Temperature is the fundamental component in describing the actual state of climate change in the entire world. Extreme temperature has far-reaching consequences for human and nonhuman life (Choufani et al., 2017; Watts et al., 2018). Since 1880, the average global temperature has risen by 0.14°F (0.08°C) each decade, which is twice the rise after 1981, 0.32°F (0.18°C) each decade. According to the National Oceanic and Atmospheric Administration Agency’s (NOAA) climate change data Wana et al., 2021 had become the sixth warmest year when the average surface temperature was 1.51°F (0.84°Celsius), the warmest in the twentieth century,¹⁴ posing severe food security and health risk, especially to those already susceptible to the effects of extreme heat (Choufani et al., 2017; Watts et al., 2018). Likewise, temperature increases lead to more extreme weather events, including droughts, storms, floods and typhoons, which deplete natural resources and threaten food security (including availability, safety, and sustainability; Godde et al., 2021). On a detailed note, global warming, including the increase in day and night temperature (Jha and Tripathi, 2017) and pollution, severely impacted and caused a 5.2% drop in the wheat crop from 1981 to 2009 in India (Gupta et al., 2017). Changes in weather patterns have also had an impact on Pakistan’s agricultural sector. In 2010–2014, Pakistan was hit by a rapid sequence of its four most enormous floods, which resulted in significant losses of cattle, agriculture, forest, and fishing, as well as the destruction of critical agricultural systems (Arora, 2019; Ahmad and Afzal, 2022). The severe flooding in 2022 resulted in an aggregate economic loss of 30 billion United States dollars, damaged an agricultural area equivalent to 1.2 million hectares alone in Sindh, 61% farming community exposed with transboundary animal disease in Baluchistan and 755,000 animals were lost in the flood in Pakistan.¹⁵ Similarly, Indonesia, China, Bangladesh, Malaysia are facing the temperature change severely which impact their food security.

According to the Food and Agriculture Organization of the United Nations (FAO), arable land is used for short-term agricultural purposes, such as seasonal crops, grazing or home gardening. In contrast, agricultural land refers to long-term agricultural purposes, such as cultivating crops and meadows.¹⁶ Agriculture and arable land play a preemptive role in ensuring food security, which combines the three components: availability of food, food access, and food utilization (Aisyah et al., 2020). However, food consumption is expected to rise by 59–102% due to the world population’s rapid rise; in 2018,¹⁷ the world population was 7.6 billion, which is expected to reach 9.7 billion in 2050 (Elferink and Schierhorn, 2016; Fukase and Martin, 2020). These high demands are imposing a burden on the agriculture sector to provide enough supply to meet the required demand, which can be done in one of two ways: either by expanding the amount of land used for agriculture or by enhancing the existing agricultural land’s productivity through the use of fertilizer, precision farming and novel technology (Genetically modified crops and food) (Ali et al., 2019; Fukase and Martin, 2020; Pawlak and Kołodziejczak, 2020). Researchers preferably support the idea of increasing the productivity of the existing cultivation land by inducting precision farming and genetically modified crops (which are more resilience to the harsh environment along with high productivity) relative to the expansion of the agriculture and arable land (Ali et al., 2019, 2021; Pawlak and Kołodziejczak, 2020), resulting the deforestation (Bahar et al., 2020). The impact of prudent land management on productivity and food security is an evolving area of investigation in China (Du et al., 2018). In 2019, although the Indian cultivated land area became the largest in the world, however the country’s per unit production remained lower than most of the countries and contributed little to improving the country’s food security situation (Li and Song, 2023). Similarly, Pakistan has experienced land cover and land use increment while facing a production reduction and contributing to the rise of land surface temperature (Hussain et al., 2020). While the Bangladesh facing the challenges of soil salinity, tidal flooding, and erosion which is imparing the production capacity of farmers and pressuring the food security outlook of the country (Parven et al., 2022). Alike Bangladesh Indonesia is also encountering the adverse effect of land-use change on the national food security levels (Chrisendo et al., 2020; Rozaki, 2021). Malaysia is also encountering a land use change phenomenon which is exerting sever pressure on the country’s ability to contribute locally in its food security outlook (Azizan and Hussin, 2015).

Fertilizers are generally classified as either organic or inorganic, where organic fertilizers are made up of enhanced organic matter derived from plants or animals, while inorganic fertilizers are made up of manufactured chemicals like nitrogen, phosphate, and potash (Heinrich, 2000) which are used as soil additive that provides certain nutritional levels to the soil to enhance the productivity of the crop (Hammed et al., 2019). Theriault et al. (2018) found that in the West African Sahel, fertilizers boost land productivity and crops yield 24.1 kg per ha by including nitrogen each kg per ha. Likewise, Belete et al. (2018) explained that wheat varieties Menze, ET-13 and Tsehay produced a high yield because of the fertilizer (nitrogen). Some researchers also argued that overuse of fertilizers does not increase productivity; sometimes, it increases the productivity of some products and sometimes does not have a significant effect (Sheahan and Barrett, 2017; Belete et al., 2018; Van Wesenbeeck et al., 2021). Therefore, it is crucial to understand the land nutrition values and crops that farmers will cultivate. For instance, wheat needs 17 essential nutritional components, three of which are hydrogen, carbon and oxygen, while the remaining 14 come from the soil and mostly from plants, animals, compost, manure, or mineral fertilizers (Panhwar et al., 2019). In this case, nitrogen (N) is only required at the time of the deficiency (Panhwar et al., 2019). China classifies its cultivated land through a 10-grade classification system where grade 1 classifies the best land for cultivation and the 10 attributes to the low-quality land. In 2019, the average grade of the land was 4.76, and two-thirds of the soil was of low to medium quality, indicating the deficiencies that needed to be covered to increase land productivity.¹⁸ Similarly, in India, 55% of the soil is nitrogen (N) deficient, and 42% is deficient in phosphorus (P), making India an intensive user of fertilizers to augment productivity.¹⁹ Soil nutrient deficiency, which has been attributed as a vital factor in low yielding, has also been reported by Pakistan. The deficient nutrients in Pakistani soil, like India, are also nitrogen (N), phosphorus (P), and potassium (K) (Saber et al., 2009; Thanh et al., 2018). The soil nutrient deficiency has been recorded in indonesia as well where the studies have reported the deficiency of nitrogen (N), phosphorus (P), potassium (K), and organic carbon; needing various areas to employ different proportions of fertilizers for the enhancement of land productivity (Prasetyo et al., 2022). In Bangladesh, significant reduction in potassium (K), boron (B), copper (Cu), iron (Fe), manganese (Mn), and zinc (Zn), whereas an increase in calcium (Ca), and magnesium (mg) was recorded; indicating the proportions of fartilizers needed for enhancing crop yields (Shamim et al., 2019). Malaysia is also encountering the potassium (K), phosphorus (P), sulfur (S), and boron (B) deficiency; requiring it to use fartilizers for augmenting productivity (Lai et al., 2019).

According to traditional consumption-based accounting research, fixed capital consumption is the fulfilment of the actual demand for household needs (Kanemoto et al., 2020; Kobayakawa, 2022) by food products from agriculture, fishing and forest that are the bare necessities and embedded in food security (Garcia et al., 2020). Likewise, the production and consumption of fixed capital are tightly intertwined (Södersten et al., 2018). Therefore, fixed capital allows us to utilize resources to enhance agricultural productivity, which assists in subsiding the food shortage problems (Fukase and Martin, 2020). Developing populous countries like China, India, Pakistan, Bangladesh, Indonesia, and Malaysia encounter the challenges of forming fixed capital and increasing consumption in the sector where the masses need it the most; they can overcome these shortcomings through foreign direct investment and strategic technology sharing in the food sector (Liu, 2014; Slimane et al., 2016) to attain the United Nations sustainable development goal of “Zero Hunger” and attain the food security for the masses.

The study investigates the impact of environmental temperature surges, arable land, agricultural land, fertilizer and consumption of fixed capital on food security in the context of six populous Asian countries: China, India, Indonesia, Pakistan, Bangladesh, and Malaysia. The study analyzes these indicators spanning from 2016 to 2020. The study relies on the data available on public databases such as FAOstat,²⁰ World Bank,²¹ Economist Impact²² and national statistics bureaus (see Table 1). The United Nations (UN) database reasonably defines the grasp of distinct indicators and explains the methods opted for their computation and the measures employed for the validation; the same criteria are considered while employing the data obtained from sources other than the UN. Moreover, the study analyzes the models through the panel data analysis approach, a widely used methodology that primarily accommodates the analysis entailing both spatial and temporal dimensions (Yaffee, 2003; Chen et al., 2019).

This article goes through the most common panel data analysis models in academic papers (Greene, 2003; Baltagi, 2008; Hsiao, 2022). The panel data approach sheds light on both temporal and spatial dimensions. The temporal dimension covers the data collected through periodic measurements, and the spatial dimension presents the level at which we observe phenomena such as individual actions and reactions, national and organizational decisions and trends (Wooldridge, 2015; Hsiao, 2022).

Mathematically generic regression model of panel data looks like this:

Where j is the observation unit, t time, k indicates the k^th explanatory variable, β₀ intercept, β_k represents the coefficient of the k^th explanatory variable, and ( v j t ) is the error term which is divided into two sub-components like ( b j ) representing the unit-specific cross-sectional error that refers to the fixed effects, unobserved heterogeneity and also the unobserved effect in the literature, which does not vary over time and ( u j t ) represent the idiosyncratic error that changes with time and cross-sectional units (Baltagi and Kao, 2001; Greene, 2003; Baltagi, 2008; Wooldridge, 2015; Hsiao, 2022). Moreover, using panel data and separating the error terms into two categories allows us to alleviate some concerns about bias in omitted variables due to unquantified unit-specific characteristics.

Thus, by integrating Equations (1, 2):

Similarly, the model employed in this study is as follows:

In Equation 4, FS represents food security, TS is environmental temperature surges, ARL is arable land, AGL is agricultural land, N is Nutrient nitrogen, PH is Nutrient phosphate P₂O₅, and CFC is the consumption of fixed capital.

Scholars often assume the data has a Gaussian or normal distribution and conduct analyses like Pearson correlation, regression, and variance that rely on this assumption to draw valid conclusions about the results of the proposed models (Wooldridge, 2015; Hsiao, 2022). However, this assumption can backfire if the data does not actually follow a Gaussian or normal distribution; if this is the case, the scholars have invested their time and effort in the wrong direction instead of employing the non-parametric techniques such as the spearman correlation test, polynomial regression, Wilcoxon rank sum test, the Mann–Whitney U test, and the Kruskal test (Ghasemi and Zahediasl, 2012; Field, 2013; Derrick et al., 2020). Therefore, first, we checked the normal distribution of the data, which helped us to transform the data as per the valid and accurate transformation technique. Thus, in this study, we normalized (Yu et al., 2009) the data on the 0 to 100 scale and performed the normality test to confirm our assumption was valid, and Table 2 shows that Shapiro Wilk W results meet the minimum criteria (Ghasemi and Zahediasl, 2012; Derrick et al., 2020).

We obtained the baseline regression results by relying on the more appropriate model between the fixed and the random; the Hausman test results (Baltagi, 2008; Bartels, 2008) provided the foundation for the model selection. For this reason, we utilized STATA 17 to analyze the model selection and proposed relationship association. First, in STATA, we set the data as a panel time series data, then we performed the fixed effect regression and stored their values. Afterwards, we performed the random effect regression and stored their values; then, we used the Hausman test command on the stored values. Results of the Hausman test favored the fixed effect because the p value of the Chi-square is less than 0.05 (see Table 3; Hausman, 1978; Baltagi, 2008; Bartels, 2008). Hence, the fixed effect is more suitable for the problem investigated in this study. However, it is also imperative to determine whether the time-fixed effect contributes to the baseline regression outcomes. Thus, we performed the testparm yearly and found Prob > F is non-significant, meaning that accounting for the time-fixed effect is not needed in the present situation (Torres-Reyna, 2007).

Finally, we selected the fixed effect model to investigate the impact of the change in temperature, arable land, agricultural land, fertilizers such as nutrient nitrogen and phosphate and the consumption of the fixed capital on food security. We found that temperature change and arable land have a significantly adverse effect on food security; meanwhile, expansion of the agricultural land, use of fertilizers based on the soil nutrient information and consumption of the fixed capital in the agriculture sector have a positive impact on food security (see Table 4).

United Nations established 17 sustainable development goals along with 169 sub-targets as an urgent call for the globe to actively pursue the agenda of the greater good for the betterment of humanity and the entire world’s sustainability and prosperity. In this regard, the United Nations encourages developed and developing nations to have a global partnership to eradicate the world’s most critical problems; one of these critical problems is global hunger for the eradication of which the UN devised its second SDG with the focus of attaining “zero hunger” by 2030. Thus, this study investigates zero hunger through the lens of food security in populous Asia from the perspectives of the pre-and post-pandemic eras. The findings of this study explain that temperature change negatively affects food security. The temperature surge breeds unfavorable conditions for agricultural products and human life, evidenced by the low productivity of staple crops like wheat in India and Pakistan during unprecedented heat waves and loss of life due to heat strokes pointing toward the far-reaching consequences (Choufani et al., 2017; Watts et al., 2018). Notably, our findings are aligned with previous research, which highlights that the temperature changes (rise 0.08°C to 0.84°Celsius) around the globe cause unprecedented weather events like floods, drought, storms, and typhoons which are the primary source of natural resources’ impairment and threaten food security (including availability, safety, and sustainability) (Choufani et al., 2017; Watts et al., 2018; Godde et al., 2021). For instance, from 1981 to 2009, India saw a 5.2% decline in its wheat crop due to global warming, soil nutrient deficiency (Gupta et al., 2017), and related factors such as rising day and nighttime temperatures (Jha and Tripathi, 2017). In Pakistan, the impact was more devastating; it endured damage to 78,000 square kilometers (30,000 square miles) of agricultural land throughout 81 districts, and more than 80 per cent of the nation’s crops were ravaged. The Sindh province, which provides a significant portion of the nation’s food, is among the most severely impacted.²³ We saw the same temperature rise trend, threatening the food supply in places like Indonesia, China, Bangladesh, and Malaysia.

Second, the results of this study show that arable land negatively affects food security due to the expansion of arable land and its use for grazing or home gardening and tree cultivation, indirectly affecting agricultural crop production. In contrast, agricultural land positively influences food security because it is the primary source of food production. While the world has an overpopulation burden, in 2018 global population was 7.6 billion which is projected to reach 9.7 billion by 2050 (Elferink and Schierhorn, 2016; Fukase and Martin, 2020); especially Asia contributing a significant portion of this rise. As a result, food consumption is bound to depict a surge of 59 to 102%.²⁴ The impact of these issues can be diminished by extending the agricultural land area for agricultural production or boosting land productivity by utilizing fertilizers based on the soil nutrient deficiencies as it is garnering positive results in the under-instigation countries, coupled with the new technologies such as genetically modified (GM) crops and food in the agriculture sector (Ali et al., 2019; Fukase and Martin, 2020; Pawlak and Kołodziejczak, 2020). The adoption of GM crops is seeing a rising trend in China, India, and Pakistan mostly because of the tendency of these crops to perform in even harsh climatic conditions, protect themselves from insect attacks, have the reputation of a safe product, and be nutritionally rich (Ali et al., 2019, 2021). The option of agricultural land expansion can trigger deforestation (Bahar et al., 2020), harming the environment, ecosystem and food security. For a sustainable solution, experts usually suggest the mass production of crops and food on the existing land through innovative techniques such as drip irrigation, drone seeding, technologically modified crops and food cultivation without utilizing extensive natural resources (Ali et al., 2019, 2021; Pawlak and Kołodziejczak, 2020).

Third, this study’s findings show that nitrogen and phosphate positively influence food security. Fertilizers are considered soil additives that enhance land nutrient values that support the crop’s productivity (Hammed et al., 2019). Similarly, our findings align with previous research (Belete et al., 2018; Theriault et al., 2018; Hammed et al., 2019; Panhwar et al., 2019; Ghufran et al., 2024), explaining that fertilizers boost land productivity and crop yield. Evidence from all under-investigation countries (China, Pakistan, India, Bangladesh, Indonesia, Malaysia) also supports that using fertilizers based on soil nutrient deficiencies augments land productivity. The approach promoted by several experts for effective fertilizer utilization while warning about the misusage of fertilizers, causing productivity loss and adverse effects on human health (Sheahan and Barrett, 2017; Belete et al., 2018; Van Wesenbeeck et al., 2021). Hence, our findings endorse fertilizer utilization to cover the soil nutrient gap, bolstering land productivity and subsiding human health risks.

Fourth, in this study, we find that fixed capital consumption substantially influences food security because it is tightly intertwined (Södersten et al., 2018) and satisfies genuine household needs, such as essential foods products derived from agriculture, fishing, and forestry that contribute to food security (Garcia et al., 2020; Kanemoto et al., 2020; Kobayakawa, 2022). As a result, the availability of fixed capital enables economies to capitalize on opportunities for enhancing agricultural output and curtailing the challenges like food scarcity (Fukase and Martin, 2020). Hence, foreign direct investment and strategic technology sharing in the food sector can augment developing and underdeveloped countries’ ability to form fixed capital and direct its consumption in the sector where they need it the most (Liu, 2014; Slimane et al., 2016) to achieve the United Nations sustainable development goal of “Zero Hunger” from the perspective of food security.