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<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.2023.1224530</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>Integrated systems improve the sustainability of soybean cultivation in the tropical region</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>e Silva</surname>
<given-names>Jo&#x00E3;o Ant&#x00F4;nio Gon&#x00E7;alves</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2292104/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Costa</surname>
<given-names>K&#x00E1;tia Aparecida de Pinho</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="c001" ref-type="corresp"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2285124/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>da Silva</surname>
<given-names>Luciana Maria</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2288862/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Severiano</surname>
<given-names>Eduardo da Costa</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2363267/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Silva</surname>
<given-names>Fabiano Guimar&#x00E3;es</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1264883/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Habermann</surname>
<given-names>Eduardo</given-names>
</name>
<xref rid="aff2" ref-type="aff"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/658173/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Martinez</surname>
<given-names>Carlos Alberto</given-names>
</name>
<xref rid="aff2" ref-type="aff"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/365827/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Vilela</surname>
<given-names>Lourival</given-names>
</name>
<xref rid="aff3" ref-type="aff"><sup>3</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2404449/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>da Silva</surname>
<given-names>Alessandro Guerra</given-names>
</name>
<xref rid="aff4" ref-type="aff"><sup>4</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2403661/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Costa</surname>
<given-names>Adriano Carvalho</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2362573/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Costa</surname>
<given-names>Jo&#x00E3;o Victor Campos Pinho</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2362220/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>de Oliveira</surname>
<given-names>Katryne Jordana</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2403659/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Agricultural Sciences/Agronomy and Animal Science, Goiano Federal Institute (IF Goiano)</institution>, <addr-line>Rio Verde</addr-line>, <country>Brazil</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Biology, School of Philosophy, Science and Literature (FFCLRP), University of S&#x00E3;o Paulo</institution>, <addr-line>Ribeir&#x00E3;o Preto</addr-line>, <country>Brazil</country></aff>
<aff id="aff3"><sup>3</sup><institution>Embrapa Cerrados</institution>, <addr-line>Planaltina</addr-line>, <country>Brazil</country></aff>
<aff id="aff4"><sup>4</sup><institution>Department of Agronomy, University of Rio Verde</institution>, <addr-line>Rio Verde</addr-line>, <country>Brazil</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001"><p>Edited by: Xiukang Wang, Yan'an University, China</p></fn>
<fn fn-type="edited-by" id="fn0002"><p>Reviewed by: Rodolfo Lizcano Toledo, Tolima University, Colombia; Kolima Pe&#x00F1;a, University of Sancti Spiritus, Cuba</p></fn>
<corresp id="c001">&#x002A;Correspondence: K&#x00E1;tia Aparecida de Pinho Costa, <email>katia.costa@ifgoiano.edu.br</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>23</day>
<month>08</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>7</volume>
<elocation-id>1224530</elocation-id>
<history>
<date date-type="received">
<day>17</day>
<month>05</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>03</day>
<month>08</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2023 e Silva, Costa, da Silva, Severiano, Silva, Habermann, Martinez, Vilela, da Silva, Costa, Costa and de Oliveira.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>e Silva, Costa, da Silva, Severiano, Silva, Habermann, Martinez, Vilela, da Silva, Costa, Costa and de Oliveira</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>
<p>Inter-cropping between annual crops with tropical forages through integration crop-livestock systems (ICL) is considered a sustainable option to increase crop diversity and soybean productivity. In this study, we evaluated (1) the biomass production, desiccation efficiency, nutrient accumulation, and biomass decomposition of soil crop residues produced by <italic>Panicum maximum</italic> plants intercropped with maize in two different sowing methods during the second harvest and (2) investigated how soil crop residues impact the productivity of soybean. The experiment was conducted in a complete block design with three replicates. We compared conventional soybean cultivation with soybean cultivated over soil crop residues produced by a previous integration between maize and two <italic>Panicum maximum</italic> cultivars: Tamani and Zuri guinea grass, within and between rows of maize plants. Our results showed that Tamani guinea grass showed the highest desiccation efficiency. Zuri and Tamani guinea grass cultivated within and between maize plants resulted in higher biomass production and nutrient cycling potential, resulting in an increase of 28.4% in soybean productivity, compared to soybean grown without soil crop residues. We concluded that ICL system is an efficient method to increase the sustainability of soybean cultivation.</p>
</abstract>
<kwd-group>
<kwd><italic>Glycine max</italic> L.</kwd>
<kwd><italic>Panicum maximum</italic> cv. BRS Tamani</kwd>
<kwd><italic>Panicum maximum</italic> cv. BRS Zuri</kwd>
<kwd>sustainability</kwd>
<kwd>
<italic>Zea mays</italic>
</kwd>
</kwd-group>
<contract-sponsor id="cn1">National Council for Scientific and Technological Development<named-content content-type="fundref-id">10.13039/501100003593</named-content></contract-sponsor>
<counts>
<fig-count count="6"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="48"/>
<page-count count="13"/>
<word-count count="8641"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Crop Biology and Sustainability</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<label>1.</label>
<title>Introduction</title>
<p>The intensification of land use for food production is a global, complex, and urgent challenge in a growing world population. Reaching future demands efficiently using natural resources is the central point for agricultural sustainability (<xref ref-type="bibr" rid="ref14">Damian et al., 2023</xref>). Therefore, it is necessary to rethink the future of agricultural production to simultaneously ensure food security and alleviate environmental pressure (<xref ref-type="bibr" rid="ref45">Yue et al., 2022</xref>). Integrated crop-livestock system (ICL) is considered an efficient, cheap, and sustainable strategy for food production, reducing costs, and risks and conserving natural resources (<xref ref-type="bibr" rid="ref35">Silva et al., 2022</xref>). When well-managed, ICL systems provide multiple ecosystem services through increased carbon sequestration, water, and soil conservation (<xref ref-type="bibr" rid="ref21">Maia et al., 2022</xref>), greater efficiency in nutrient use (<xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>), and production diversification (<xref ref-type="bibr" rid="ref23">Meo-Filho et al., 2022</xref>).</p>
<p>ICL systems can be defined as the cultivation of annual crops and forage species intercropped and/or in rotation, promoting pastures recovery (<xref ref-type="bibr" rid="ref14">Damian et al., 2023</xref>), greater stocks of soil organic matter and soil moisture (<xref ref-type="bibr" rid="ref20">Laroca et al., 2018</xref>), improved production efficiency and increased soil fertility through nutrient cycling (<xref ref-type="bibr" rid="ref4">Bansal et al., 2022</xref>). In addition, ICL systems can contribute to the reduction of greenhouse gas (GHG) emissions, mainly nitrous oxide, by reducing the use of nitrogenous fertilizers. These fertilizers when used as the only source of nitrogen can increase the soil emission of nitrous oxide (<xref ref-type="bibr" rid="ref9">Carvalho et al., 2022</xref>). Additionally, the ICL system contributes to reducing fertilizer costs (<xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>). Covering the soil with plant residues promotes less variation in soil temperature and preserves soil moisture (<xref ref-type="bibr" rid="ref7">Calonego et al., 2017</xref>). Benefits to the biological properties of the soil are also observed, such as increased microbial activity and suppression of weeds through physical barriers, competition for light and nutrients, and allelopathic effects, reducing the use of pesticides (<xref ref-type="bibr" rid="ref43">Vincent-Caboud et al., 2019</xref>).</p>
<p>One of the most crucial aspects of ICL systems that affect its success is the composition of forage species, which must present adaptability, versatility, and good performance. In the last years, <italic>Panicum maximum</italic> cultivars have shown potential to integrate ICL systems (<xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>, <xref ref-type="bibr" rid="ref16">2021</xref>; <xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). The correct choice of forage composition of the crop-livestock integration system must provide good soil cover (<xref ref-type="bibr" rid="ref2">Andrade et al., 2017</xref>), satisfactory animal performance (<xref ref-type="bibr" rid="ref16">Dias et al., 2021</xref>), adequate biomass production for no-tillage system, slow decomposition of plant residues, and gradual release of nutrients to meet the demand of the subsequent crop (<xref ref-type="bibr" rid="ref11">Costa et al., 2020</xref>; <xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>; <xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). Therefore, knowledge of the decomposition of the remaining biomass, in the management of a no-tillage system, is fundamental for the adoption of practices to increase the efficiency of the system (<xref ref-type="bibr" rid="ref44">Wenneck et al., 2021</xref>).</p>
<p>The success of the no-tillage system depends on the amount of biomass present on the soil surface, since it contributes to the accumulation of organic matter, providing improvements in the physical, chemical, and biological attributes of the soil over the years (<xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). From the perspective of nutrient cycling in production systems, the amount and release rate of nutrients from plant residues left by a previously cultivated crop are of great importance for the nutritional management of the succeeding crop (<xref ref-type="bibr" rid="ref5">Baptistella et al., 2020</xref>). Therefore, the periods of higher demand for plant nutrients and release of nutrients by plant residues must coincide (<xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). In the las years, there&#x2019;s has been a considerable increase in the cost of fertilizers. Therefore, the use of plant residues in agricultural systems should become more important since it provides a more efficient use of nutrients available in the soil (<xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>), reducing the need of additional sources of nutrients (<xref ref-type="bibr" rid="ref9002">Soares et al., 2019</xref>). Moreover, ICL systems may increase carbon and nitrogen stocks in the soil (<xref ref-type="bibr" rid="ref41">Torres et al., 2019</xref>), favoring the mineralization process if the C:N ratio is adequate.</p>
<p>In addition to the species composition, the forage sowing method is another crucial aspect of a successful ICL system. The sowing method is responsible for the success of the integration system due to its influence on biomass production for the no-tillage system and crop productivity due to the different levels of competition between plants (<xref ref-type="bibr" rid="ref19">Guarnieri et al., 2019</xref>; <xref ref-type="bibr" rid="ref27">Oliveira et al., 2020</xref>). In this context, integrated systems are technologies that ensure sustainability by improving soil quality (<xref ref-type="bibr" rid="ref34">Sarto et al., 2020</xref>) and represent an important alternative to ensure high soybean yields in the Brazilian Savannah (Cerrado) (<xref ref-type="bibr" rid="ref30">Pires et al., 2022</xref>).</p>
<p>Due to the lack of information regarding the performance of the new <italic>Panicum maximum</italic> cultivars and the adequate sowing methods in a ICL system, studies that investigate these topics are paramount. In this study, we evaluated (1) the biomass production, desiccation efficiency, nutrient accumulation, and biomass decomposition of soil crop residues produced by <italic>Panicum maximum</italic> plants intercropped with maize in two different sowing methods during the second harvest and (2) investigated how soil crop residues impact the productivity of soybean. We hypothesized that: (a) intercropping systems where the forage is cultivated between rows of maize is more beneficial than sowing in the same row due to the small competition between species, and (b) soybean plants grown over soil crop residues produced by previous integration systems will have better agronomic traits, mainly thousand grain weight and yield increase, when compared to soybean grown without soil cover (conventional soybean cultivation).</p>
</sec>
<sec sec-type="materials|methods" id="sec2">
<label>2.</label>
<title>Materials and methods</title>
<sec id="sec3">
<label>2.1.</label>
<title>Experimental site and design</title>
<p>The experiment was conducted at Goiano Federal Institute in Rio Verde, Goi&#x00E1;s, Brazil (17&#x00B0; 48&#x2032; 53&#x2032;&#x2032; S e 50 o 54&#x2032; 02&#x2032;&#x2032; W) between January 2021 to March 2022. The soil in the experimental site was classified as Latossolo Vermelho Acrif&#x00E9;rrico (<xref ref-type="bibr" rid="ref33">Santos et al., 2018</xref>). A timeline showing the climate conditions registered during the experiment can be found in <xref rid="fig1" ref-type="fig">Figure 1</xref>.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Experimental timeline containing the main events and climate conditions registered during the experiment. Bars show the accumulated rainfall in each month, while symbols + lines show the monthly average temperature, maximum temperature, and minimum temperature.</p>
</caption>
<graphic xlink:href="fsufs-07-1224530-g001.tif"/>
</fig>
<p>In the first stage of the experiment, a consortium of maize plants (<italic>Zea mays</italic> hybrid P4285) with forage grasses of the <italic>Panicum maximum</italic> genus (cv. BRS Tamani and cv. BRS Zuri) was carried out within rows and between rows of maize plants, in addition to sowing maize in monoculture. When grown in both systems, monoculture and consortium, maize seeds were sown at 2&#x2009;cm depth and 0.5&#x2009;m distance between rows. <italic>Panicum</italic> seeds (Tamani and Zuri) were sown at 6&#x2009;cm depth when intercropped within rows of maize plants to delay their germination compared to maize. When intercropped between rows of maize, <italic>Panicum</italic> seeds were sown at 0.25&#x2009;m distance from the maize plants and at 2&#x2009;cm depth. Each plot contained six rows 3&#x2009;m long and 0.5&#x2009;m apart from each other.</p>
<p>All measurements were conducted with plants located inside the four central lines, eliminating 0.5&#x2009;m from borders. On 5 May 2021, maize and grasses were harvested for silage production. During the off-season (between June and August 2021), forages were successively clipped to simulate grazing. In August, we made the last clipping and forage plants were left in the field for regrowth, desiccation, and formation of biomass to cover the soil.</p>
<p>In the next stage, we prepared the soil for soybean planting. We collected soil samples at 0&#x2013;20&#x2009;cm deep and mixed them to form a composite sample. According to the chemical analysis, we observed the following soil characteristics: pH determined in CaCl<sub>2</sub>: 5.3; Ca: 2.30 cmol<sub>c</sub> dm<sup>&#x2212;3</sup>; Mg: 1.35 cmol<sub>c</sub> dm<sup>&#x2212;3</sup>; Al: 0.01; Al&#x2009;+&#x2009;H: 4.80 cmol<sub>c</sub> dm<sup>&#x2212;3</sup>; K: 0.60 cmol<sub>c</sub> dm<sup>&#x2212;3</sup>; cation exchange capacity of 9.06 cmol<sub>c</sub> dm<sup>&#x2212;3</sup>; base saturation of 47.30%, P (Mehlich): 4.8&#x2009;mg&#x2009;dm<sup>&#x2212;3</sup>; Cu: 4.6&#x2009;mg&#x2009;dm<sup>&#x2212;3</sup>; Zn: 1.0&#x2009;mg&#x2009;dm<sup>&#x2212;3</sup>; Fe: 17.4&#x2009;mg&#x2009;dm<sup>&#x2212;3</sup>; and organic matter (MO) of 39.8&#x2009;g&#x2009;kg<sup>&#x2212;1</sup>. We applied limestone filler (1 ton ha<sup>&#x2212;1</sup>) in the entire experimental field.</p>
<p>Soybean seeds (B&#x00F4;nus IPRO 8579 variety) were mechanized sowed in rows 50&#x2009;cm apart from each other in October 2021. During soybean sowing, we applied phosphorus (120&#x2009;kg&#x2009;ha<sup>&#x2212;1</sup> of P<sub>2</sub>O<sub>5</sub>) in the planting furrow. We did not apply potassium in treatments containing soil cover to utilize the nutrient cycling process provided by the integrated system. Indeed, we only applied potassium (85&#x2009;kg&#x2009;ha<sup>&#x2212;1</sup> of K<sub>2</sub>O) in the treatment of Soybean without soil cover, to meet the needs of the crop, because in the absence of soil cover there would be no utilization of nutrient cycling. Fungicide (0.3&#x2009;L&#x2009;ha<sup>&#x2212;1</sup> of Pyraclostrobin) was applied 40&#x2009;days after sowing (DAS). We harvested soybean plants in March 2022.</p>
</sec>
<sec id="sec4">
<label>2.2.</label>
<title>Treatments</title>
<p>In this study, the experiment was organized in three completely randomized blocks with three replications for each treatment (<italic>n</italic>&#x2009;=&#x2009;3), totalizing 8 treatments where soybean was cultivated with or without plant cover residues as follows: Maize monoculture (Soybean cultivated with plant residues of maize without integration with forages), Tamani monoculture (Soybean cultivated with plant residues of Tamani guinea grass without integration with maize), Zuri guinea grass monoculture (Soybean cultivated with plant residues of Zuri guinea grass without integration with Maize), maize + Tamani within rows (Soybean cultivated with plant residues of Tamani guinea grass planted within rows of maize plants), maize + Tamani between rows (Soybean cultivated with plant residues of Tamani guinea grass planted between rows of maize plants), maize + Zuri guinea grass within rows (Soybean cultivated with plant residues of Zuri guinea grass planted within rows of maize plants), maize + Zuri guinea grass between rows (Soybean cultivated with plant residues of Zuri guinea grass planted between rows of Maize plants), and Soybean without soil cover (traditional Soybean monoculture without soil cover residues). A schematic showing the cropping systems can be found in <xref rid="fig2" ref-type="fig">Figure 2</xref>.</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p><bold>A</bold> Scheme showing the cropping systems: monoculture of maize <bold>(A)</bold>; monoculture of <italic>Panicum</italic> forage plants <bold>(B)</bold>; maize in intercropped with <italic>Panicum</italic> cultivated within rows of maize plants <bold>(C)</bold> and between rows of maize plants <bold>(D)</bold> and soybean without soil cover <bold>(E)</bold>, during the entire experimental period.</p>
</caption>
<graphic xlink:href="fsufs-07-1224530-g002.tif"/>
</fig>
</sec>
<sec id="sec5">
<label>2.3.</label>
<title>Desiccation efficiency of forage plants</title>
<p>The desiccation of forage plants was performed using Glyphosate (3&#x2009;L&#x2009;ha<sup>&#x2212;1</sup>) (480&#x2009;g&#x2009;L<sup>&#x2212;1</sup> of active ingredient) in October 2021. Herbicide efficiency was evaluated based on Brazilian Society of Weed Sciences (SBCPD) guidelines (<xref ref-type="bibr" rid="ref18">Gazziero, 1995</xref>). Desiccation efficiency was evaluated at 7, 14, and 21&#x2009;days after herbicide application through a visual scale ranging from 0 to 100%, where 0% represents no injury promoted by herbicide and 100% representing the death of plants.</p>
</sec>
<sec id="sec6">
<label>2.4.</label>
<title>Forage biomass production</title>
<p>One day before soybean sowing, we collected all the biomass produced in a quadrat of 0.5&#x2009;&#x00D7;&#x2009;0.5&#x2009;m (0.25&#x2009;m<sup>2</sup>). Each quadrat was placed randomly in each plot. Plant material was clipped close the soil surface and dried under 55&#x00B0;C in an oven until reach constant dry weight. Then, biomass production (kg&#x2009;ha<sup>&#x2212;1</sup>) was calculated.</p>
</sec>
<sec id="sec7">
<label>2.5.</label>
<title>Biomass decomposition rates</title>
<p>The decomposition rate of forage biomass was evaluate using litter bags (2&#x2009;mm mesh, 25&#x2009;&#x00D7;&#x2009;30&#x2009;cm) (<xref ref-type="bibr" rid="ref40">Thomas and Asakawa, 1993</xref>). Four litter bags per plot were filled with 300&#x2009;g of dry biomass produced by the treatment and placed on the soil surface. Each litter bag was washed in running water to remove any soil residue and dried in a stoven at 55&#x00B0;C until constant dry weight to obtain the dry mass. Using the biomass production (kg&#x2009;ha<sup>&#x2212;1</sup>) of each treatment, we calculated the percentage of biomass decomposition using the ratio between the biomass of litter bags (kg&#x2009;ha<sup>&#x2212;1</sup>) and biomass production (<xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>).</p>
</sec>
<sec id="sec8">
<label>2.6.</label>
<title>Release of nutrients from biomass</title>
<p>Biomass samples were grounded to measure the concentration of C, N, P, K, and S according to the method proposed by <xref ref-type="bibr" rid="ref22">Malavolta et al. (1997)</xref>. We calculated the C:N ratio. To evaluate the nutrient accumulation, the concentration of each macronutrient was multiplied by biomass production. The equivalent of fertilizers such as N, P<sub>2</sub>O<sub>5</sub>, and K<sub>2</sub>O released by soil cover produced by maize&#x2009;+&#x2009;forage plants was determined using the atomic mass of each element, according to conventions of analytical chemistry and the concentration of each nutrient (<xref ref-type="bibr" rid="ref32">Santos et al., 2014</xref>).</p>
</sec>
<sec id="sec9">
<label>2.7.</label>
<title>Soybean agronomic traits</title>
<p>Agronomic traits of soybean plants were measured in March 2022 (123&#x2009;days after sowing). We evaluated the plant height (10 plants evaluated per plot), height of the first and last pod (10 plants evaluated per plot), the number of pods per plant (10 plants evaluated per plot), the number of grains per pod (10 plants per plot), thousand-grain weight, and productivity (kg&#x2009;ha<sup>&#x2212;1</sup>).</p>
</sec>
<sec id="sec10">
<label>2.8.</label>
<title>Statistical analysis</title>
<p>The efficiency of desiccation was adjusted by regression equations. To describe biomass decomposition and nutrient accumulation, data were fitted with standard error to an exponential mathematical model (y&#x2009;=&#x2009;aekx) and linear to C:N ratio (y&#x2009;=&#x2009;a&#x2009;+&#x2009;bx), using Sigma Plot software. Comparisons between the estimated equations were performed according to <xref ref-type="bibr" rid="ref36">Snedecor and Cochran (1989)</xref>, which tests the homogeneity of the data (F) and the significance of the angular coefficients of the straight (0.4343&#x2009;k) and linear (log a) of the linearized equations (logy&#x2009;=&#x2009;loga+0.4343kx). To calculate the half-life (t &#x00BD;), that is, the time required to decompose 50% of the remaining biomass, we used the equation proposed by <xref ref-type="bibr" rid="ref29">Paul and Clark (1989)</xref>, in which, t &#x00BD;&#x2009;=&#x2009;0.693/k, where t &#x00BD; is the dry biomass half-life and k is the dry biomass decomposition constant.</p>
<p>Nutrient concentration, fertilizer equivalent, soybean agronomic traits, and grain yield were submitted to analysis of variance using the R program version R-3.1.1 (2014) and ExpDes package (<xref ref-type="bibr" rid="ref17">Ferreira et al., 2014</xref>). Means were compared using Tukey&#x2019;s test, with a significance level of 5% probability. Principal component analysis (PCA) was performed using the computational packages &#x201C;tidyverse,&#x201D; &#x201C;stats,&#x201D; and &#x201C;factoextra.&#x201D;</p>
</sec>
</sec>
<sec sec-type="results" id="sec11">
<label>3.</label>
<title>Results</title>
<sec id="sec12">
<label>3.1.</label>
<title>Desiccation efficiency, biomass production and C:N ratio</title>
<p>We observed no significant differences in desiccation efficiency between monoculture and intercropped treatments. However, we observed differences in desiccation efficiency between forages (<xref rid="fig3" ref-type="fig">Figure 3</xref>). The desiccation efficiency of Tamani guinea grass was 28, 66, and 95% at 7, 14, and 21&#x2009;days after herbicide application, respectively, while the desiccation efficiency of Zuri guinea grass was 17, 39, and 78% at 7, 14, and 21&#x2009;days after herbicide application, respectively.</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Desiccation efficiency of forage plants. Vertical bars represent the standard deviation of the mean.</p>
</caption>
<graphic xlink:href="fsufs-07-1224530-g003.tif"/>
</fig>
<p>The different cultivation systems and cultivars of <italic>Panicum maximum</italic> influenced soil cover biomass production (<xref rid="tab1" ref-type="table">Table 1</xref>). The highest biomass production was observed for Zuri guinea grass monoculture followed by Zuri guinea grass cultivated between and within rows of maize. On average, Zuri guinea grass regardless sowing method produced 45.34% more biomass compared to maize. In addition, maize in monoculture showed the lowest biomass production when compared to all other treatments. Tamani guinea grass in monoculture showed the highest N concentration, followed by Tamani and Zuri guinea grass intercropped within rows and between rows of maize (<xref rid="tab1" ref-type="table">Table 1</xref>). On average, Tamani guinea grass in monoculture, Tamani and Zuri guinea grass intercropped within rows and between rows of maize showed a 41.63% increase in N concentration when compared to maize biomass in monoculture. For P, K and S, only maize in monoculture had different and smaller concentration of nutrients when compared to concentrations in forages in monoculture and intercropped.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Biomass production and initial concentration of nutrients in the biomass of different cultivation systems.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Cultivation systems</th>
<th align="center" valign="top" rowspan="2">Biomass (kg&#x2009;ha<sup>&#x2212;1</sup>)</th>
<th align="center" valign="top" colspan="4">Nutrients (g&#x2009;kg<sup>&#x2212;1</sup>)</th>
</tr>
<tr>
<th align="center" valign="top">N</th>
<th align="center" valign="top">P</th>
<th align="center" valign="top">K</th>
<th align="center" valign="top">S</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Maize monoculture</td>
<td align="center" valign="top">3,028 e</td>
<td align="center" valign="top">8.50 c</td>
<td align="center" valign="top">1.53 c</td>
<td align="center" valign="top">8.13 b</td>
<td align="center" valign="top">2.37 b</td>
</tr>
<tr>
<td align="left" valign="top">Tamani guinea grass monoculture</td>
<td align="center" valign="top">4,298&#x2009;cd</td>
<td align="center" valign="top">17.60 a</td>
<td align="center" valign="top">2.46 a</td>
<td align="center" valign="top">17.81 a</td>
<td align="center" valign="top">3.58 a</td>
</tr>
<tr>
<td align="left" valign="top">Zuri guinea grass monoculture</td>
<td align="center" valign="top">6,527 a</td>
<td align="center" valign="top">14.80 b</td>
<td align="center" valign="top">2.35 ab</td>
<td align="center" valign="top">18.08 a</td>
<td align="center" valign="top">3.37 a</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani within rows</td>
<td align="center" valign="top">3,392 e</td>
<td align="center" valign="top">14.10 b</td>
<td align="center" valign="top">2.12 b</td>
<td align="center" valign="top">15.08 a</td>
<td align="center" valign="top">2.95 b</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani between rows</td>
<td align="center" valign="top">3,873 d</td>
<td align="center" valign="top">14.56 b</td>
<td align="center" valign="top">2.23 b</td>
<td align="center" valign="top">17.59 a</td>
<td align="center" valign="top">3.26 ab</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri within rows</td>
<td align="center" valign="top">4,814bc</td>
<td align="center" valign="top">12.80 b</td>
<td align="center" valign="top">2.17 b</td>
<td align="center" valign="top">17.12 a</td>
<td align="center" valign="top">3.14 b</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri between rows</td>
<td align="center" valign="top">5,280 b</td>
<td align="center" valign="top">13.53 b</td>
<td align="center" valign="top">2.22 b</td>
<td align="center" valign="top">16.97 a</td>
<td align="center" valign="top">3.27 ab</td>
</tr>
<tr>
<td align="left" valign="top">Standard error mean</td>
<td align="center" valign="top">171.20</td>
<td align="center" valign="top">0.661</td>
<td align="center" valign="top">0.0609</td>
<td align="center" valign="top">0.675</td>
<td align="center" valign="top">0.161</td>
</tr>
<tr>
<td align="left" valign="top"><italic>p</italic>-value</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td align="center" valign="top">0.0054</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Means followed by equal letters do not differ (<italic>p</italic>&#x2009;&#x003C;&#x2009;0.05) by Tukey&#x2019;s test.</p>
</table-wrap-foot>
</table-wrap>
<p>The remaining biomass at the end of soybean growing season (120&#x2009;days) (<xref rid="fig4" ref-type="fig">Figure 4A</xref>) was 1,166; 1,753; 2,707; 1,417; 1,613; 2,032 and 2,323&#x2009;kg&#x2009;ha<sup>&#x2212;1</sup> for maize monoculture, Tamani monoculture, Zuri monoculture, maize + Tamani within rows, maize + Tamani between rows, maize + Zuri within rows, and maize + Zuri between rows, respectively. These results indicate that Zuri guinea grass in monoculture or intercropped showed the highest remaining biomass. Regarding half-life, maize monoculture, and Zuri guinea grass in monoculture or in intercropped with maize showed the highest values (similar average values of 103&#x2009;days). C:N ratio linearly decreased in all cultivation systems during biomass decomposition. In all evaluated seasons, maize showed the highest C:N ratio and Tamani guinea grass in monoculture the lowest ratio (<xref rid="fig4" ref-type="fig">Figure 4B</xref>).</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Remaining biomass <bold>(A)</bold> and C:N ratio <bold>(B)</bold> of maize cultivation systems and <italic>Panicum maximum</italic> cultivars in monoculture and intercropping, during soybean growing season. Vertical bars represent the standard deviation of the mean.</p>
</caption>
<graphic xlink:href="fsufs-07-1224530-g004.tif"/>
</fig>
</sec>
<sec id="sec13">
<label>3.2.</label>
<title>Accumulation and nutrient release from plant residues</title>
<p>The accumulation of nutrients in plant residues exponentially decreased during the growing season with influence of cultivation systems (<xref rid="fig5" ref-type="fig">Figure 5</xref>). We observed that after 0, 30, 60, and 90&#x2009;days of biomass decomposition the accumulation of N, P, K, and S was higher for Zuri guinea grass in monoculture followed by Zuri guinea grass in intercropped between and within rows of maize. However, after 120&#x2009;days of biomass decomposition, the accumulation of nutrients was similar between all cultivation systems. We observed that maize showed the lowest accumulation of all nutrients during the entire growing season.</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Accumulation of N <bold>(A)</bold>, P <bold>(B)</bold>, K <bold>(C)</bold>, and S <bold>(D)</bold> of maize cultivation systems and <italic>Panicum maximum</italic> cultivars in monoculture and intercropping, during soybean growing season. Vertical bars represent the standard deviation of the mean.</p>
</caption>
<graphic xlink:href="fsufs-07-1224530-g005.tif"/>
</fig>
<p>Compared with the initial accumulation of nutrients, we observed that after 120&#x2009;days of biomass decomposition, the percentage of N released on the soil was approximately 74, 81, 80, 83, 79, 81, and 78% at maize monoculture, Tamani guinea grass monoculture, Zuri monoculture, maize + Tamani guinea grass within rows, maize + Tamani guinea grass between rows, maize + Zuri guinea grass within rows, and maize + Zuri between rows treatments, respectively. The percentage of P released on the soil was approximately 74, 78, 81, 79, 78, 79, and 76% at treatments maize monoculture, Tamani guinea grass monoculture, Zuri monoculture, maize + Tamani guinea grass within rows, maize + Tamani guinea grass between rows, maize + Zuri guinea grass within rows, and maize + Zuri between rows treatments, respectively. The percentage of K released on the soil was approximately 94, 94, 96, 9, 95, 96, and 95% at treatments maize monoculture, Tamani guinea grass monoculture, zuri monoculture, maize + Tamani guinea grass within rows, maize + Tamani guinea grass between rows, maize + Zuri guinea grass within rows, and maize + Zuri between rows treatments, respectively. The percentage of S released on the soil was approximately 72, 82, 83, 86, 85, 83, and 79% at treatments maize monoculture, Tamani guinea grass monoculture, zuri monoculture, maize + Tamani guinea grass within rows, maize + Tamani guinea grass between rows, maize + Zuri guinea grass within rows, and maize + Zuri between rows treatments, respectively.</p>
<p>Regarding nutrients half-life (t&#x00BD;), the lowest values were obtained for K: 40&#x2009;days for maize in monoculture and 33&#x2009;days for all forages in monoculture or in consortium, indicating a rapid and strong release rate of this nutrient. For all nutrients, maize in monoculture showed the lowest half-life (t&#x00BD;) values, releasing less nutrients to the soil, followed by Zuri guinea grass in monoculture and in intercropped.</p>
<p>We observed that Tamani and Zuri guinea grass in monoculture and Zuri guinea grass between rows promoted the best results in terms of N and P fertilizer equivalent, providing an increase of 67 and 63.27%, respectively, in the return of these nutrients to the soil, compared to maize biomass in monoculture (<xref rid="tab2" ref-type="table">Table 2</xref>). For K, Zuri guinea grass in monoculture was the most efficient cultivar in releasing this nutrient back to the soil. In the contrary direction, maize showed the lowest values of fertilizer equivalent, releasing less nutrients in the soil.</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Equivalent of N, urea, P<sub>2</sub>O<sub>5</sub>, simple superphosphate (SSP), K<sub>2</sub>O and potassium chloride (KCl) of biomass in different cultivation systems.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Cultivation system</th>
<th align="center" valign="top" colspan="6">Equivalent (kg&#x2009;ha<sup>&#x2212;1</sup>)</th>
</tr>
<tr>
<th align="center" valign="top">N</th>
<th align="center" valign="top">Urea</th>
<th align="center" valign="top">P<sub>2</sub>O<sub>5</sub></th>
<th align="center" valign="top">SSP</th>
<th align="center" valign="top">K<sub>2</sub>O</th>
<th align="center" valign="top">KCl</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Maize monoculture</td>
<td align="center" valign="top">25.69 d</td>
<td align="center" valign="top">57.0</td>
<td align="center" valign="top">10.58 d</td>
<td align="center" valign="top">24.0</td>
<td align="center" valign="top">29.79 e</td>
<td align="center" valign="top">51.3</td>
</tr>
<tr>
<td align="left" valign="top">Tamani guinea grass monoculture</td>
<td align="center" valign="top">75.58 a</td>
<td align="center" valign="top">167.9</td>
<td align="center" valign="top">24.30 ab</td>
<td align="center" valign="top">55.2</td>
<td align="center" valign="top">88.24 bc</td>
<td align="center" valign="top">152.1</td>
</tr>
<tr>
<td align="left" valign="top">Zuri guinea grass monoculture</td>
<td align="center" valign="top">83.46 a</td>
<td align="center" valign="top">185.5</td>
<td align="center" valign="top">35.22 a</td>
<td align="center" valign="top">80.0</td>
<td align="center" valign="top">142.11 a</td>
<td align="center" valign="top">245.0</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani within rows</td>
<td align="center" valign="top">45.76 c</td>
<td align="center" valign="top">101.7</td>
<td align="center" valign="top">16.46 bc</td>
<td align="center" valign="top">37.4</td>
<td align="center" valign="top">61.67 d</td>
<td align="center" valign="top">106.3</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani between rows</td>
<td align="center" valign="top">56.27 bc</td>
<td align="center" valign="top">125.0</td>
<td align="center" valign="top">19.82 b</td>
<td align="center" valign="top">45.0</td>
<td align="center" valign="top">81.89&#x2009;cd</td>
<td align="center" valign="top">141.2</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri within rows</td>
<td align="center" valign="top">62.01 b</td>
<td align="center" valign="top">137.8</td>
<td align="center" valign="top">23.99 b</td>
<td align="center" valign="top">54.5</td>
<td align="center" valign="top">103.08 b</td>
<td align="center" valign="top">177.7</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri between rows</td>
<td align="center" valign="top">74.50 a</td>
<td align="center" valign="top">165.6</td>
<td align="center" valign="top">26.89 ab</td>
<td align="center" valign="top">61.1</td>
<td align="center" valign="top">107.93 b</td>
<td align="center" valign="top">186.1</td>
</tr>
<tr>
<td align="left" valign="top">Standard error mean</td>
<td align="center" valign="top">2.298</td>
<td/>
<td align="center" valign="top">1.306</td>
<td/>
<td align="center" valign="top">4.303</td>
<td/>
</tr>
<tr>
<td align="left" valign="top"><italic>P</italic>-value</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td/>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td/>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Means followed by equal letters do not differ (<italic>p</italic>&#x2009;&#x003C;&#x2009;0.05) by Tukey&#x2019;s test.</p>
<p>SSP, simple superphosphate; KCl, potassium chloride.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec14">
<label>3.3.</label>
<title>Agronomic traits and productivity of soybean</title>
<p>Cultivation systems promoted changes in the agronomic traits of soybean plants and grain productivity (<xref rid="tab3" ref-type="table">Table 3</xref>). Taller plants and higher values of first pod height, and number of pods were obtained in Tamani and Zuri guinea grass in monoculture and in consortium. All agronomic traits of soybean cultivated without soil cover were smaller when compared to soybean cultivated with soil cover produced by previous integration.</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Plant height, height of the first pod, number of pods per plant, number of grains per bean, thousand grain weight, and grain productivity of different cultivation systems.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Cultivation systems</th>
<th align="center" valign="top">Plant height (cm)</th>
<th align="center" valign="top">Height 1<sup>a</sup> pod (cm)</th>
<th align="center" valign="top">Number of pods/plant</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Maize monoculture</td>
<td align="center" valign="top">91.46 bc</td>
<td align="center" valign="top">18.33 bc</td>
<td align="center" valign="top">43.50 bc</td>
</tr>
<tr>
<td align="left" valign="top">Tamani guinea grass monoculture</td>
<td align="center" valign="top">110.83 ab</td>
<td align="center" valign="top">20.00 ab</td>
<td align="center" valign="top">48.16 ab</td>
</tr>
<tr>
<td align="left" valign="top">Zuri guinea grass monoculture</td>
<td align="center" valign="top">118.85 a</td>
<td align="center" valign="top">21.16 a</td>
<td align="center" valign="top">48.33 a</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani within rows</td>
<td align="center" valign="top">102.23 b</td>
<td align="center" valign="top">20.60 a</td>
<td align="center" valign="top">46.00 ab</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani between rows</td>
<td align="center" valign="top">108.50 ab</td>
<td align="center" valign="top">21.40 a</td>
<td align="center" valign="top">45.36 ab</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri within rows</td>
<td align="center" valign="top">106.13 ab</td>
<td align="center" valign="top">19.85 b</td>
<td align="center" valign="top">47.53 ab</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri between rows</td>
<td align="center" valign="top">115.58 ab</td>
<td align="center" valign="top">22.15 a</td>
<td align="center" valign="top">48.00 ab</td>
</tr>
<tr>
<td align="left" valign="top">Soybean without soil cover</td>
<td align="center" valign="top">86.44 c</td>
<td align="center" valign="top">16.72 c</td>
<td align="center" valign="top">41.47 c</td>
</tr>
<tr>
<td align="left" valign="top">Standard error mean</td>
<td align="center" valign="top">2.450</td>
<td align="center" valign="top">0.618</td>
<td align="center" valign="top">0.955</td>
</tr>
<tr>
<td align="left" valign="top"><italic>p-</italic>value</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td align="center" valign="top">0.0004</td>
<td align="center" valign="top">0.0012</td>
</tr>
<tr>
<td align="left" valign="top"><bold>Cultivation systems</bold></td>
<td align="center" valign="top"><bold>Number of grains/bean</bold></td>
<td align="center" valign="top"><bold>1,000 grain weight (g)</bold></td>
<td align="center" valign="top"><bold>Productivity (kg&#x2009;ha</bold><sup><bold>&#x2212;1</bold></sup><bold>)</bold></td>
</tr>
<tr>
<td align="left" valign="top">Maize monoculture</td>
<td align="center" valign="top">2.0 a</td>
<td align="center" valign="top">210.65 a</td>
<td align="center" valign="top">4,398 b</td>
</tr>
<tr>
<td align="left" valign="top">Tamani guinea grass monoculture</td>
<td align="center" valign="top">2.3 a</td>
<td align="center" valign="top">215.33 a</td>
<td align="center" valign="top">5,256 a</td>
</tr>
<tr>
<td align="left" valign="top">Zuri guinea grass monoculture</td>
<td align="center" valign="top">2.3 a</td>
<td align="center" valign="top">215.31 a</td>
<td align="center" valign="top">5,280 a</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani within rows</td>
<td align="center" valign="top">2.3 a</td>
<td align="center" valign="top">215.65 a</td>
<td align="center" valign="top">5,021 ab</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Tamani between rows</td>
<td align="center" valign="top">2.3 a</td>
<td align="center" valign="top">215.00 a</td>
<td align="center" valign="top">4,942 ab</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri within rows</td>
<td align="center" valign="top">2.3 a</td>
<td align="center" valign="top">222.67 a</td>
<td align="center" valign="top">5,216 ab</td>
</tr>
<tr>
<td align="left" valign="top">Maize + Zuri between rows</td>
<td align="center" valign="top">2.3 a</td>
<td align="center" valign="top">222.32 a</td>
<td align="center" valign="top">5,549 a</td>
</tr>
<tr>
<td align="left" valign="top">Soybean without soil cover</td>
<td align="center" valign="top">2.0 a</td>
<td align="center" valign="top">186.33 b</td>
<td align="center" valign="top">3,708 c</td>
</tr>
<tr>
<td align="left" valign="top">Standard error mean</td>
<td align="center" valign="top">0.267</td>
<td align="center" valign="top">3.005</td>
<td align="center" valign="top">171.68</td>
</tr>
<tr>
<td align="left" valign="top"><italic>p</italic>-value</td>
<td align="center" valign="top">0.9255</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
<td align="center" valign="top"><italic>p</italic> &#x003C;&#x2009;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Means followed by equal letters do not differ by Tukey&#x2019;s test at 5% probability. <sup>a</sup>First.</p>
</table-wrap-foot>
</table-wrap>
<p>We observed no statistical differences between treatments for the number of grains per pod (<xref rid="tab3" ref-type="table">Table 3</xref>). However, the thousand-grain weight was approximately 16% smaller at soybean without soil cover treatment when compared to all other cultivation systems with soil cover. The highest productivity of grains was observed at Tamani and Zuri guinea grass, both in monoculture and in the consortium, followed by maize in monoculture, while the smaller productivity was observed in the conventional soybean cultivation (without soil cover).</p>
</sec>
<sec id="sec15">
<label>3.4.</label>
<title>Multivariable analysis</title>
<p>According to the principal component analysis (PCA) we were able to understand the relationship between measured parameters and treatments discrimination. PCA is a technique used to comprehend the variance and covariance structure of data by employing linear combinations of all the variables. In this analysis, the covariance and/or correlation matrix are decomposed into eigenvalues and eigenvectors, with eigenvalues indicating the variance and eigenvectors representing the coefficients of each variable in the linear combinations. Each principal component is independent and estimated to retain the maximum amount of information regarding the total variation present in the data, in an ordered manner. The number of principal components is equal to the number of variables. In this study, 8 components were obtained, and it was observed that the first and second components explained 92.56% of the total variation in the data (<xref rid="fig6" ref-type="fig">Figure 6</xref>). Additionally, all the variables used displayed a strong correlation (<italic>r</italic> &#x003E;&#x2009;0.7) with the first component, suggesting that it effectively describes the structure of variance and covariance in the data. The criteria proposed by <xref ref-type="bibr" rid="ref47">Zwick and Velicer (1982)</xref>, which recommend that variances &#x003E;70% are considered ideal, were satisfied in our analysis. Therefore, the PCA results were consistent with our initial findings. <xref rid="fig6" ref-type="fig">Figure 6</xref> displays the scores for the treatments and variables represented through linear combinations, with the first component represented horizontally and the second component vertically.</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Bidimensional dispersion of principal component analysis scores of the 8 parameters, observations, and average values of treatments regarding biomass production, nutrient accumulation, thousand grain weight, and soybean productivity. Treatments: Maize (Soybean cultivated with plant residues of maize without integration with forages), Tamani (Soybean cultivated with plant residues of Tamani guinea grass without integration with maize), Zuri (Soybean cultivated with plant residues of Zuri guinea grass without integration with maize), MTL: maize + Tamani within rows (Soybean cultivated with plant residues of Tamani guinea grass planted within rows of maize plants), MTE: maize + Tamani between rows (Soybean cultivated with plant residues of Tamani guinea grass planted between rows of maize plants), MZL: maize + Zuri within rows (Soybean cultivated with plant residues of Zuri guinea grass planted within rows of maize plants), MZE: maize + Zuri between rows (Soybean cultivated with plant residues of Zuri guinea grass planted between rows of maize plants), and Soybean (traditional Soybean monoculture without soil cover residues). Biomass&#x2009;=&#x2009;biomass production. Nitrogen, Phosphorous, Sulfur, weight: the thousand grain weight, productivity&#x2009;=&#x2009;soybean productivity.</p>
</caption>
<graphic xlink:href="fsufs-07-1224530-g006.tif"/>
</fig>
</sec>
</sec>
<sec sec-type="discussions" id="sec16">
<label>4.</label>
<title>Discussion</title>
<sec id="sec17">
<label>4.1.</label>
<title>Desiccation efficiency, biomass production, and C:N ratio</title>
<p>In this study, we observed a greater desiccation efficiency of Tamani guinea grass. This result is presumably associated with the large proportion of leaves of this cultivar., making it more susceptible to glyphosate. On the other hand, Zuri guinea grass showed an efficiency of only 78% at 21&#x2009;days after desiccation. This lower efficiency can be explained by the morphology of this forage, which has a greater number of tussocks (<xref ref-type="bibr" rid="ref31">Rhodes et al., 2021</xref>). However, Zuri guinea grass in monoculture, followed by Zuri guinea grass in consortium, showed the highest biomass production and remaining biomass after a few weeks of decomposition. This result can be explained by the morphology of this cultivar., which has a tall size, high production of dry mass per hectare, caespitous growth, high regrowth vigor, and elevated production of support structures such as stems, demonstrating its high potential for biomass production (<xref ref-type="bibr" rid="ref1">Almeida et al., 2022</xref>). In addition, Zuri guinea grass is recognized as a drought tolerant cultivar (<xref rid="fig1" ref-type="fig">Figure 1</xref>) and moderately adapted to conditions of excessive soil moisture (<xref ref-type="bibr" rid="ref6">Bonfim-Silva et al., 2022</xref>).</p>
<p>It is important to highlight that at the end of the soybean cycle, the remaining biomass (<xref rid="fig3" ref-type="fig">Figure 3A</xref>) of Zuri guinea grass in monoculture and intercropped were higher by 25% compared to Tamani guinea grass in monoculture (1,753&#x2009;kg&#x2009;ha<sup>&#x2212;1</sup>) and 50% when compared to maize (1,166&#x2009;kg&#x2009;ha<sup>&#x2212;1</sup>), demonstrating that Zuri guinea grass provided the greatest soil cover during the soybean cycle. Moreover, it is important to note that the biomass produced by Zuri guinea grass in the different cultivation systems provided greater soil coverage until soybean harvest, demonstrating the potential to ensure production stability and soil protection in cases of dry spells. The results reported in this study are relevant in the decision making of the correct choice of forage, especially considering the Brazilian Savannah (Cerrado) located in the central region Brazil, which presents high temperatures throughout the year (<xref ref-type="bibr" rid="ref46">Zagato et al., 2018</xref>).</p>
<p>Maize biomass remained in the soil between May and November 2021 (off-season) and had more time of decomposition when compared to forages. Although maize biomass has a large number of stalks, increasing the decomposition time on the soil surface, it has a small soil cover, corroborating the results reported by <xref ref-type="bibr" rid="ref15">Dias et al. (2020)</xref> and <xref ref-type="bibr" rid="ref26">Muniz et al. (2021)</xref>. The biomass produced by maize + Zuri guinea grass in both sowing methods showed a longer half-life with an average of 103&#x2009;days. This result can be explained by the fact that maize and Zuri guinea grass both have a high proportion of stems, a higher proportion of lignin and a high C:N ratio in the residues, promoting greater persistence of soil cover (<xref ref-type="bibr" rid="ref10">Chen et al., 2021</xref>; <xref ref-type="bibr" rid="ref31">Rhodes et al., 2021</xref>). However, as previously mentioned, maize biomass does not provide adequate soil cover.</p>
<p>The amount of time that biomass remains in the soil is determined by the rate of decomposition, which is directly influenced by the C:N ratio and lignin content of the residue (<xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). According to <xref ref-type="bibr" rid="ref42">Truong and Marschner (2018)</xref>, C:N ratio values between 12 and 25 contribute to mineralization, while values above 50 contribute to the immobilization of nutrients in the soil. Therefore, an adequate range from 25 to 30 is ideal to balance mineralization and immobilization. Corroborating the findings of <xref ref-type="bibr" rid="ref25">Mingotte et al. (2020)</xref>, we found that in all evaluated decomposition times, the highest C:N ratio was observed for maize biomass, as shown in <xref rid="fig3" ref-type="fig">Figure 3B</xref>. According to <xref ref-type="bibr" rid="ref24">Miguel et al. (2018)</xref>, maize has a higher proportion of recalcitrant material (stem, cob, and straw), and the action and penetration of decomposing microorganisms is hampered due to the high concentration of fibers that confers resistance to the material. In the opposite direction, forage cultivation systems in monoculture or in intercropped showed lower values of C:N ratio in all decomposition periods. This result can be explained by the high ratio of leaves to stems that both cultivars have, leading to more intense biomass decomposition (<xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>), especially for Tamani guinea grass, which presented the lowest C:N ratio. Different from what was observed for maize, biomass production produced an adequate amount of soil cover which remained in the soil until the final cycle of soybean development (<xref rid="fig3" ref-type="fig">Figure 3A</xref>).</p>
</sec>
<sec id="sec18">
<label>4.2.</label>
<title>Accumulation and nutrient release from plant residues</title>
<p>According to our results, Tamani guinea grass produced the soil cover with the highest N concentration, presumably because this cultivar has a higher proportion of leaves, greatly contributing to the ecosystem N cycling (<xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). N and K are the nutrients most extracted by forage plants (<xref ref-type="bibr" rid="ref13">Costa et al., 2017</xref>) but at the same time, these nutrients are easily leached. Therefore, through its deep and aggressive root system, forage plants can absorb nutrients from deep layers and release them on the soil surface, benefiting the subsequent crop (<xref ref-type="bibr" rid="ref5">Baptistella et al., 2020</xref>; <xref ref-type="bibr" rid="ref12">Costa et al., 2021</xref>). We also observed a high N, P, K, and S accumulation in treatments containing Zuri guinea grass (<xref rid="fig4" ref-type="fig">Figure 4</xref>), which is presumable associated with the elevated production of biomass in these treatments (<xref rid="tab1" ref-type="table">Table 1</xref>), where the accumulated nutrients were deposited in the soil and supplied the soybean demands, especially N, since in its initial phase, soybeans still do not present an efficient N fixation by biological activity (<xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). According to <xref ref-type="bibr" rid="ref28">Oliveira Junior et al. (2016)</xref>, from all the N that soybean demands (190&#x2013;372&#x2009;kg&#x2009;ha<sup>&#x2212;1</sup>), around 65&#x2013;85% of N comes from biological fixation, while the rest is provided by the soil.</p>
<p>Corroborating the findings of <xref ref-type="bibr" rid="ref24">Miguel et al. (2018)</xref>, <xref ref-type="bibr" rid="ref5">Baptistella et al. (2020)</xref>, and <xref ref-type="bibr" rid="ref12">Costa et al. (2021)</xref>, K showed the shortest half-life (t&#x00BD;) of all nutrients. K is easily released from the plant tissue, since it is not part of any structure or organic molecule, being predominantly a free cation with high mobility in plants, being easily washed by rainwater after the disruption of plasma membranes (<xref ref-type="bibr" rid="ref38">Taiz et al., 2017</xref>). In our study, K showed a release rate above 95% for all cropping systems with soil cover biomass. Since here we do not apply K fertilizer in treatments with soil cover, soil biomass contributed to the greater cycling rate of this nutrient, which is the most absorbed by soybean plants. During the soybean growing season, K sharply decreased its amount in the residues, corroborating the observations made by <xref ref-type="bibr" rid="ref15">Dias et al. (2020)</xref> and <xref ref-type="bibr" rid="ref26">Muniz et al. (2021)</xref>. It is noteworthy that at the end of the soybean cycle (120&#x2009;days), the remaining amount of K in the biomass was less than 5% of the total initial amount. In the opposite direction, the longest half-life (t&#x00BD;) for all nutrients was observed in maize monoculture treatment followed by Zuri guinea grass in monoculture and in consortium. The higher lignin content and C:N ratio of these crops, mainly maize, contributes to the immobilization of nutrients (<xref ref-type="bibr" rid="ref31">Rhodes et al., 2021</xref>).</p>
<p>Soybean accumulates most of the macronutrients between 82 and 92&#x2009;days of its development, and the highest absorption rate occurs between 39 and 58&#x2009;days (<xref ref-type="bibr" rid="ref8">Carmello and Oliveira, 2006</xref>). In the present study, the half-life of nutrients averaged 53, 66, 34, and 59&#x2009;days for N, P, K, and S, respectively, with a release above 78% at 120&#x2009;days of decomposition, demonstrating the potential of forages as supply of nutrients for soybean crop. The increased biomass production by Tamani and Zuri guinea grasses in monoculture and intercropped resulted in higher values of N and P fertilizer equivalent. According to our results, Zuri guinea grass in monoculture seems to be the most efficient cultivar in returning K to the soil, which can also be explained by the higher biomass production that this forage produced. The biomass produced by maize provided lower values of equivalent in fertilizers. This result shows the importance of forages in the nutritional balance of plants in integrated production systems, where part of the nutrients is returned to the soil by the mineralization process.</p>
<p>In the integrated systems is important to consider how much nutrients will be release from plant residues when calculating fertilizer recommendations, as a large proportion of these nutrients returns to the soil (<xref ref-type="bibr" rid="ref9001">Assmann et al., 2017</xref>). Our study shows the saving of mineral fertilizer (<xref rid="tab2" ref-type="table">Table 2</xref>), with greater emphasis on the biomass produced by Zuri guinea grass, which showed savings of 185&#x2009;kg of urea, 80&#x2009;kg of simple superphosphate and 142&#x2009;kg&#x2009;ha<sup>&#x2212;1</sup> of potassium chloride. This elevated amount of equivalent in nutrients obtained from plant residues can help producers to obtain a greater productivity reducing the cost of mineral fertilizers (<xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>).</p>
</sec>
<sec id="sec19">
<label>4.3.</label>
<title>Agronomic traits and productivity of soybean</title>
<p>The integrated crop-livestock system is a promising and sustainable technique for producing biomass for no-tillage systems, positively influencing the productivity of cultivated plants. In this study, we observed the clear benefits of integrated systems for soybean growth and grain productivity. In the cultivation systems with Tamani and Zuri guinea grasses intercropped or not, plant height, insertion of the first pod, and the number of pods per soybean plant were higher, presumably due to the higher amount of plant residues produced by each forage and the release of nutrients. Our results also demonstrate that the release of nutrients by plant residues was synchronized with the nutrient absorption by soybean plants during their development cycle, improving soybean productivity (<xref ref-type="bibr" rid="ref12">Costa et al., 2021</xref>). These results have also been corroborated in other studies with different integration systems (<xref ref-type="bibr" rid="ref39">Tanaka et al., 2019</xref>; <xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>; <xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>; <xref ref-type="bibr" rid="ref30">Pires et al., 2022</xref>).</p>
<p>The weight of 1,000 grains is a component of soybean yield, directly related to crop productivity. In this study, the highest values of the weight of 1,000 grains were obtained in cropping systems with soil cover biomass. Moreover, we observed higher grain yields, in integrated systems. All these previous results have been corroborated by other recent studies (<xref ref-type="bibr" rid="ref15">Dias et al., 2020</xref>; <xref ref-type="bibr" rid="ref27">Oliveira et al., 2020</xref>; <xref ref-type="bibr" rid="ref12">Costa et al., 2021</xref>; <xref ref-type="bibr" rid="ref26">Muniz et al., 2021</xref>). Higher soybean yields are related to improvements in soil biochemical and biological properties, which are positively influenced by integrated systems. In fallow areas during the off-season, the accumulation of biomass and nutrient absorption by soybean in the succession system is negatively affected, especially in years with unfavorable weather conditions, compromising crop productivity (<xref ref-type="bibr" rid="ref37">Soratto et al., 2022</xref>). Therefore, the correct choice of forage and sowing method to compose the crop-livestock integration system optimizes land use, increases the diversity of production, and reduces the use of mineral fertilizers, bringing greater sustainability to agricultural systems. PCA analyses also reinforced our results by grouping Zuri and Tamani guinea grasses (Groups 3 and 4) due to the greater productivity, nutrient accumulation, and soybean productivity when compared to maize in monoculture and soybean without soil cover (Groups 1 and 2).</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec20">
<label>5.</label>
<title>Conclusion</title>
<p>Tamani guinea grass showed the highest desiccation efficiency.</p>
<p>Zuri guinea grass in monoculture and intercropped in the two forms of sowing provided greater biomass production and nutrient cycling. However, both Zuri and Tamani guinea grass can be indicated as cover crops for positively influencing agronomic characteristics and soybean productivity.</p>
<p>Integrated systems with tropical forages for soil cover proved to be an efficient technique for biomass production and nutrient cycling since it makes better use of soil nutrients and contributes to the sustainability of agricultural systems in tropical regions.</p>
</sec>
<sec sec-type="data-availability" id="sec21">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref rid="SM1" ref-type="supplementary-material">Supplementary material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="sec22">
<title>Author contributions</title>
<p>JS, KC, and LS wrote the manuscript. JS, LS, JC, and KO collected data in the field and processed the data. KC, AC, EH, and ES contributed with statistical analysis. JS, KC, ES, EH, LV, FS, CM, AS, and AC conceived and designed the experiments. All authors contributed to the revision of the manuscript.</p>
</sec>
<sec sec-type="funding-information" id="sec23">
<title>Funding</title>
<p>This work was supported by National Council for Scientific and Technological Development (CNPq) and Coordination of Superior Level Staff Improvement (CAPES). CNPq provided a scholarship for Jo&#x00E3;o Victor Campos Pinho Costa (process 138753/2022&#x2013;9). CAPES provided scholarships for Jo&#x00E3;o Ant&#x00F4;nio Gon&#x00E7;alves e Silva (process 88887.718294/2022&#x2013;00) and Luciana Maria da Silva (process 88887.613180/2021&#x2013;00).</p>
</sec>
<sec sec-type="COI-statement" id="sec24">
<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 id="sec100" sec-type="disclaimer">
<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>
</body>
<back>
<ack>
<p>The authors thank the Instituto Federal Goiano for supporting this study and the Coordination for the Improvement of Higher Education Personnel (CAPES) for granting the PhD scholarship.</p>
</ack>
<sec sec-type="supplementary-material" id="sec25">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fsufs.2023.1224530/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fsufs.2023.1224530/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Image_1.JPEG" id="SM1" mimetype="image/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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