td align="center" valign="middle" rowspan="5">52.4%</td>
<td align="center" valign="middle" rowspan="5">107</td>
<td align="center" valign="middle" rowspan="5">47.6%</td>
<td align="center" valign="middle">They do not raise livestock, so they are unclear</td>
<td align="center" valign="middle">57</td>
<td align="center" valign="middle">53.3%</td>
</tr>
<tr>
<td align="center" valign="middle">Hc stems and leaves lack nutrients</td>
<td align="center" valign="middle">16</td>
<td align="center" valign="middle">14.0%</td>
</tr>
<tr>
<td align="center" valign="middle">Burning is more convenient and can reduce pests and diseases</td>
<td align="center" valign="middle">11</td>
<td align="center" valign="middle">10.3%</td>
</tr>
<tr>
<td align="center" valign="middle">Harvesting the stems and leaves of Hc is troublesome and has little value</td>
<td align="center" valign="middle">18</td>
<td align="center" valign="middle">16.8%</td>
</tr>
<tr>
<td align="center" valign="middle">There is enough forage for livestock</td>
<td align="center" valign="middle">6</td>
<td align="center" valign="middle">5.6%</td>
</tr>
<tr>
<td align="left" valign="middle">Whether you have heard of the Hc-FUT?</td>
<td align="center" valign="middle">82</td>
<td align="center" valign="middle">36.4%</td>
<td align="center" valign="middle">143</td>
<td align="center" valign="middle">63.6%</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle" rowspan="8">Whether you are willing to try the Hc-FUT?</td>
<td align="center" valign="middle" rowspan="8">100</td>
<td align="center" valign="middle" rowspan="8">44.4%</td>
<td align="center" valign="middle" rowspan="8">125</td>
<td align="center" valign="middle" rowspan="8">55.6%</td>
<td align="center" valign="middle">It has a high cutting cost</td>
<td align="center" valign="middle">7</td>
<td align="center" valign="middle">6.7%</td>
</tr>
<tr>
<td align="center" valign="middle">Hc stems and leaves have no market</td>
<td align="center" valign="middle">12</td>
<td align="center" valign="middle">11.4%</td>
</tr>
<tr>
<td align="center" valign="middle">There is a lack of understanding of Hc-FUT</td>
<td align="center" valign="middle">39</td>
<td align="center" valign="middle">37.1%</td>
</tr>
<tr>
<td align="center" valign="middle">Lack of cutting funds</td>
<td align="center" valign="middle">39</td>
<td align="center" valign="middle">37.1%</td>
</tr>
<tr>
<td align="center" valign="middle">Lack of labor power</td>
<td align="center" valign="middle">52</td>
<td align="center" valign="middle">49.5%</td>
</tr>
<tr>
<td align="center" valign="middle">Not planting Hc</td>
<td align="center" valign="middle">20</td>
<td align="center" valign="middle">19.0%</td>
</tr>
<tr>
<td align="center" valign="middle">Worried about affecting the yield of Hc</td>
<td align="center" valign="middle">11</td>
<td align="center" valign="middle">10.5%</td>
</tr>
<tr>
<td align="center" valign="middle">There is enough forage for livestock</td>
<td align="center" valign="middle">10</td>
<td align="center" valign="middle">9.5%</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="3">When do you think cutting the stems and leaves of Hc will not affect its yield in the following year?</td>
<td rowspan="3"/>
<td rowspan="3"/>
<td rowspan="3"/>
<td rowspan="3"/>
<td align="center" valign="middle">1&#x2013;2&#x202F;months after picking Hc flowers.</td>
<td align="center" valign="middle">65</td>
<td align="center" valign="middle">28.9%</td>
</tr>
<tr>
<td align="center" valign="middle">After 1/3 of the Hc stems and leaves withered</td>
<td align="center" valign="middle">82</td>
<td align="center" valign="middle">36.4%</td>
</tr>
<tr>
<td align="center" valign="middle">The end of October to the end of November</td>
<td align="center" valign="middle">78</td>
<td align="center" valign="middle">34.7%</td>
</tr>
</tbody>
</table>
</table-wrap>
<disp-quote>
<p><italic>H1</italic>: Behavioral attitude has a significantly positive impact on farmers&#x2019; intention to adopt Hc-FUT.</p>
</disp-quote>
<disp-quote>
<p><italic>H2</italic>: Subjective norms have a significantly positive impact on farmers&#x2019; intention to adopt Hc-FUT.</p>
</disp-quote>
<disp-quote>
<p><italic>H3</italic>: Perceived behavioral control has a significant positive impact on farmers&#x2019; intention to adopt Hc-FUT.</p>
</disp-quote>
<disp-quote>
<p><italic>H4</italic>: Perceived behavioral control has a significant positive impact on behavioral attitude.</p>
</disp-quote>
<disp-quote>
<p><italic>H5</italic>: Subjective norms have a significant positive impact on behavioral attitude.</p>
</disp-quote>
<p>Based on these hypotheses, a model was constructed, as shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Hypothesis model.</p>
</caption>
<graphic xlink:href="fsufs-09-1506842-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Flowchart depicting relationships between constructs: Subjective Norms (SN) influence Behavioral Attitude (BA) and Intention (I) via Hypotheses H5 and H2, respectively. Perceived Behavioral Control (PBC) impacts BA and I via Hypotheses H4 and H3. BA affects I through Hypothesis H1.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="materials|methods" id="sec8">
<label>3</label>
<title>Materials and methods</title>
<sec id="sec9">
<label>3.1</label>
<title>Data source</title>
<sec id="sec10">
<label>3.1.1</label>
<title>Study area</title>
<p>Shanxi Province is located in the middle of the Yellow River Basin, with a total area of 156,700 square kilometers, accounting for 1.6% of the total area of the country. Shanxi Province has a large population and limited land resources, leading to shortages of land and water resources (<xref ref-type="bibr" rid="ref54">Zhang et al., 2024</xref>). This study used a stratified random sampling method. A total of five townships, namely Dangliuzhuang Township, Jijia Township, Jule Township, Xiping Town, and Xubao Township in Yunzhou District, Datong City, Shanxi Province, were selected as the research areas. The research team conducted on-site household surveys in the research area in April 2024.</p>
</sec>
<sec id="sec11">
<label>3.1.2</label>
<title>Survey overview</title>
<p>Before conducting the formal research, a pre-survey was conducted by randomly selecting 10 farmers within the research area. The questionnaire was revised and improved based on the survey results. After these modifications, formal research began. A total of 235 questionnaires were distributed during the formal survey; after removing 10 invalid questionnaires, 225 valid questionnaires were collected, with an effective recovery rate of 95.74%. The distribution of the number of surveyed farmers is shown in <xref ref-type="table" rid="tab2">Table 2</xref>. This study investigated farmers&#x2019; awareness of and willingness to adopt Hc-FUT. Overall, farmers had a certain level of understanding regarding the utilization of Hc stems and leaves; however, their degree of understanding of Hc-FUT was relatively low. Of the farmers surveyed, 52.4% believed that Hc stems and leaves could be utilized as forage, 36.4% had heard of Hc-FUT, and 44.4% were willing to try it. The specific views and opinions of the farmers are shown in <xref ref-type="table" rid="tab1">Table 1</xref>.</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Distribution of farmers investigation.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">City investigation</th>
<th align="center" valign="top">Townships (towns) investigation</th>
<th align="center" valign="top">The number of samples</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="5">Yunzhou District of Datong City</td>
<td align="center" valign="top">Dangliuzhuang Township</td>
<td align="center" valign="top">28</td>
</tr>
<tr>
<td align="center" valign="top">Jijia Township</td>
<td align="center" valign="top">24</td>
</tr>
<tr>
<td align="center" valign="top">Jule Township</td>
<td align="center" valign="top">58</td>
</tr>
<tr>
<td align="center" valign="top">Xiping Town</td>
<td align="center" valign="top">85</td>
</tr>
<tr>
<td align="center" valign="top">Xubao Township</td>
<td align="center" valign="top">36</td>
</tr>
<tr>
<td align="left" valign="middle">Total</td>
<td align="center" valign="middle">5</td>
<td align="center" valign="middle">225</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec id="sec12">
<label>3.2</label>
<title>Variable and model selection</title>
<sec id="sec13">
<label>3.2.1</label>
<title>Variable and model</title>
<p>The variables are selected in two parts. The first part includes the four main characteristics. In terms of research on farmers&#x2019; willingness to adopt technology, scholars have categorized the factors influencing farmers&#x2019; willingness to adopt agricultural technology into personal characteristics, family characteristics, planting characteristics, and other characteristics. Personal characteristics mainly include gender, age, education level, etc. (<xref ref-type="bibr" rid="ref5">Burton, 2014</xref>; <xref ref-type="bibr" rid="ref13">Giua et al., 2022</xref>; <xref ref-type="bibr" rid="ref39">Serebrennikov et al., 2020</xref>); family characteristics mainly include the labor force, income, expenditure, etc. (<xref ref-type="bibr" rid="ref11">Cui et al., 2022</xref>; <xref ref-type="bibr" rid="ref36">Sardianou and Genoudi, 2013</xref>); planting characteristics mainly include planting area (<xref ref-type="bibr" rid="ref29">Mi et al., 2021</xref>), and whether the farm has suffered from natural disasters (<xref ref-type="bibr" rid="ref23">Khodadad et al., 2022</xref>), etc.; other characteristics include financial support (<xref ref-type="bibr" rid="ref61">Zhou et al., 2022</xref>), technological innovation (<xref ref-type="bibr" rid="ref22">Khan et al., 2022</xref>), etc. In this section, we use a logistic regression model to analyze the data.</p>
<p>The second part is based on the TPB. According to the TPB, we selected four latent variables and set the corresponding observation variables, each of which is reflected by multiple observed variables. We consider adoption intention as the dependent variable, while behavioral attitude, subjective norms, and perceived behavioral control are the independent variables. Structural Equation Modeling (SEM) is a data analysis method that allows the detection of relationships between multiple variables in the model (<xref ref-type="bibr" rid="ref24">Khoshmaram et al., 2020</xref>). Therefore, we used SEM to analyze the data in this section.</p>
</sec>
<sec id="sec14">
<label>3.2.2</label>
<title>Variable statistics of logistic regression model</title>
<p>In the logistic regression model, the dependent variable is &#x201C;whether the farmer is willing to adopt Hc-FUT.&#x201D; &#x201C;Y&#x202F;=&#x202F;0&#x201D; represents that the farmer is unwilling, while &#x201C;Y&#x202F;=&#x202F;1&#x201D; represents that the farmer is willing. The independent variables include personal, family, planting, and other characteristics, with a total of 18 indices. The specific variables and measures are shown in <xref ref-type="table" rid="tab3">Table 3</xref>.</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Variable meanings and descriptive statistics.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Variable</th>
<th align="center" valign="top">Definition and measurement</th>
<th align="center" valign="top">Expected sign</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Planting intention (Y)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Willing; 0&#x202F;=&#x202F;Unwilling</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Gender (X1)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Male; 0&#x202F;=&#x202F;Female</td>
<td align="center" valign="middle">+/&#x2212;</td>
</tr>
<tr>
<td align="left" valign="middle">Is he/she the head of the household? (X2)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Yes; 0&#x202F;=&#x202F;No</td>
<td align="center" valign="middle">+/&#x2212;</td>
</tr>
<tr>
<td align="left" valign="middle">Age (X3)</td>
<td align="center" valign="middle">Assign values based on the actual situation</td>
<td align="center" valign="middle">+/&#x2212;</td>
</tr>
<tr>
<td align="left" valign="middle">Degree of education (X4)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Lower than junior middle school; 2&#x202F;=&#x202F;Junior middle school; 3&#x202F;=&#x202F;High school; 4&#x202F;=&#x202F;University and above</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Health condition (X5)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Very bad; 2&#x202F;=&#x202F;Bad; 3&#x202F;=&#x202F;Common; 4&#x202F;=&#x202F;Good; 5&#x202F;=&#x202F;Very good</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Attitude toward risk (X6)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Conservative; 2&#x202F;=&#x202F;Steadiness; 3&#x202F;=&#x202F;Adventurous</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Actual number of agricultural labor force in the family (X7)</td>
<td align="center" valign="middle">Assign values based on actual situation</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Occupational status (X8)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Farmer; 2&#x202F;=&#x202F;Farming and working part-time; 3&#x202F;=&#x202F;Worker;</td>
<td align="center" valign="middle">&#x2212;</td>
</tr>
<tr>
<td align="left" valign="middle">Whether to raise livestock or not (X9)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Yes; 0&#x202F;=&#x202F;No</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Land area (hm<sup>2</sup>) (X10)</td>
<td align="center" valign="middle">Assign values based on actual situation</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Is the land contiguous? (X11)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Yes; 0&#x202F;=&#x202F;No</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Whether to rent land or not? (X12)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Yes; 0&#x202F;=&#x202F;No</td>
<td align="center" valign="middle">+/&#x2212;</td>
</tr>
<tr>
<td align="left" valign="middle">Fertility level of land (X13)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Very fertile; 2&#x202F;=&#x202F;Fertile; 3&#x202F;=&#x202F;Common; 4&#x202F;=&#x202F;Barren; 5&#x202F;=&#x202F;Very barren</td>
<td align="center" valign="middle">&#x2212;</td>
</tr>
<tr>
<td align="left" valign="middle">Irrigation conditions (X14)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Very bad; 2&#x202F;=&#x202F;Bad; 3&#x202F;=&#x202F;Common; 4&#x202F;=&#x202F;Good; 5&#x202F;=&#x202F;Very good</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Planting area of Hc (hm<sup>2</sup>) (X15)</td>
<td align="center" valign="middle">Assign values based on actual situation</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Have natural disasters occurred in agricultural production in recent years? (X16)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Yes; 0&#x202F;=&#x202F;No</td>
<td align="center" valign="middle">&#x2212;</td>
</tr>
<tr>
<td align="left" valign="middle">Do you think the stems and leaves of yellow flowers can be used as feed through processing or other methods? (X17)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Yes; 0&#x202F;=&#x202F;No</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Have you ever fed livestock with yellow flower stems and leaves? (X18)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Yes; 0&#x202F;=&#x202F;No</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">Government support intensity (X19)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Very unsupported; 2&#x202F;=&#x202F;Unsupported; 3&#x202F;=&#x202F;Common; 4&#x202F;=&#x202F;Support; 5&#x202F;=&#x202F;Very support</td>
<td align="center" valign="middle">+</td>
</tr>
<tr>
<td align="left" valign="middle">The number of people planting yellow flowers around (X20)</td>
<td align="center" valign="middle">1&#x202F;=&#x202F;Very little; 2&#x202F;=&#x202F;Little; 3&#x202F;=&#x202F;Common; 4&#x202F;=&#x202F;Many; 5&#x202F;=&#x202F;A lot</td>
<td align="center" valign="middle">+</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec15">
<label>3.2.3</label>
<title>Variable statistics of SEM</title>
<p>There were four latent variables (behavioral intention, attitude toward behavior, subjective norms, and perceived behavioral control), and each latent variable had multiple corresponding observed variables. A 5-level Likert scale was adopted to measure the observed variables, with values ranging from 1 to 5 representing &#x201C;completely disagree&#x201D; to &#x201C;completely agree,&#x201D; respectively. The selection of observation variables and data statistics are shown in <xref ref-type="table" rid="tab4">Table 4</xref>.</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Variable selection and data statistic.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Latent variable</th>
<th align="center" valign="top">Measurement questions</th>
<th align="center" valign="top">Dimension</th>
<th align="center" valign="top">Source</th>
<th align="center" valign="top">Mean value</th>
<th align="center" valign="top">Standard deviation</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" rowspan="2">Intention (I)</td>
<td align="center" valign="middle">You are willing to adopt the Hc-FUT (I1)</td>
<td align="center" valign="middle">Behavioral tendency</td>
<td align="center" valign="middle" rowspan="2"><xref ref-type="bibr" rid="ref50">Xiao (2016)</xref> and <xref ref-type="bibr" rid="ref2">Ahmmadi et al. (2021)</xref></td>
<td align="center" valign="middle">2.83</td>
<td align="center" valign="middle">1.34</td>
</tr>
<tr>
<td align="center" valign="middle">You plan to adopt the Hc-FUT next year (I2)</td>
<td align="center" valign="middle">Future commitment</td>
<td align="center" valign="middle">2.32</td>
<td align="center" valign="middle">1.16</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="3">Attitude (A)</td>
<td align="center" valign="middle">The Hc-FUT can help livestock grow better (A1)</td>
<td align="center" valign="middle">Production</td>
<td align="center" valign="middle" rowspan="3"><xref ref-type="bibr" rid="ref2">Ahmmadi et al. (2021)</xref> and <xref ref-type="bibr" rid="ref18">Holland and Hill (2007)</xref></td>
<td align="center" valign="middle">3.28</td>
<td align="center" valign="middle">0.98</td>
</tr>
<tr>
<td align="center" valign="middle">The Hc-FUT can generate more income (A2)</td>
<td align="center" valign="middle">Economy</td>
<td align="center" valign="middle">3.45</td>
<td align="center" valign="middle">0.93</td>
</tr>
<tr>
<td align="center" valign="middle">The Hc-FUT is beneficial to the environment (A3)</td>
<td align="center" valign="middle">Environment</td>
<td align="center" valign="middle">3.64</td>
<td align="center" valign="middle">0.93</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="3">Subjective norms (SN)</td>
<td align="center" valign="middle">Government supports the Hc-FUT (SN1)</td>
<td align="center" valign="middle">Governmental guidance</td>
<td align="center" valign="middle" rowspan="3">
<xref ref-type="bibr" rid="ref35">Roh et al. (2022)</xref>
</td>
<td align="center" valign="middle">2.95</td>
<td align="center" valign="middle">0.99</td>
</tr>
<tr>
<td align="center" valign="middle">Many people adopt the Hc-FUT (SN2)</td>
<td align="center" valign="middle">Community pressure</td>
<td align="center" valign="middle">2.23</td>
<td align="center" valign="middle">0.90</td>
</tr>
<tr>
<td align="center" valign="middle">If someone recommends the Hc-FUT to you, would you be willing to try it? (SN3)</td>
<td align="center" valign="middle">Compliance propensity</td>
<td align="center" valign="middle">2.92</td>
<td align="center" valign="middle">1.33</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="3">Perceived behavioral control (PBC)</td>
<td align="center" valign="middle">Your mechanical conditions are not suitable for the Hc-FUT (PBC1)</td>
<td align="center" valign="middle">Mechanical conditions</td>
<td align="center" valign="middle" rowspan="3">
<xref ref-type="bibr" rid="ref40">Shi et al. (2017)</xref>
</td>
<td align="center" valign="middle">3.43</td>
<td align="center" valign="middle">0.95</td>
</tr>
<tr>
<td align="center" valign="middle">Your labor force is insufficient for the Hc-FUT (PBC2)</td>
<td align="center" valign="middle">Labor force</td>
<td align="center" valign="middle">3.52</td>
<td align="center" valign="middle">1.00</td>
</tr>
<tr>
<td align="center" valign="middle">You have not mastered the knowledge and techniques required for the Hc-FUT (PBC3)</td>
<td align="center" valign="middle">Knowledge</td>
<td align="center" valign="middle">3.83</td>
<td align="center" valign="middle">1.00</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>In SPSS, principal component analysis was applied to the above variables for factor dimensionality reduction, and the rotated factor loadings were calculated to validate the scale&#x2019;s rationality. The results are shown in <xref ref-type="table" rid="tab5">Tables 5</xref>, <xref ref-type="table" rid="tab6">6</xref>. The factor dimensionality reduction results indicated that three factors could be extracted from the above variables. The rotated factor loadings showed that the coefficients for the observed variables of each latent variable were all greater than 0.5. Notably, the observed variables for Intention and Subjective Norm belonged to the same component, suggesting a strong connection between Intention and Subjective Norm.</p>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Total variance explained.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Component</th>
<th align="center" valign="top" colspan="3">Initial Eigenvalues</th>
<th align="center" valign="top" colspan="3">Extraction Sums of Squared Loadings</th>
<th align="center" valign="top" colspan="3">Rotation Sums of Squared Loadings</th>
</tr>
<tr>
<th align="center" valign="top">Total</th>
<th align="center" valign="top">% of Variance</th>
<th align="center" valign="top">Cumulative %</th>
<th align="center" valign="top">Total</th>
<th align="center" valign="top">% of Variance</th>
<th align="center" valign="top">Cumulative %</th>
<th align="center" valign="top">Total</th>
<th align="center" valign="top">% of Variance</th>
<th align="center" valign="top">Cumulative %</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="center" valign="middle">5.778</td>
<td align="center" valign="middle">52.526</td>
<td align="center" valign="middle">52.526</td>
<td align="center" valign="middle">5.778</td>
<td align="center" valign="middle">52.526</td>
<td align="center" valign="middle">52.526</td>
<td align="center" valign="middle">4.032</td>
<td align="center" valign="middle">36.654</td>
<td align="center" valign="middle">36.654</td>
</tr>
<tr>
<td align="left" valign="middle">2</td>
<td align="center" valign="middle">1.524</td>
<td align="center" valign="middle">13.851</td>
<td align="center" valign="middle">66.377</td>
<td align="center" valign="middle">1.524</td>
<td align="center" valign="middle">13.851</td>
<td align="center" valign="middle">66.377</td>
<td align="center" valign="middle">2.393</td>
<td align="center" valign="middle">21.756</td>
<td align="center" valign="middle">58.410</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="center" valign="middle">1.149</td>
<td align="center" valign="middle">10.447</td>
<td align="center" valign="middle">76.824</td>
<td align="center" valign="middle">1.149</td>
<td align="center" valign="middle">10.447</td>
<td align="center" valign="middle">76.824</td>
<td align="center" valign="middle">2.025</td>
<td align="center" valign="middle">18.413</td>
<td align="center" valign="middle">76.824</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="center" valign="middle">0.565</td>
<td align="center" valign="middle">5.140</td>
<td align="center" valign="middle">81.964</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">5</td>
<td align="center" valign="middle">0.507</td>
<td align="center" valign="middle">4.609</td>
<td align="center" valign="middle">86.572</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap position="float" id="tab6">
<label>Table 6</label>
<caption>
<p>Rotated component matrix.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Variable</th>
<th align="center" valign="top" colspan="3">Component</th>
</tr>
<tr>
<th align="center" valign="top">1</th>
<th align="center" valign="top">2</th>
<th align="center" valign="top">3</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">I1</td>
<td align="center" valign="middle">0.857</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">I2</td>
<td align="center" valign="middle">0.857</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">A1</td>
<td/>
<td align="center" valign="middle">0.770</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">A2</td>
<td/>
<td align="center" valign="middle">0.820</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">A3</td>
<td/>
<td align="center" valign="middle">0.876</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">SN1</td>
<td align="center" valign="middle">0.808</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">SN2</td>
<td align="center" valign="middle">0.827</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">SN3</td>
<td align="center" valign="middle">0.847</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">PBC1</td>
<td/>
<td/>
<td align="center" valign="middle">0.878</td>
</tr>
<tr>
<td align="left" valign="middle">PBC2</td>
<td/>
<td/>
<td align="center" valign="middle">0.836</td>
</tr>
<tr>
<td align="left" valign="middle">PBC3</td>
<td/>
<td/>
<td align="center" valign="middle">0.537</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec id="sec16">
<label>3.3</label>
<title>Model building</title>
<sec id="sec17">
<label>3.3.1</label>
<title>Logistic regression model</title>
<p>The logistic regression model is an effective tool for studying the factors that influence farmers&#x2019; adoption intention. Given independent variables X&#x202F;=&#x202F;(x<sub>1</sub>, x<sub>2</sub>, &#x2026;, x<sub>n</sub>) and parameters <italic>&#x03B2;</italic>&#x202F;=&#x202F;(<italic>&#x03B2;</italic><sub>0</sub>, <italic>&#x03B2;</italic><sub>1</sub>, &#x2026;, <italic>&#x03B2;</italic><sub>n</sub>), the linear combination is <xref ref-type="disp-formula" rid="E1">Equation 1</xref>:</p>
<disp-formula id="E1">
<label>(1)</label>
<mml:math id="M1">
<mml:mi>z</mml:mi>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>&#x03B2;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>&#x03B2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>&#x03B2;</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mo>&#x22EF;</mml:mo>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>&#x03B2;</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:math>
</disp-formula>
<p>In <xref ref-type="disp-formula" rid="E2">Equation 2</xref>: The linear output z is transformed into a probability <italic>P</italic>(Y&#x202F;=&#x202F;1|X) via the Sigmoid function:</p>
<disp-formula id="E2">
<label>(2)</label>
<mml:math id="M2">
<mml:mi>P</mml:mi>
<mml:mo stretchy="true">(</mml:mo>
<mml:mi>Y</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>&#x2223;</mml:mo>
<mml:mi>X</mml:mi>
<mml:mo stretchy="true">)</mml:mo>
<mml:mo>=</mml:mo>
<mml:mi>&#x03C3;</mml:mi>
<mml:mo stretchy="true">(</mml:mo>
<mml:mi>z</mml:mi>
<mml:mo stretchy="true">)</mml:mo>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mn>1</mml:mn>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>+</mml:mo>
<mml:msup>
<mml:mi>e</mml:mi>
<mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>z</mml:mi>
</mml:mrow>
</mml:msup>
</mml:mrow>
</mml:mfrac>
</mml:math>
</disp-formula>
<p>The linear component of binary logistic regression corresponds to the log-odds of the event probability:</p>
<disp-formula id="E3">
<label>(3)</label>
<mml:math id="M3">
<mml:mo>ln</mml:mo>
<mml:mo stretchy="true">(</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>P</mml:mi>
<mml:mo stretchy="true">(</mml:mo>
<mml:mi>Y</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>&#x2223;</mml:mo>
<mml:mi>X</mml:mi>
<mml:mo stretchy="true">)</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>P</mml:mi>
<mml:mo stretchy="true">(</mml:mo>
<mml:mi>Y</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>&#x2223;</mml:mo>
<mml:mi>X</mml:mi>
<mml:mo stretchy="true">)</mml:mo>
</mml:mrow>
</mml:mfrac>
<mml:mo stretchy="true">)</mml:mo>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>&#x03B2;</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>&#x03B2;</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>x</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mo>&#x22EF;</mml:mo>
<mml:msub>
<mml:mi>&#x03B2;</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
<mml:msub>
<mml:mi>x</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:math>
</disp-formula>
<p>In <xref ref-type="disp-formula" rid="E3">Equation 3</xref>, dependent variable <italic>Y</italic> is a binary variable (0 or 1) representing the classification outcome, independent variables <italic>X</italic> is Continuous or discrete feature variables, parameters <italic>&#x03B2;</italic> is estimated via maximum likelihood estimation (MLE), indicating the direction and magnitude of each variable&#x2019;s contribution to the probability, and the role of sigmoid function is maps the linear output <italic>z</italic> to the interval (0, 1), enabling probabilistic interpretation.</p>
</sec>
<sec id="sec18">
<label>3.3.2</label>
<title>Structural equation modeling</title>
<p>Structural Equation Modeling (SEM) is a data analysis method that allows the detection of relationships between multiple variables in a model (<xref ref-type="bibr" rid="ref24">Khoshmaram et al., 2020</xref>). This method also considers measurement errors, allowing the investigator to report the data analysis while accounting for these errors (<xref ref-type="bibr" rid="ref15">Hair et al., 2017</xref>). The specific forms of SEM are as follows:</p>
<disp-formula id="EQ4">
<label>(4)</label>
<mml:math id="M4">
<mml:mi>&#x03B7;</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi mathvariant="italic">B&#x03B7;</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi mathvariant="italic">&#x0393;&#x03BE;</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>&#x03C2;</mml:mi>
</mml:math>
</disp-formula>
<disp-formula id="EQ5">
<label>(5)</label>
<mml:math id="M5">
<mml:mi mathvariant="normal">X</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi mathvariant="italic">&#x039B;x</mml:mi>
<mml:mspace width="0.1em"/>
<mml:mi>&#x03BE;</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>&#x03B4;</mml:mi>
</mml:math>
</disp-formula>
<disp-formula id="EQ6">
<label>(6)</label>
<mml:math id="M6">
<mml:mi mathvariant="normal">Y</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi mathvariant="italic">&#x039B;y&#x03B7;</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>&#x03B5;</mml:mi>
</mml:math>
</disp-formula>
<p>In <xref ref-type="disp-formula" rid="EQ4">Equation 4</xref>: <italic>&#x0392;</italic> represents the relationship between endogenous variables, <italic>&#x0393;</italic> represents the impact of <italic>&#x03BE;</italic> (external latent variable) on <italic>&#x03B7;</italic> (internal latent variable). <italic>&#x03B6;</italic> represents the vector of residual terms of the structural model, reflecting the part of <italic>&#x03B7;</italic> that could not be explained in the structural model. In <xref ref-type="disp-formula" rid="EQ5">Equations 5</xref>, <xref ref-type="disp-formula" rid="EQ6">6</xref>, <italic>X</italic> and <italic>Y</italic> represent the exogenous dominant variables, <italic>&#x039B;x</italic> and <italic>&#x039B;y</italic> represent the factor load of <italic>X</italic> and <italic>Y, re</italic>spectively; <italic>&#x03BE;</italic> and <italic>&#x03B7;</italic> represent the exogenous latent variables and endogenous latent variables, respectively; <italic>&#x03B4;</italic> and <italic>&#x03B5;</italic> represent the measurement errors of <italic>X</italic> and <italic>Y, resp</italic>ectively, where <italic>&#x03B5;</italic> is not correlated with <italic>&#x03B7;</italic>, <italic>&#x03BE;</italic>, and <italic>&#x03B4;</italic>, and <italic>&#x03B4;</italic> is not correlated with <italic>&#x03BE;</italic>, <italic>&#x03B7;</italic>, and <italic>&#x03B5;</italic>.</p>
</sec>
</sec>
</sec>
<sec sec-type="results" id="sec19">
<label>4</label>
<title>Results</title>
<sec id="sec20">
<label>4.1</label>
<title>Logistic regression results</title>
<sec id="sec21">
<label>4.1.1</label>
<title>Multicollinearity test and regression results</title>
<p>Multicollinearity is a statistical phenomenon that affects the results of logistic regression models. The Variance Inflation Factor (VIF) indicates whether a variable has a strong linear relationship with other variable: a VIF higher than 10 or tolerance (1/VIF) less than 0.1 both indicate that multicollinearity causes bias in the model. Therefore, this study first used SPSS (version 26.0) to test the multicollinearity between the variables, as shown in <xref ref-type="table" rid="tab7">Table 7</xref>.</p>
<table-wrap position="float" id="tab7">
<label>Table 7</label>
<caption>
<p>Collinearity test.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Variable</th>
<th align="center" valign="top">Collinearity statistics</th>
</tr>
<tr>
<th align="center" valign="top">VIF</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Gender (X1)</td>
<td align="center" valign="top">2.152</td>
</tr>
<tr>
<td align="left" valign="middle">Is he/she the head of household (X2)</td>
<td align="center" valign="top">2.048</td>
</tr>
<tr>
<td align="left" valign="middle">Age (X3)</td>
<td align="center" valign="top">1.313</td>
</tr>
<tr>
<td align="left" valign="middle">Degree of education (X4)</td>
<td align="center" valign="top">1.193</td>
</tr>
<tr>
<td align="left" valign="middle">Health condition (X5)</td>
<td align="center" valign="top">1.288</td>
</tr>
<tr>
<td align="left" valign="middle">Attitude toward risk (X6)</td>
<td align="center" valign="top">1.191</td>
</tr>
<tr>
<td align="left" valign="middle">Actual number of agricultural labor force in the family (X7)</td>
<td align="center" valign="top">1.249</td>
</tr>
<tr>
<td align="left" valign="middle">Occupational status (X8)</td>
<td align="center" valign="top">1.095</td>
</tr>
<tr>
<td align="left" valign="middle">Whether to raise livestock or not (X9)</td>
<td align="center" valign="top">1.163</td>
</tr>
<tr>
<td align="left" valign="middle">Land area (mu) (X10)</td>
<td align="center" valign="top">1.232</td>
</tr>
<tr>
<td align="left" valign="middle">Is the land contiguous? (X11)</td>
<td align="center" valign="top">1.208</td>
</tr>
<tr>
<td align="left" valign="middle">Whether to rent land or not? (X12)</td>
<td align="center" valign="top">1.155</td>
</tr>
<tr>
<td align="left" valign="middle">Fertility level of land (X13)</td>
<td align="center" valign="top">1.675</td>
</tr>
<tr>
<td align="left" valign="middle">Irrigation conditions (X14)</td>
<td align="center" valign="top">1.658</td>
</tr>
<tr>
<td align="left" valign="middle">Planting area of Hc (mu) (X15)</td>
<td align="center" valign="top">1.275</td>
</tr>
<tr>
<td align="left" valign="middle">Have natural disasters occurred in agricultural production in recent years? (X16)</td>
<td align="center" valign="top">1.144</td>
</tr>
<tr>
<td align="left" valign="middle">Do you think the stems and leaves of yellow flowers can be used as feed through processing or other methods? (X17)</td>
<td align="center" valign="top">1.48</td>
</tr>
<tr>
<td align="left" valign="middle">Have you ever fed livestock with yellow flower stems and leaves? (X18)</td>
<td align="center" valign="top">1.295</td>
</tr>
<tr>
<td align="left" valign="middle">Government support intensity (X19)</td>
<td align="center" valign="top">2.264</td>
</tr>
<tr>
<td align="left" valign="middle">The number of people planting yellow flowers around (X20)</td>
<td align="center" valign="top">2.255</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The tolerances of the selected independent variables are all greater than 0.1 and the VIFs are all less than 10, indicating that there is no multicollinearity among the variables. A binary logistic regression analysis was conducted using SPSS 26.0 software. This study has passed the mixed test of model coefficients, logarithmic test of maximum likelihood squared, and Hosmer Lemeshow test, confirming that the model fits the data well. The chi-square value of the model is 119.563, with a <italic>p</italic>-value of 0.000, which is less than 0.001, indicating that at least one variable coefficient among the independent variables is non-zero.</p>
</sec>
<sec id="sec22">
<label>4.1.2</label>
<title>Results of logistic regression analysis</title>
<p>The significance of each variable is shown in <xref ref-type="table" rid="tab8">Table 8</xref>. Based on the above results, we further analyze the degree and direction of influence of each independent variable on the dependent variable. The specific findings are as follows:</p>
<table-wrap position="float" id="tab8">
<label>Table 8</label>
<caption>
<p>Results of the logistic regression model.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Variable</th>
<th align="center" valign="top" colspan="2">Model 1</th>
<th align="center" valign="top" colspan="2">Model 2</th>
<th align="center" valign="top" colspan="2">Model 3</th>
</tr>
<tr>
<th align="center" valign="top">Coefficient</th>
<th align="center" valign="top">Standard error</th>
<th align="center" valign="top">Coefficient</th>
<th align="center" valign="top">Standard error</th>
<th align="center" valign="top">Coefficient</th>
<th align="center" valign="top">Standard error</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Have you ever fed livestock with yellow flower stems and leaves? (X18)</td>
<td align="center" valign="middle">1.954&#x002A;&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.501</td>
<td align="center" valign="middle">1.939&#x002A;&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.498</td>
<td align="center" valign="middle">1.97&#x002A;&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.495</td>
</tr>
<tr>
<td align="left" valign="middle">Government support intensity (X19)</td>
<td align="center" valign="middle">0.845&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.288</td>
<td align="center" valign="middle">0.863&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.285</td>
<td align="center" valign="middle">0.84&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.286</td>
</tr>
<tr>
<td align="left" valign="middle">The number of people planting yellow flowers around (X20)</td>
<td align="center" valign="middle">1.126&#x002A;&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.35</td>
<td align="center" valign="middle">1.118&#x002A;&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.349</td>
<td align="center" valign="middle">1.128&#x002A;&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.35</td>
</tr>
<tr>
<td align="left" valign="middle">constant</td>
<td align="center" valign="middle">&#x2212;4.882&#x002A;</td>
<td align="center" valign="middle">2.52</td>
<td align="center" valign="middle">&#x2212;5.351&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">2.233</td>
<td align="center" valign="middle">&#x2212;4.784&#x002A;</td>
<td align="center" valign="middle">2.484</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.1, &#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05, &#x002A;&#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.01, &#x002A;&#x002A;&#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001.</p>
</table-wrap-foot>
</table-wrap>
<p>The research has found that X18 has a significantly positive influence on adoption intentions. Analyzing the reasons based on actual research results, farmers who have used Hc stems and leaves to feed livestock have a deeper understanding of the feeding characteristics of Hc stems and leaves, resulting in a higher willingness to adopt this technology. Moreover, X19 also significantly positively influences adoption intention, mainly because the promotion of agricultural technology needs strong support from the government; the greater the government support, the higher the willingness of farmers to adopt it. Additionally, owing to geographical and kinship factors, farmers often communicate and learn agricultural techniques among themselves. The suggestions of their neighbors are frequently considered by farmers, improving their decisions. Thus, the neighborhood effect can positively influence farmers&#x2019; intentions to adopt the technology.</p>
</sec>
<sec id="sec23">
<label>4.1.3</label>
<title>Robust test</title>
<p>To verify the regression results, this study employs a method of removing certain independent variables and conducting a series of robustness tests. As shown in <xref ref-type="table" rid="tab6">Table 6</xref>, Model 2 presents the regression results after removing &#x201C;gender&#x201D; from personal characteristics, while Model 3 shows the regression results after excluding &#x201C;whether to raise livestock or not&#x201D; from family characteristics. In both cases, the three factors&#x2014; &#x201C;X18,&#x201D; &#x201C;X19,&#x201D; and &#x201C;X20&#x201D;&#x2014;continue to significantly positively influence adoption intention, and the direction of influence remains unchanged. Thus, the analysis results demonstrate robustness.</p>
</sec>
</sec>
<sec id="sec24">
<label>4.2</label>
<title>Structural equation modeling</title>
<sec id="sec25">
<label>4.2.1</label>
<title>Reliability and validity testing</title>
<p>Because this study drew on well-established scales, confirmatory factor analysis was used in this study to test the reliability and effectiveness of the model.</p>
<p>Cronbach&#x2019;s alpha and composite reliability (CR) were used to test the internal consistency of each latent variable. Convergent validity refers to the theoretical correlation between two or more items, measured by the path loading coefficient and average variance extraction (AVE). Differential validity refers to the degree to which two or more latent variables are uncorrelated with other latent variables, as measured by comparing the square root of the AVE values of each latent variable with the correlation coefficients of other latent variables. All indicators of the model were verified, and the table displays the values of each indicator (See Appendix). The Cronbach&#x2019;s alpha coefficient and combination reliability (CR) both exceeded the minimum value of 0.7 (<xref ref-type="bibr" rid="ref15">Hair et al., 2017</xref>). The factor loading coefficients were close to or greater than the threshold value of 0.7, and all AVE values were greater than 0.5. Furthermore, most of the square roots of the latent variables&#x2019; AVE values were greater than the correlation coefficients between those latent variables and other latent variables. These results indicate that the model performed well in terms of structural reliability, convergent validity, and discriminant validity.</p>
<p>The chi-square value divided by degrees of freedom (CMIN\DF), root mean square error of approximation (RMSEA), comparative fit index (CFI), goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), and normed fit index (NFI) were selected to measure the structural validity of the structural equation modeling. After analysis with Amos 26.0, the results are as follows: chi-square/degree of freedom&#x202F;=&#x202F;3.953; RMSEA&#x202F;=&#x202F;0.115; CFI&#x202F;=&#x202F;0.925; GFI&#x202F;=&#x202F;0.890; AGFI&#x202F;=&#x202F;0.821; NFI&#x202F;=&#x202F;0.903. The measured indicators suggest that the structural validity of the structural equation model is acceptable.</p>
</sec>
<sec id="sec26">
<label>4.2.2</label>
<title>Results of SEM analysis</title>
<p>The path coefficient estimation results obtained by running the research model using Amos 26.0 software are listed in <xref ref-type="table" rid="tab9">Table 9</xref>. As shown in the table, three hypotheses are supported, while two others are not. Specifically, hypotheses H2, H5, and H3 are significant at the 0.001, 0.001, and 0.05 levels, respectively, whereas H1 and H4 are not significant.</p>
<table-wrap position="float" id="tab9">
<label>Table 9</label>
<caption>
<p>Results of heterogeneity analysis.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" colspan="2">Hypotheses</th>
<th align="center" valign="top">Estimate</th>
<th align="center" valign="top">S. E.</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">Whether the hypothesis is supported or not</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">H1</td>
<td align="center" valign="top">A -&#x202F;&#x003E;&#x202F;I</td>
<td align="center" valign="top">&#x2212;0.039</td>
<td align="center" valign="top">0.072</td>
<td align="center" valign="top">0.586</td>
<td align="center" valign="top">No support</td>
</tr>
<tr>
<td align="left" valign="middle">H2</td>
<td align="center" valign="middle">SN -&#x202F;&#x003E;&#x202F;I</td>
<td align="center" valign="middle">0.982&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.063</td>
<td align="center" valign="middle">&#x003C;0.001</td>
<td align="center" valign="middle">Support</td>
</tr>
<tr>
<td align="left" valign="middle">H3</td>
<td align="center" valign="middle">PBC -&#x202F;&#x003E;&#x202F;I</td>
<td align="center" valign="middle">&#x2212;0.217&#x002A;</td>
<td align="center" valign="middle">0.092</td>
<td align="center" valign="middle">0.019</td>
<td align="center" valign="middle">Support</td>
</tr>
<tr>
<td align="left" valign="middle">H4</td>
<td align="center" valign="middle">PBC -&#x202F;&#x003E;&#x202F;A</td>
<td align="center" valign="middle">&#x2212;0.027</td>
<td align="center" valign="middle">0.112</td>
<td align="center" valign="middle">0.808</td>
<td align="center" valign="middle">No support</td>
</tr>
<tr>
<td align="left" valign="middle">H5</td>
<td align="center" valign="middle">SN -&#x202F;&#x003E;&#x202F;A</td>
<td align="center" valign="middle">0.383&#x002A;&#x002A;&#x002A;</td>
<td align="center" valign="middle">0.062</td>
<td align="center" valign="middle">&#x003C;0.001</td>
<td align="center" valign="middle">Support</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.1, &#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05, &#x002A;&#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.01, &#x002A;&#x002A;&#x002A;&#x002A;<italic>p</italic>&#x202F;&#x003C;&#x202F;0.001.</p>
</table-wrap-foot>
</table-wrap>
<sec id="sec27">
<label>4.2.2.1</label>
<title>Concretely</title>
<list list-type="order">
<list-item>
<p>Hypotheses H2 and H5 had correlation coefficients of 0.982 and 0.383, respectively, and were significant at the 0.001 level. In the study, subjective norms include three questions: &#x201C;Government supports the utilization of Hc stems and leaves as forage,&#x201D; &#x201C;Many people adopt the utilization of Hc stems and leaves as forage,&#x201D; and &#x201C;If someone recommends this technology to you, would you be willing to try it?&#x201D; This shows that the more the government supports this technology, the higher the willingness of farmers to adopt it, and the more positive attitude toward the technology. The more people around farmers adopt this technology, the higher the willingness of farmers to adopt it, and the more positive attitude toward the technology. Moreover, the more recommendations farmers receive about this technology, the higher the willingness of farmers to adopt it, and the more positive attitude toward the technology. Therefore, in the future process of technology promotion, giving full play to the organizational and driving roles of the government and others is an important direction.</p>
</list-item>
<list-item>
<p>Hypothesis H3: The correlation coefficient is &#x2212;0.217, <italic>p</italic>&#x202F;=&#x202F;0.019, and there is a significant negative correlation at the 5% level. In this study, perceived behavioral control included three aspects: mechanical conditions, labor force, and mastery of relevant technologies, showing that the better the corresponding mechanical conditions, the more abundant the labor force, and the more familiar the technology, the higher the willingness to adopt it. In the future promotion of this technology, attention should be paid to the improvement of related supporting facilities, alleviating the problem of labor shortage, and more publicity and guidance should be provided at the same time.</p>
</list-item>
<list-item>
<p>Hypotheses H1 and H4 did not pass the significance level test for two possible reasons: first, farmers who use this technology and have relevant knowledge are few. Thus, farmers judge whether to adopt technology based on their perception of their surroundings and the difficulty of implementation. Second, relevant technologies were introduced and promoted during the research period, thereby weakening farmers&#x2019; awareness of restrictive conditions.</p>
</list-item>
</list>
</sec>
</sec>
</sec>
</sec>
<sec sec-type="discussion" id="sec28">
<label>5</label>
<title>Discussion</title>
<p>By integrating logistic regression with Structural Equation Modeling (SEM), this study systematically elucidates the multifaceted mechanisms influencing farmers&#x2019; adoption intention of Hc-FUT. The logistic regression model identified three significant drivers: farmers&#x2019; prior experience of feeding livestock with <italic>Hemerocallis citrina</italic> stems and leaves (X18, <italic>&#x03B2;</italic>&#x202F;=&#x202F;2.00, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001), government support intensity (X19, <italic>&#x03B2;</italic>&#x202F;=&#x202F;0.84, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.01), and neighborhood adoption rate (X20, <italic>&#x03B2;</italic>&#x202F;=&#x202F;1.13, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). SEM path analysis further validated the psychological mechanisms underlying behavioral decisions, revealing that subjective norms exerted a significant positive influence on adoption intention (<italic>&#x03B2;</italic>&#x202F;=&#x202F;0.982, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001), consistent with findings from <xref ref-type="bibr" rid="ref31">Pan and Wang&#x2019;s (2018)</xref> ecotourism research and <xref ref-type="bibr" rid="ref7">Chen and Jiang&#x2019;s (2013)</xref> ecological construction willingness study, indicating external pressures (government/neighborhood influence) dominated adoption decisions. Subjective norms also positively affected behavioral attitudes (<italic>&#x03B2;</italic>&#x202F;=&#x202F;0.383, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001), aligning with <xref ref-type="bibr" rid="ref45">Wang et al.&#x2019;s (2023)</xref> findings. Perceived behavioral control demonstrated a positive impact on adoption intention (<italic>&#x03B2;</italic>&#x202F;=&#x202F;&#x2212;0.217, <italic>p</italic>&#x202F;=&#x202F;0.019), congruent with <xref ref-type="bibr" rid="ref30">Nhuong and Truong (2024)</xref> and <xref ref-type="bibr" rid="ref58">Zheng et al. (2024)</xref>. Notably, the attitude-intention decoupling contrasted with <xref ref-type="bibr" rid="ref1">Adnan et al.'s (2019)</xref> findings where attitudes strongly predicted green fertilizer adoption, and perceived behavioral control showed no significant effect on attitudes. Hypotheses H2, H3, and H5 were validated, whereas H1 and H4 were rejected.</p>
<p>The significant effects of X19 and X20 in logistic regression reinforce the crucial role of subjective norms in farmers&#x2019; technology adoption intention. Farmers&#x2019; prior experience of feeding livestock with <italic>Hemerocallis citrina</italic> stems and leaves exhibited stronger Hc-FUT adoption willingness, suggesting experiential learning fostered positive attitudes. However, behavioral attitudes failed to significantly influence adoption intention in SEM analysis, potentially attributable to limited technology familiarity - only 36.4% of respondents reported awareness of Hc-FUT, with merely 24% possessing relevant feeding experience (<xref ref-type="table" rid="tab1">Table 1</xref>). This knowledge deficit likely hindered attitude-to-intention conversion, consistent with findings from low-diffusion agricultural innovation studies (<xref ref-type="bibr" rid="ref37">Sarkar et al., 2022</xref>). Furthermore, the omission of risk perception variables (e.g., cost&#x2013;benefit concerns), established as critical moderators in technology adoption literature (<xref ref-type="bibr" rid="ref29">Mi et al., 2021</xref>; <xref ref-type="bibr" rid="ref13">Giua et al., 2022</xref>), might explain the unvalidated PBC&#x202F;&#x2192;&#x202F;A pathway, as risk perceptions could counteract perceived behavioral control&#x2019;s positive effects.</p>
<p>Suboptimal SEM fit indices (RMSEA&#x202F;=&#x202F;0.115, the ideal value should be &#x2264;0.08; GFI&#x202F;=&#x202F;0.890, the ideal value should be &#x2265;0.90.) indicate systematic deviations between the Theory of Planned Behavior framework and empirical data. While TPB presupposes rational individual assessments, the collectivist context of rural Shanxi, where community norms (kinship networks, neighborhood exemplars) supersede personal attitudes, may distort theoretical intention formation pathways. Sample heterogeneity further complicates model fit - the inclusion of both livestock farmers (18%) and non-farmers introduces group disparities in resource endowment and technological needs.</p>
<p>This research reveals TPB&#x2019;s distinctive manifestation in collectivist agricultural systems: Hc-FUT adoption decisions predominantly hinge on subjective norms. The non-significant attitude-intention relationship challenges TPB&#x2019;s universal assumption about attitude centrality, highlighting cultural context&#x2019;s moderating role and providing empirical evidence for TPB&#x2019;s cross-cultural adaptation. Methodologically, the integrated logistic regression-SEM framework incorporating personal characteristics, household attributes, cultivation features, and psychological cognition enhances explanatory power in agricultural technology adoption research. These findings contribute to Hc-FUT dissemination strategies and China&#x2019;s ongoing efforts to alleviate feed shortages through technological innovation.</p>
</sec>
<sec id="sec29">
<label>6</label>
<title>Recommendation</title>
<p>Through data analysis of this survey, subjective norms had the most significant impact on farmers&#x2019; willingness to adopt yellow flower stem and leaf forage technology, followed by perceived behavioral control. Although there was no significant correlation between behavioral attitude and willingness to adopt the technology, most farmers had a positive attitude toward the technology. Therefore, theoretically implementing this technology is feasible. However, in practice, the following points need to be noted.</p>
<p>First, government support is an important means of effectively promoting Hc-FUT. We suggest increasing government attention and elevating the utilization of Hc stems and leaves as forage for the strategic integrated development of the yellow flower industry in counties and cities. Corresponding subsidy policies should be issued by the government as soon as possible, and the range of subsidies should include Hc stem, leaf forage, and related machinery. The government has taken the lead in formulating quality standards for HC stem and leaf forage. Supervise the entire production, processing, and sales of Hc stems and leaf forage by establishing a quality inspection system. Forage-processing enterprises should be encouraged to develop diversified Hc stem and leaf forage products to meet different breeding needs and enhance the added value and market competitiveness of Hc stem and leaf forage. Organize relevant technical personnel to regularly conduct technical training and hold exhibitions and promotion events to enhance the renown and influence of the Datong City Hc stem and leaf forage products, thereby attracting more attention and use from breeding enterprises.</p>
<p>Second, perceived behavioral control has a significant positive impact on farmers&#x2019; willingness to adopt yellow flower stem and leaf forage technology. Therefore, effective measures should be taken to solve the problems of insufficient machinery, labor, and knowledge regarding the use of yellow flower stem and leaf forage. Relevant scientific research institutions and enterprises should coordinate to strengthen cooperation and develop and promote suitable machinery for Hc stem and leaf forage, addressing the problem of labor shortage among farmers by leveraging the coordination of professional cooperatives.</p>
<p>Third, there is a need to continue to strengthen research and innovation in Hc stem and leaf forage utilization technologies. We suggest setting up special funds for innovative research and promoting the utilization of Hc stems and leaves for forage to strengthen the scientific and technological support foundation for extending the yellow flower industry chain. For example, research and development of forage-cutting machinery, nutrient composition testing of different varieties of forage grass with different proportions and combinations, testing the feeding effect on cattle and sheep, experiments on optimal cutting time, and optimal acquisition methods. Develop technical regulations and product standards for the utilization of Hc stem and leaf forage through an agricultural technology promotion service system and popularize these technologies to a vast number of farmers. Additionally, enterprises should be guided and supported in establishing Hc stem and leaf forage collection, storage, and sales systems. They should be equipped with corresponding equipment, facilities, and markets to achieve centralized collection, storage, processing, distribution, and sales of yellow flower stems and leaf forage.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec30">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="ethics-statement" id="sec31">
<title>Ethics statement</title>
<p>Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the [patients/ participants OR patients/participants legal guardian/next of kin] was not required to participate in this study in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec sec-type="author-contributions" id="sec32">
<title>Author contributions</title>
<p>XiangjH: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Validation, Writing &#x2013; original draft. QL: Data curation, Formal analysis, Investigation, Software, Validation, Writing &#x2013; original draft. QJ: Data curation, Formal analysis, Investigation, Software, Writing &#x2013; review &#x0026; editing. MZ: Investigation, Writing &#x2013; review &#x0026; editing. ChL: Data curation, Investigation, Writing &#x2013; review &#x0026; editing. YY: Data curation, Investigation, Writing &#x2013; review &#x0026; editing. CG: Data curation, Investigation, Methodology, Writing &#x2013; review &#x0026; editing. CuL: Investigation, Writing &#x2013; review &#x0026; editing. XiangyH: Funding acquisition, Resources, Supervision, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec33">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This study was supported by the Modern Agricultural Forage Industry Technology System in Shanxi Province, Shanxi Province Key Research and Development Project (grant number: 202102140601008), Shanxi Provincial Science and Technology Department Science and Technology Strategy Special Project (grant number: 202204031401221), 2024 Science and Technology Support Project for Agricultural High-Quality Development of Shanxi Agricultural University (grant number: TYGC24-72), and Shanxi Provincial High-Level Talent Introduction Project (grant number: 2021XG006).</p>
</sec>
<ack>
<p>We thank our colleagues who assisted us during the field survey, and the farmers who patiently answered our questions during this study.</p>
</ack>
<sec sec-type="COI-statement" id="sec34">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec35">
<title>Generative AI statement</title>
<p>The authors declare that no Gen AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="sec36">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<ref-list>
<title>References</title>
<ref id="ref1"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Adnan</surname><given-names>N.</given-names></name> <name><surname>Nordin</surname><given-names>S. M.</given-names></name> <name><surname>Bahruddin</surname><given-names>M. A.</given-names></name> <name><surname>Tareq</surname><given-names>A. H.</given-names></name></person-group> (<year>2019</year>). <article-title>A state-of-the-art review on facilitating sustainable agriculture through green fertilizer technology adoption: assessing farmers behavior</article-title>. <source>Trends Food Sci. Technol.</source> <volume>86</volume>, <fpage>439</fpage>&#x2013;<lpage>452</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.tifs.2019.02.040</pub-id></citation></ref>
<ref id="ref2"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ahmmadi</surname><given-names>P.</given-names></name> <name><surname>Rahimian</surname><given-names>M.</given-names></name> <name><surname>Movahed</surname><given-names>R. G.</given-names></name></person-group> (<year>2021</year>). <article-title>Theory of planned behavior to predict consumer behavior in using products irrigated with purified wastewater in Iran consumer</article-title>. <source>J. Clean. Prod.</source> <volume>296</volume>:<fpage>126359</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jclepro.2021.126359</pub-id></citation></ref>
<ref id="ref3"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ajzen</surname><given-names>I.</given-names></name></person-group> (<year>1991</year>). <article-title>The theory of planned behavior</article-title>. <source>Organ. Behav. Hum. Decis. Process.</source> <volume>50</volume>, <fpage>179</fpage>&#x2013;<lpage>211</lpage>. doi: <pub-id pub-id-type="doi">10.1016/0749-5978(91)90020-T</pub-id></citation></ref>
<ref id="ref5"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Burton</surname><given-names>R. J. F.</given-names></name></person-group> (<year>2014</year>). <article-title>The influence of farmer demographic characteristics on environmental behavior: a review</article-title>. <source>J. Environ. Manag.</source> <volume>135</volume>, <fpage>19</fpage>&#x2013;<lpage>26</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jenvman.2013.12.005</pub-id>, PMID: <pub-id pub-id-type="pmid">24508843</pub-id></citation></ref>
<ref id="ref6"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Cai</surname><given-names>Y. Q.</given-names></name> <name><surname>Chou</surname><given-names>G. H.</given-names></name> <name><surname>Xu</surname><given-names>Z. G.</given-names></name></person-group> (<year>2011</year>). <article-title>Evaluation on potentials of energy utilization of crop residual resources in different regions of China</article-title>. <source>J. Nat. Resour.</source> <volume>26</volume>, <fpage>1637</fpage>&#x2013;<lpage>1646</lpage>.</citation></ref>
<ref id="ref7"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Chen</surname><given-names>H. T.</given-names></name> <name><surname>Jiang</surname><given-names>Z. D.</given-names></name></person-group> (<year>2013</year>). <article-title>Farmers ecological construction willingness and behavior in grain for green: data from farmer household survey in Ansai and Mizhi County</article-title>. <source>J. China Agric. Univ.</source> <volume>26</volume>, <fpage>224</fpage>&#x2013;<lpage>231</lpage>. doi: <pub-id pub-id-type="doi">10.11841/j.issn.1007-4333.2013.04.34</pub-id></citation></ref>
<ref id="ref8"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Chen</surname><given-names>Y. Q.</given-names></name> <name><surname>Liu</surname><given-names>J. Y.</given-names></name> <name><surname>Liu</surname><given-names>W. K.</given-names></name> <name><surname>Wang</surname><given-names>Q.</given-names></name></person-group> (<year>2023</year>). <article-title>Effects of red and blue light intensities on the growth, yield, and quality of perennial ryegrass</article-title>. <source>Pratacult. Sci.</source> <volume>40</volume>, <fpage>502</fpage>&#x2013;<lpage>510</lpage>. doi: <pub-id pub-id-type="doi">10.11829/j.issn.1001-0629.2022-0487</pub-id></citation></ref>
<ref id="ref9"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Clapp</surname><given-names>J.</given-names></name></person-group> (<year>2023</year>). <article-title>Concentration and crises: exploring the deep roots of vulnerability in the global industrial food system</article-title>. <source>J. Peasant Stud.</source> <volume>50</volume>, <fpage>1</fpage>&#x2013;<lpage>25</lpage>. doi: <pub-id pub-id-type="doi">10.1080/03066150.2022.2129013</pub-id></citation></ref>
<ref id="ref10"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Conner</surname><given-names>M.</given-names></name> <name><surname>Armitage</surname><given-names>C. J.</given-names></name></person-group> (<year>1998</year>). <article-title>Extending the theory of planned behavior: a review and avenues for further research</article-title>. <source>J. Appl. Soc. Psychol.</source> <volume>28</volume>, <fpage>1429</fpage>&#x2013;<lpage>1464</lpage>. doi: <pub-id pub-id-type="doi">10.1111/j.1559-1816.1998.tb01685.x</pub-id></citation></ref>
<ref id="ref11"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Cui</surname><given-names>S. L.</given-names></name> <name><surname>Li</surname><given-names>Y. J.</given-names></name> <name><surname>Jiao</surname><given-names>X. Q.</given-names></name> <name><surname>Zhang</surname><given-names>D.</given-names></name></person-group> (<year>2022</year>). <article-title>Hierarchical linkage between the basic characteristics of smallholders and technology awareness determines small-holders&#x2019; willingness to adopt green production technology</article-title>. <source>Agriculture</source> <volume>12</volume>:<fpage>1275</fpage>. doi: <pub-id pub-id-type="doi">10.3390/agriculture12081275</pub-id></citation></ref>
<ref id="ref12"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Daxini</surname><given-names>A.</given-names></name> <name><surname>Ryan</surname><given-names>M.</given-names></name> <name><surname>O&#x2019;Donoghue</surname><given-names>C.</given-names></name> <name><surname>Barnes</surname><given-names>A. P.</given-names></name> <name><surname>Buckley</surname><given-names>C.</given-names></name></person-group> (<year>2019</year>). <article-title>Using a typology to understand farmers&#x2019; intentions towards following a nutrient management plan</article-title>. <source>Resour. Conserv. Recycl.</source> <volume>146</volume>, <fpage>280</fpage>&#x2013;<lpage>290</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.resconrec.2019.03.027</pub-id></citation></ref>
<ref id="ref13"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Giua</surname><given-names>C.</given-names></name> <name><surname>Materia</surname><given-names>V. C.</given-names></name> <name><surname>Camanzi</surname><given-names>L.</given-names></name></person-group> (<year>2022</year>). <article-title>Smart farming technologies adoption: which factors play a role in the digital transition?</article-title> <source>Technol. Soc.</source> <volume>68</volume>:<fpage>101869</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.techsoc.2022.101869</pub-id></citation></ref>
<ref id="ref14"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Guo</surname><given-names>A. H.</given-names></name> <name><surname>Li</surname><given-names>S.</given-names></name> <name><surname>Yang</surname><given-names>Y.</given-names></name> <name><surname>Hou</surname><given-names>F. F.</given-names></name> <name><surname>Wu</surname><given-names>J.</given-names></name> <name><surname>Gao</surname><given-names>Y.</given-names></name> <etal/></person-group>. (<year>2022</year>). <article-title>Lecithin extraction optimisation and synthesis in <italic>Hemerocallis citrina</italic> Baroni</article-title>. <source>Sci. Hortic.</source> <volume>293</volume>:<fpage>110682</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.scienta.2021.110682</pub-id></citation></ref>
<ref id="ref15"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Hair</surname><given-names>J. F.</given-names></name> <name><surname>Hult</surname><given-names>G. T. M.</given-names></name> <name><surname>Ringle</surname><given-names>C. M.</given-names></name> <name><surname>Sarstedy</surname><given-names>M.</given-names></name> <name><surname>Thiele</surname><given-names>K. O.</given-names></name></person-group> (<year>2017</year>). <article-title>Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods</article-title>. <source>J. Acad. Mark. Sci.</source> <volume>45</volume>, <fpage>616</fpage>&#x2013;<lpage>632</lpage>. doi: <pub-id pub-id-type="doi">10.1007/s11747-017-0517-x</pub-id></citation></ref>
<ref id="ref16"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Hazra</surname><given-names>C. R.</given-names></name></person-group> (<year>2014</year>). <article-title>Feed and forage resources for sustainable livestock development</article-title>. <source>Range Range. Manag. Agrofor.</source> <volume>35</volume>, <fpage>1</fpage>&#x2013;<lpage>14</lpage>.</citation></ref>
<ref id="ref17"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>He</surname><given-names>J. X.</given-names></name> <name><surname>Sui</surname><given-names>D. C.</given-names></name></person-group> (<year>2024</year>). <article-title>Investigating college students' green food consumption intentions in China: integrating the theory of planned behavior and norm activation theory</article-title>. <source>Sustain. Food Syst.</source> <volume>8</volume>:<fpage>1404465</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fsufs.2024.1404465</pub-id></citation></ref>
<ref id="ref18"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Holland</surname><given-names>C.</given-names></name> <name><surname>Hill</surname><given-names>R.</given-names></name></person-group> (<year>2007</year>). <article-title>The effect of age, gender and driver status on pedestrians&#x2019; intentions to cross the road in risky situations</article-title>. <source>Accid. Anal. Prev.</source> <volume>39</volume>, <fpage>224</fpage>&#x2013;<lpage>237</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.aap.2006.07.003</pub-id>, PMID: <pub-id pub-id-type="pmid">16979132</pub-id></citation></ref>
<ref id="ref19"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Hou</surname><given-names>X. Y.</given-names></name></person-group> (<year>2022</year>). <article-title>The development of forage industry should do a good job in the "three non-competition"</article-title>. <source>Agri. Prod. Market</source> <volume>13</volume>, <fpage>52</fpage>&#x2013;<lpage>53</lpage>.</citation></ref>
<ref id="ref20"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Hyland</surname><given-names>J. J.</given-names></name> <name><surname>Heanue</surname><given-names>K.</given-names></name> <name><surname>McKillop</surname><given-names>J.</given-names></name> <name><surname>Micha</surname><given-names>E.</given-names></name></person-group> (<year>2018</year>). <article-title>Factors underlying farmers' intentions to adopt best practices: the case of paddock based grazing systems</article-title>. <source>Agric. Syst.</source> <volume>162</volume>, <fpage>97</fpage>&#x2013;<lpage>106</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.agsy.2018.01.023</pub-id></citation></ref>
<ref id="ref21"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Karak</surname><given-names>P.</given-names></name></person-group> (<year>2019</year>). <article-title>Biological activities of flavonoids: an overview</article-title>. <source>Int. J. Pharm. Sci. Res.</source> <volume>10</volume>, <fpage>1567</fpage>&#x2013;<lpage>1574</lpage>. doi: <pub-id pub-id-type="doi">10.13040/IJPSR.0975-8232.10(4).1567-74</pub-id></citation></ref>
<ref id="ref22"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Khan</surname><given-names>N.</given-names></name> <name><surname>Ray</surname><given-names>R. L.</given-names></name> <name><surname>Kassem</surname><given-names>H. S.</given-names></name> <name><surname>Zhang</surname><given-names>S. M.</given-names></name></person-group> (<year>2022</year>). <article-title>Mobile internet technology adoption for sustainable agriculture: evidence from wheat farmers</article-title>. <source>Appl. Sci.</source> <volume>12</volume>:<fpage>4902</fpage>. doi: <pub-id pub-id-type="doi">10.3390/app12104902</pub-id></citation></ref>
<ref id="ref23"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Khodadad</surname><given-names>M.</given-names></name> <name><surname>Sanei</surname><given-names>M.</given-names></name> <name><surname>Narvaez-Montoya</surname><given-names>C.</given-names></name> <name><surname>Aguilar-Barajas</surname><given-names>I.</given-names></name></person-group> (<year>2022</year>). <article-title>Climatic hazards and the associated impacts on households&#x2019; willingness to adopt water-saving measures: evidence from Mexico</article-title>. <source>Sustainability</source> <volume>14</volume>:<fpage>5817</fpage>. doi: <pub-id pub-id-type="doi">10.3390/su14105817</pub-id></citation></ref>
<ref id="ref24"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Khoshmaram</surname><given-names>M.</given-names></name> <name><surname>Shiri</surname><given-names>N.</given-names></name> <name><surname>Shinnar</surname><given-names>R. S.</given-names></name> <name><surname>Savari</surname><given-names>M.</given-names></name></person-group> (<year>2020</year>). <article-title>Environmental support and entrepreneurial behavior among Iranian farmers: the mediating roles of social and human capital</article-title>. <source>J. Small Bus. Manage.</source> <volume>58</volume>, <fpage>1064</fpage>&#x2013;<lpage>1088</lpage>. doi: <pub-id pub-id-type="doi">10.1111/jsbm.12501</pub-id></citation></ref>
<ref id="ref26"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Lu</surname><given-names>S.</given-names></name> <name><surname>Sun</surname><given-names>Z. N.</given-names></name> <name><surname>Huang</surname><given-names>M.</given-names></name></person-group> (<year>2024</year>). <article-title>The impact of digital literacy on farmers' pro-environmental behavior: an analysis with the theory of planned behavior</article-title>. <source>Front. Sustain. Food Syst.</source> <volume>8</volume>:<fpage>1432184</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fsufs.2024.1432184</pub-id></citation></ref>
<ref id="ref27"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Lv</surname><given-names>H.</given-names></name> <name><surname>Guo</surname><given-names>S.</given-names></name></person-group> (<year>2023</year>). <article-title>Comparative analysis of flavonoid metabolites from different parts of <italic>Hemerocallis citrina</italic></article-title>. <source>BMC Plant Biol.</source> <volume>23</volume>:<fpage>491</fpage>. doi: <pub-id pub-id-type="doi">10.1186/s12870-023-04510-6</pub-id>, PMID: <pub-id pub-id-type="pmid">37828495</pub-id></citation></ref>
<ref id="ref28"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mei</surname><given-names>N. A.</given-names></name> <name><surname>Li</surname><given-names>J. G.</given-names></name> <name><surname>Xin</surname><given-names>G. S.</given-names></name> <name><surname>Liu</surname><given-names>Z. X.</given-names></name> <name><surname>Yun</surname><given-names>H.</given-names></name> <name><surname>Ding</surname><given-names>Y. R.</given-names></name> <etal/></person-group>. (<year>2021</year>). <article-title>Effects of <italic>Hemerocallis citrina</italic> Baroni stems and leaves silage on the production, slaughter performance, and meat quality of tan sheep</article-title>. <source>J. Anim. Feed Sci.</source> <volume>11</volume>, <fpage>29</fpage>&#x2013;<lpage>32</lpage>. doi: <pub-id pub-id-type="doi">10.13300/j.cnki.cn42-1648/s.2021.11.007</pub-id></citation></ref>
<ref id="ref29"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mi</surname><given-names>Q.</given-names></name> <name><surname>Li</surname><given-names>X.</given-names></name> <name><surname>Li</surname><given-names>X.</given-names></name> <name><surname>Yu</surname><given-names>G.</given-names></name> <name><surname>Gao</surname><given-names>J.</given-names></name></person-group> (<year>2021</year>). <article-title>Cotton farmers' adaptation to arid climates: waiting times to adopt water-saving technology</article-title>. <source>Agric. Water Manag.</source> <volume>244</volume>:<fpage>106596</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.agwat.2020.106596</pub-id></citation></ref>
<ref id="ref30"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Nhuong</surname><given-names>B. H.</given-names></name> <name><surname>Truong</surname><given-names>D. D.</given-names></name></person-group> (<year>2024</year>). <article-title>Factors affecting the adoption of high technology in vegetable production in Hanoi, Vietnam</article-title>. <source>Front. Sustain. Food Syst.</source> <volume>8</volume>:<fpage>1345598</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fsufs.2024.1345598</pub-id></citation></ref>
<ref id="ref31"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Pan</surname><given-names>L. L.</given-names></name> <name><surname>Wang</surname><given-names>X. Y.</given-names></name></person-group> (<year>2018</year>). <article-title>The factors affecting the intention to exhibit environmental behavior by tourists: a case study of Xixi National Wetland Park in Hangzhou</article-title>. <source>Sci. Geogr. Sin.</source> <volume>38</volume>, <fpage>1337</fpage>&#x2013;<lpage>1345</lpage>. doi: <pub-id pub-id-type="doi">10.13249/j.cnki.sgs.2018.08.016</pub-id></citation></ref>
<ref id="ref32"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Qi</surname><given-names>D.</given-names></name> <name><surname>Zhou</surname><given-names>T.</given-names></name></person-group> (<year>2023</year>). <article-title>Feed utilization of soybean dregs and its impact on economic benefits of breeding</article-title>. <source>Feed Ind.</source> <volume>46</volume>, <fpage>175</fpage>&#x2013;<lpage>179</lpage>. doi: <pub-id pub-id-type="doi">10.13557/j.cnki.issn1002-2813.2023.22.033</pub-id></citation></ref>
<ref id="ref33"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Rahmaninkoshkaki</surname><given-names>M.</given-names></name> <name><surname>Zarei</surname><given-names>Y.</given-names></name></person-group> (<year>2018</year>). <article-title>Designing the structural equation model of agricultural entrepreneurship development in rural areas of Iran (case study: villages of Marvdasht county)</article-title>. <source>Int. J. Agric. Sci. Res. Technol. Ext. Educ. Syst.</source> <volume>8</volume>, <fpage>17</fpage>&#x2013;<lpage>27</lpage>.</citation></ref>
<ref id="ref34"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Rodriguez-Enriquez</surname><given-names>M. J.</given-names></name> <name><surname>Grant-Downton</surname><given-names>R. T.</given-names></name></person-group> (<year>2013</year>). <article-title>A new day dawning: <italic>Hemerocallis</italic> (daylily) as a future model organism</article-title>. <source>AoB Plants</source> <volume>5</volume>:<fpage>pls055</fpage>. doi: <pub-id pub-id-type="doi">10.1093/aobpla/pls055</pub-id></citation></ref>
<ref id="ref35"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Roh</surname><given-names>T.</given-names></name> <name><surname>Seok</surname><given-names>J.</given-names></name> <name><surname>Kim</surname><given-names>Y.</given-names></name></person-group> (<year>2022</year>). <article-title>Unveiling ways to reach organic purchase: green perceived value, perceived knowledge, attitude, subjective norm, and trust</article-title>. <source>J. Retail. Consum. Serv.</source> <volume>67</volume>:<fpage>102988</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jretconser.2022.102988</pub-id></citation></ref>
<ref id="ref36"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sardianou</surname><given-names>E.</given-names></name> <name><surname>Genoudi</surname><given-names>P.</given-names></name></person-group> (<year>2013</year>). <article-title>Which factors affect the willingness of consumers to adopt renewable energies?</article-title> <source>Renew. Energ.</source> <volume>57</volume>, <fpage>1</fpage>&#x2013;<lpage>4</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.renene.2013.01.031</pub-id></citation></ref>
<ref id="ref37"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sarkar</surname><given-names>A.</given-names></name> <name><surname>Wang</surname><given-names>H.</given-names></name> <name><surname>Rahman</surname><given-names>A.</given-names></name> <name><surname>Azim</surname><given-names>J. A.</given-names></name> <name><surname>Memon</surname><given-names>W. H.</given-names></name> <name><surname>Qian</surname><given-names>L.</given-names></name></person-group> (<year>2022</year>). <article-title>Structural equation model of young farmers' intention to adopt sustainable agriculture: a case study in Bangladesh</article-title>. <source>Renew. Agric. Food Syst.</source> <volume>37</volume>, <fpage>142</fpage>&#x2013;<lpage>154</lpage>. doi: <pub-id pub-id-type="doi">10.1017/S1742170521000429</pub-id></citation></ref>
<ref id="ref38"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Senger</surname><given-names>I.</given-names></name> <name><surname>Borges</surname><given-names>J. A. R.</given-names></name> <name><surname>Machado</surname><given-names>J. A. D.</given-names></name></person-group> (<year>2017</year>). <article-title>Using the theory of planned behavior to understand the intention of small farmers in diversifying their agricultural production</article-title>. <source>J. Rural. Stud.</source> <volume>49</volume>, <fpage>32</fpage>&#x2013;<lpage>40</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jrurstud.2016.10.006</pub-id></citation></ref>
<ref id="ref39"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Serebrennikov</surname><given-names>D.</given-names></name> <name><surname>Thorne</surname><given-names>F.</given-names></name> <name><surname>Kallas</surname><given-names>Z.</given-names></name> <name><surname>McCarthy</surname><given-names>S. N.</given-names></name></person-group> (<year>2020</year>). <article-title>Factors influencing adoption of sustainable farming practices in Europe: a systemic review of empirical literature</article-title>. <source>Sustainability</source> <volume>12</volume>:<fpage>9719</fpage>. doi: <pub-id pub-id-type="doi">10.3390/su12229719</pub-id></citation></ref>
<ref id="ref40"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shi</surname><given-names>H.</given-names></name> <name><surname>Fan</surname><given-names>J.</given-names></name> <name><surname>Zhao</surname><given-names>D.</given-names></name></person-group> (<year>2017</year>). <article-title>Predicting household PM2.5-reduction behavior in Chinese urban areas: an integrative model of theory of planned behavior and norm activation theory</article-title>. <source>J. Clean. Prod.</source> <volume>145</volume>, <fpage>64</fpage>&#x2013;<lpage>73</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jclepro.2016.12.169</pub-id></citation></ref>
<ref id="ref41"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shiao</surname><given-names>S. H.</given-names></name> <name><surname>Shao</surname><given-names>B. R.</given-names></name> <name><surname>He</surname><given-names>Y. X.</given-names></name> <name><surname>Yang</surname><given-names>Y. Q.</given-names></name> <name><surname>Yang</surname><given-names>H. Z.</given-names></name> <name><surname>Chang</surname><given-names>Y. C.</given-names></name></person-group> (<year>1962</year>). <article-title>Studies on <italic>Hemerocallis thunbergii</italic> baker. II. Effectiveness of <italic>Hemerocallis thunbergii</italic> in oral treatment of experimental schistosomiasis in mice</article-title>. <source>Yao Xue Xue Bao</source> <volume>9</volume>, <fpage>218</fpage>&#x2013;<lpage>224</lpage>.</citation></ref>
<ref id="ref42"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sun</surname><given-names>Z. N.</given-names></name> <name><surname>Shen</surname><given-names>H.</given-names></name> <name><surname>Chen</surname><given-names>Z. T.</given-names></name> <name><surname>Ma</surname><given-names>N.</given-names></name> <name><surname>Yang</surname><given-names>Y.</given-names></name> <name><surname>Liu</surname><given-names>H. X.</given-names></name> <etal/></person-group>. (<year>2024</year>). <article-title>Physiological responses and transcriptome analysis of <italic>Hemerocallis citrina</italic> Baroni exposed to <italic>Thrips palmi</italic> feeding stress</article-title>. <source>Front. Plant Sci.</source> <volume>15</volume>:<fpage>1361276</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fpls.2024.1361276</pub-id>, PMID: <pub-id pub-id-type="pmid">38807785</pub-id></citation></ref>
<ref id="ref43"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Tang</surname><given-names>L. Z.</given-names></name></person-group> (<year>2024</year>). <article-title>Feed utilization of fruit and vegetable processing by-products</article-title>. <source>Feed Ind.</source> <volume>45</volume>, <fpage>129</fpage>&#x2013;<lpage>134</lpage>. doi: <pub-id pub-id-type="doi">10.13302/j.cnki.fi.2024.22.018</pub-id></citation></ref>
<ref id="ref44"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>J.</given-names></name> <name><surname>Liu</surname><given-names>L. M.</given-names></name> <name><surname>Zhao</surname><given-names>K. Y.</given-names></name> <name><surname>Wen</surname><given-names>Q.</given-names></name></person-group> (<year>2023</year>). <article-title>Farmers&#x2019; adoption intentions of water-saving agriculture under the risks of frequent irrigation-induced landslides</article-title>. <source>Clim. Risk Manag.</source> <volume>39</volume>:<fpage>100484</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.crm.2023.100484</pub-id></citation></ref>
<ref id="ref45"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>J. Q.</given-names></name> <name><surname>Wang</surname><given-names>N. N.</given-names></name> <name><surname>Fan</surname><given-names>Z. Z.</given-names></name> <name><surname>Yuan</surname><given-names>T. T.</given-names></name> <name><surname>Zhou</surname><given-names>J. H.</given-names></name></person-group> (<year>2023</year>). <article-title>Analysis of influencing factors on green production behavior selection of fruit farmers based on 285 micro samples in Hebei province</article-title>. <source>J. Hebei Agric. Sci.</source> <volume>27</volume>, <fpage>89</fpage>&#x2013;<lpage>93</lpage>. doi: <pub-id pub-id-type="doi">10.12148/hbnykx.20230151</pub-id></citation></ref>
<ref id="ref46"><citation citation-type="book"><person-group person-group-type="author"><collab id="coll1">World Health Organization</collab></person-group> (<year>2022</year>). <source>The state of food security and nutrition in the world 2022: Repurposing food and agricultural policies to make healthy diets more affordable</source>. <publisher-loc>Rome</publisher-loc>: <publisher-name>Food and Agriculture Organization</publisher-name>.</citation></ref>
<ref id="ref47"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wu</surname><given-names>L. P.</given-names></name></person-group> (<year>2023</year>). <article-title>Full understanding of China&#x2019;s food security from perspective of the greater food approach</article-title>. <source>Soc. Sci. J.</source>, <fpage>191</fpage>&#x2013;<lpage>200</lpage>.</citation></ref>
<ref id="ref48"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Wu</surname><given-names>Z. C.</given-names></name></person-group> (<year>2024</year>). <article-title>Research on strategies for ensuring feed and grain supply under the background of food security</article-title>. <source>China Feed.</source>, <fpage>160</fpage>&#x2013;<lpage>163</lpage>. doi: <pub-id pub-id-type="doi">10.15906/j.cnki.cn11-2975/s.20241040</pub-id></citation></ref>
<ref id="ref49"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Xiang</surname><given-names>P. A.</given-names></name> <name><surname>Guo</surname><given-names>J.</given-names></name></person-group> (<year>2023</year>). <article-title>Understanding farmers&#x2019; intentions to adopt pest and disease green control techniques: comparison and integration based on multiple models</article-title>. <source>Sustainability</source> <volume>15</volume>:<fpage>10822</fpage>. doi: <pub-id pub-id-type="doi">10.3390/su151410822</pub-id></citation></ref>
<ref id="ref50"><citation citation-type="book"><person-group person-group-type="author"><name><surname>Xiao</surname><given-names>Y.</given-names></name></person-group> (<year>2016</year>). <source>Analyzing and modeling of the influence of driving distraction on traffic safety and traffic efficiency</source>. <publisher-loc>Beijing, China</publisher-loc>: <publisher-name>Tsinghua University</publisher-name>.</citation></ref>
<ref id="ref51"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Yin</surname><given-names>Y. L.</given-names></name> <name><surname>Yang</surname><given-names>Z.</given-names></name></person-group> (<year>2025</year>). <article-title>Development and efficient utilization of unconventional feed</article-title>. <source>Feed Ind.</source> <volume>46</volume>, <fpage>2</fpage>&#x2013;<lpage>10</lpage>. doi: <pub-id pub-id-type="doi">10.13302/j.cnki.fi.2025.01.001</pub-id></citation></ref>
<ref id="ref52"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>Y. X.</given-names></name></person-group> (<year>2023</year>). <article-title>Promotion strategy of feed grain safety supply undernew pattern of double circulation</article-title>. <source>Feed Res.</source> <volume>46</volume>, <fpage>187</fpage>&#x2013;<lpage>190</lpage>. doi: <pub-id pub-id-type="doi">10.13557/j.cnki.issn1002-2813.2023.23.036</pub-id></citation></ref>
<ref id="ref53"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>J. L.</given-names></name> <name><surname>Ma</surname><given-names>J. F.</given-names></name> <name><surname>Ma</surname><given-names>J. F.</given-names></name> <name><surname>Zhao</surname><given-names>Z. W.</given-names></name> <name><surname>Ma</surname><given-names>X. M.</given-names></name> <name><surname>Liang</surname><given-names>X. J.</given-names></name> <etal/></person-group>. (<year>2023</year>). <article-title>Effects of yellow silage of daylily stem and leaves on fattening and serum biochemical indicators of Simmentaler hybrid cattle</article-title>. <source>Ningxia J. Agri. Fores. Sci. Tech.</source> <volume>64</volume>, <fpage>35</fpage>&#x2013;<lpage>38</lpage>. doi: <pub-id pub-id-type="doi">10.3969/j.issn.1002-204x.2023.02.010</pub-id></citation></ref>
<ref id="ref54"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>H. L.</given-names></name> <name><surname>Wang</surname><given-names>W. G.</given-names></name> <name><surname>Wang</surname><given-names>J.</given-names></name> <name><surname>Zhao</surname><given-names>X. J.</given-names></name> <name><surname>Bo</surname><given-names>Y. L.</given-names></name> <name><surname>Hou</surname><given-names>Y. J.</given-names></name></person-group> (<year>2024</year>). <article-title>Analysis on evolution of ecological vulnerability of Shanxi Province based on the remote sensing and GIS technique</article-title>. <source>Remote Sens. Technol. Appl.</source> <volume>39</volume>, <fpage>478</fpage>&#x2013;<lpage>491</lpage>. doi: <pub-id pub-id-type="doi">10.11873/j.issn.1004-0323.2024.2.0478</pub-id></citation></ref>
<ref id="ref55"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhao</surname><given-names>R. H.</given-names></name> <name><surname>Luo</surname><given-names>J. H.</given-names></name> <name><surname>Xu</surname><given-names>B. J.</given-names></name></person-group> (<year>2024</year>). <article-title>Insights into secondary metabolites and health promoting effects of edible flower <italic>Hemerocallis citrina</italic> Baroni</article-title>. <source>J. Funct. Foods</source> <volume>116</volume>:<fpage>106133</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jff.2024.106133</pub-id></citation></ref>
<ref id="ref57"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhao</surname><given-names>Z. W.</given-names></name> <name><surname>Wang</surname><given-names>Z. L.</given-names></name> <name><surname>Zhang</surname><given-names>J. L.</given-names></name> <name><surname>Yang</surname><given-names>Y. W.</given-names></name> <name><surname>Ma</surname><given-names>J. F.</given-names></name> <name><surname>Wang</surname><given-names>X. Q.</given-names></name> <etal/></person-group>. (<year>2021</year>). <article-title>Analysis of volatile fatty acid content in stem and leaf mixed storage of daylily</article-title>. <source>Feed Res.</source> <volume>44</volume>, <fpage>102</fpage>&#x2013;<lpage>105</lpage>. doi: <pub-id pub-id-type="doi">10.13557/j.cnki.issn1002-2813.2021.08.023</pub-id></citation></ref>
<ref id="ref58"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zheng</surname><given-names>M. N.</given-names></name> <name><surname>Kang</surname><given-names>J. H.</given-names></name> <name><surname>Zou</surname><given-names>C. Y.</given-names></name> <name><surname>Hou</surname><given-names>X. Y.</given-names></name> <name><surname>Liang</surname><given-names>X. Z.</given-names></name> <name><surname>Han</surname><given-names>Z. S.</given-names></name> <etal/></person-group>. (<year>2024</year>). <article-title>Effects of ratio of daylily stem and leaf mixed with corn silage on the quality of silage and microbial diversity</article-title>. <source>Acta Agrest. Sin.</source> <volume>32</volume>, <fpage>3962</fpage>&#x2013;<lpage>3972</lpage>. doi: <pub-id pub-id-type="doi">10.11733/j.issn.1007-0435.2024.12.032</pub-id></citation></ref>
<ref id="ref59"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zheng</surname><given-names>Y. Y.</given-names></name> <name><surname>Mei</surname><given-names>L. F.</given-names></name> <name><surname>Chen</surname><given-names>W. M.</given-names></name></person-group> (<year>2024</year>). <article-title>Does government policy matter in the digital transformation of farmers&#x2019; cooperatives?&#x2014;a tripartite evolutionary game analysis</article-title>. <source>Front. Sustain. Food Syst.</source> <volume>8</volume>:<fpage>1398319</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fsufs.2024.1398319</pub-id></citation></ref>
<ref id="ref61"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Zhou</surname><given-names>Z. Q.</given-names></name> <name><surname>Zhang</surname><given-names>Y. H.</given-names></name> <name><surname>Yan</surname><given-names>Z. B.</given-names></name></person-group> (<year>2022</year>). <article-title>Will digital financial inclusion increase Chinese farmers&#x2019; willingness to adopt agricultural technology?</article-title> <source>Agriculture</source> <volume>12</volume>:<fpage>1514</fpage>. doi: <pub-id pub-id-type="doi">10.3390/agriculture12101514</pub-id></citation></ref>
</ref-list>
</back>
</article>