Resilient Agriculture Research Articles

Optimizing Agricultural Yields with Artificial Intelligence-Based Climate Adaptation Strategies

In the face of climate change, agricultural productivity is severely threatened by unpredictable weather patterns and changing environmental conditions, underscoring the critical need for innovative solutions to bolster agricultural resilience and optimize yields. This study delves into the potential of artificial intelligence (AI), specifically through the use of machine learning and deep learning techniques, to develop climate adaptation strategies aimed at enhancing agricultural outcomes. By integrating AI with climatological data, the research predicts and mitigates the adverse impacts of climate on crop yields, utilizing a combination of machine learning and deep learning models to analyze historical climate data alongside crop performance. These models, trained on datasets including temperature, rainfall, soil moisture, and crop genetic information, are adept at forecasting future agricultural outcomes under varied climatic scenarios and suggest optimal adaptation strategies that significantly improve crop yields. Consequently, these AI-based models serve as robust tools for farmers and agricultural policymakers, enabling them to make informed decisions that are aligned with anticipated climatic conditions. The findings not only underscore the efficacy of AI in transforming data into actionable insights that enhance agricultural productivity but also contribute to the field of agricultural science by providing a technologically advanced approach to climate adaptation. Furthermore, this research paves the way for future studies on the integration of AI with real-time environmental sensing technologies, thereby offering a dynamic framework for agricultural management that supports sustainable farming practices and global food security amid climate challenges.

Geospatial Models for Predictive Agricultural Risk Assessment and Mitigation in Vulnerable Landscapes

This study addresses complex agricultural risk assessment under simplified conditions through a multi-pronged approach. The research problem focuses on the interactions among soil moisture, vegetation cover, and land use patterns influencing agricultural risks. Using mixed methods, we research soil internal analysis, mathematical modelling, and stakeholder insights. Stratified objective sampling ensures representative data sets and various geospatial tools, including Geographic Information System (GIS) software and remote sensing platforms, are subject to data analysis. Our study reveals a positive relationship between soil moisture and vegetation cover and establishes the role of highlighting the importance of water use in agricultural resilience -Use distribution analysis reveals spatial patterns, which identify targeted strategies for risk mitigation. Soil composition data enhance our understanding of soil health, providing usable insights for sustainable agriculture. These results contribute significantly to the existing body of knowledge and emphasize the importance of understanding detailed agricultural systems under sensitive conditions. Future research should examine temporal dynamics, socioeconomic implications, and adaptive geospatial models to support decision-making. Our research provides valuable insights for practitioners, policymakers and researchers and advances the understanding of agricultural risk in dynamic contexts.

RESILIENCE OF FARMERS ON THE SUSTAINABILITY OF NATURAL FARMING SYSTEMS FOR UPLAND RICE IN MOROTAI ISLAND

Objective: Sustainable agricultural development necessitates that every region of the world discovers or develops farming practices and systems suited to the local environment. Additionally, initiators encourage the adoption and spread of more sustainable agriculture methods. This study aimed to determine: 1) the resilience of farmers concerning the principles of natural farming methods for upland rice to the level of economic sustainability, 2) the resilience of farmers concerning the principles of natural farming systems for upland rice to the level of socio-cultural sustainability, 3) the resilience of farmers concerning the principles of natural farming systems for upland rice to the level of environmental sustainability, 4) the willingness of farmers to retain the economic viability of the natural farming system of upland rice, 5) the willingness of farmers to retain the environmental viability of the natural farming system of upland rice, and 6) the willingness of farmers to preserve the socio-cultural sustainability of the natural farming system of upland rice. Method: This research was conducted on Morotai Island, North Maluku Province. The selection of this region was purposive, while the selection of farmers as sample respondents was determined by random sampling. Data were analyzed using Structural Equation Modeling (SEM) and LISREL 8.70. Results: According to the research findings, farmers' perceptions of natural farming systems are a determining factor in farmer resilience. This factor has a positive impact on the sustainability of socio-cultural and environmental aspects but does not affect the sustainability of the economic component. Meanwhile, the willingness to maintain natural farming systems is a resilience element for farmers that influences the sustainability of economic and socio-cultural dimensions but not the environmental component. This study concludes that farmer resilience to the principles of natural upland rice farming systems in the border region of Morotai Island has distinct characteristics and is an economically, socio-culturally, and environmentally sustainable agricultural system. Conclusion: This study concludes that the resilience of farmers to the principles of natural upland rice farming systems in the border region of Morotai Island has a distinctive character and is an economically, socioculturally, and environmentally sustainable agricultural system.

Climate change and farmers' perception in Sivakasi taluk, India: a nexus and a suggestion for sustainable water reuse

Abstract Climate change poses a major threat to agriculture and food security, especially in developing countries where farmers depend on rainfall and groundwater for irrigation. This paper investigates how farmers in Sivakasi taluk, Tamil Nadu, India perceive and respond to climate change – rainfall and temperature – and its impacts on agriculture. Actual rainfall and temperature data are analyzed using Mann–Kendall test and Sen's slope estimator test, and the results are compared against the farmers' perceptions obtained through a questionnaire survey. The trend analysis showed an insignificant decrease in rainfall and a significant increase in temperature. Most farmers perceived rainfall change correctly, but not temperature change. It is found that water scarcity is a major challenge for agriculture due to reduced rainfall, increased temperature, and inadequate adaptations. To address this challenge, water reuse is proposed as a sustainable alternate adaptation that involves using treated wastewater (TWW) from a decentralized sewage treatment plant for irrigation. An index named Water Reuse Index (WRI) is developed to estimate the fraction of TWW that can replace freshwater irrigation. This study provides insights into farmers' perception of climate change and suggests a novel way to enhance water security and resilience in agriculture.

A 3D-printed hollow microneedle-based electrochemical sensing device for in situ plant health monitoring

Plant health monitoring is devised as a new concept to elucidate in situ physiological processes. The need for increased food production to nourish the growing global population is inconsistent with the dramatic impact of climate change, which hinders crop health and exacerbates plant stress. In this context, wearable sensors play a crucial role in assessing plant stress. Herein, we present a low-cost 3D-printed hollow microneedle array (HMA) patch as a sampling device coupled with biosensors based on screen-printing technology, leading to affordable analysis of biomarkers in the plant fluid of a leaf. First, a refinement of the 3D-printing method showed a tip diameter of 25.9 ± 3.7 μm with a side hole diameter on the microneedle of 228.2 ± 18.6 μm using an affordable 3D printer (<500 EUR). Notably, the HMA patch withstanded the forces exerted by thumb pressing (i.e. 20-40 N). Subsequently, the holes of the HMA enabled the fluid extraction tested in vitro and in vivo in plant leaves (i.e. 13.5 ± 1.1 μL). A paper-based sampling strategy adapted to the HMA allowed the collection of plant fluid. Finally, integrating the sampling device onto biosensors facilitated the in situ electrochemical analysis of plant health biomarkers (i.e. H2O2, glucose, and pH) and the electrochemical profiling of plants in five plant species. Overall, this electrochemical platform advances precise and versatile sensors for plant health monitoring. The wearable device can potentially improve precision farming practices, addressing the critical need for sustainable and resilient agriculture in changing environmental conditions.

Climate-Smart Agriculture: Climate Change-Friendly and Resilient Agriculture

The world is now facing a dilemma because; on the one hand, agriculture intensification to feed the skyrocketing population entails more fossil fuels consumption and more synthetic fertilizers application inducing more Greenhouse Gases (GHGs) emissions that exacerbate climate change. Climate change, on the other hand, has led to adverse effects on the agriculture sector on a global scale despite some minor advantages in higher latitudes. Climate-smart agriculture (CSA), hence, is the only solution to ensure sustainable agriculture productivity and maintain its resilience to climate change consequences. It is a modern approach to responding the climate change by reducing the trade-offs and improving the synergies of agricultural practices. It stands on three main pillars namely, sustainable productivity, resilience-building, and GHGs emissions mitigation using indigenous knowledge and site-specific solutions. Among several practices applied, the Internet of Things (IoT) in agriculture is one of the modern initiatives that can achieve the principal goals of CSA significantly. Therefore, the overall goal of this review paper is to examine the reciprocal effects of climate change and agriculture, discuss the concept of CSA, and ascertain its applicability in Afghanistan.

Economics of strip cropping with autonomous machines

AbstractAutonomous machines have the potential to maintain food production and agroecological farming resilience. However, autonomous complex mixed cropping is proving to be an engineering challenge because of differences in plant height and growth pattern. Strip cropping is technically the simplest mixed cropping system, but widespread use is constrained by higher labor requirements in conventional mechanized farms. Researchers have long hypothesized that autonomous machines (i.e., crop robots) might make strip cropping profitable, thereby allowing farmers to gain additional agroecological benefits. To examine this hypothesis, this study modeled ex‐ante scenarios for the Corn Belt of central Indiana, using the experience of the Hands Free Hectare‐Linear Programming (HFH‐LP) optimization model. Results show that per annum return to operator labor, management, and risk‐taking (ROLMRT) was $568/ha and $163/ha higher for the autonomous corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] strip crop farm compared to the whole field sole crop and the conventional strip crop farms, respectively, that were operated by human drivers. The conventional strip cropping practice was found challenging as this cropping system required four times more temporary hired labor than autonomous strip cropping and three times more than whole field sole cropping. Even if autonomous machines need 100% human supervision, the ROLMRT was higher compared to whole field sole cropping. Profitable autonomous strip cropping could restore and improve in‐field biodiversity and ecosystem services through a sustainable techno‐economic and environmental approach that will address the demand for healthier food and promote environmental sustainability.

Family farming in the Metropolitan Region of Fortaleza (RMF), Ceará

This article aims to deepen the discussion about agricultural activity in metropolitan cities. Our analysis focuses specifically on the Fortaleza Metropolitan Area (FMA), State of Ceará, Brazil, and allows us to further understand family farming in that area. For this purpose, we reviewed a set of primary and secondary data regarding the profile of the producers and agricultural and food processing establishments in the metropolitan area under analysis. This multifaceted approach helped us identify key issues related to production and food systems in the FMA, and showed the importance of a research agenda focused on evaluating the potential of family farming in this specific context. This study presents the production strategies adopted, the challenges faced and the opportunities identified by family farmers. Discussing agriculture in metropolitan areas help us connect socio-spatial and socio-environmental problems, in addition to enabling us to suggest the development of cross-sectoral public policies. By offering a comprehensive overview, this study aims to contribute to effective policy making, promoting the sustainability and resilience of family farming in metropolitan contexts. We hope that the reflection on agriculture developed in such areas and its characteristics in local and metropolitan scenarios will be helpful to researchers, managers and those responsible for the implementation and execution of public policies, as well as other agents and entities interested in family (and urban) agriculture.

Revitalizing agriculture: next-generation genotyping and -omics technologies enabling molecular prediction of resilient traits in the Solanaceae family.

This review highlights -omics research in Solanaceae family, with a particular focus on resilient traits. Extensive research has enriched our understanding of Solanaceae genomics and genetics, with historical varietal development mainly focusing on disease resistance and cultivar improvement but shifting the emphasis towards unveiling resilience mechanisms in genebank-preserved germplasm is nowadays crucial. Collecting such information, might help researchers and breeders developing new experimental design, providing an overview of the state of the art of the most advanced approaches for the identification of the genetic elements laying behind resilience. Building this starting point, we aim at providing a useful tool for tackling the global agricultural resilience goals in these crops.

Natural/Small Water Retention Measures: Their Contribution to Ecosystem-Based Concepts

The increasing incidence of droughts and heavy rainfall events is exacerbating conflicts between human and environmental demands for water. However, through providing multiple water-related ecosystem services and benefits simultaneously, Natural/Small Water Retention Measures (NSWRM) can mitigate such competing claims. Thus, they also contribute to the achievement of various Sustainable Development Goals and environmental targets set out in water- and agriculture-related policies of the European Union. In particular, NSWRM provide for the sound management of watersheds, which can significantly contribute to improved water quality and availability—as well as improving the resilience of agriculture and society. This paper demonstrates how NSWRM fit into the framework of ecosystem-based concepts, including Natural Water Retention Measures (NWRM), Green Infrastructure (GI), Sustainable Land Management (SLM), Ecosystem-based Adaptation (EbA), and Nature-based Solutions (NbS). NSWRM, as a distinct concept, bring added value to the other concepts by focussing on easy-to-implement, modestly sized, localised technical solutions to problems associated with water management, sediment, and nutrient loss. Through experience under the EU Horizon 2020 project OPTAIN (“OPtimal strategies to retAIN and re-use water and nutrients in small agricultural catchments across different soil-climatic regions in Europe”), we show what NSWRM are, how they are linked to each of the ecosystem-based concepts, and how they can help add value to these concepts. Fourteen case studies are drawn upon from diverse countries across Europe. As a result of this analysis, we present the potential for the application of NSWRM in the context of these concepts, while helping to identify planning tools, the expertise required, and potential funding mechanisms.

The Impacts of CAP Subsidies on the Financial Risk and Resilience of Hungarian Farms, 2014–2021

The present paper empirically analyzes the efficiency of European Union (EU) subsidies for farms in the Southern Great Plain region of Hungary between 2014 and 2021. The aim of this analysis was to explore whether the subsidies increased the resilience of farms, enhancing their profitability, liquidity and solvency, and economic efficiency, measured by the usual financial indicators of farm performance. The analysis also evaluated the ability of farm businesses to create and retain jobs, i.e., to increase employment in the rural environment, focusing on differences between the subsidized and non-subsidized farms. The research analyzed all agricultural companies of the selected region. The methodology was a non-parametric statistical analysis (Kruskal–Wallis test, Dunnett’s T3 test) for identifying significant differences between subsidized and non-subsidized farms in the 8-year period. Results show that subsidies significantly improved the financial stability, resilience and efficiency of subsidized farms only in the micro size category, and the employment indicators deteriorated more in subsidized farms than in non-subsidized ones. Thus, the intended purpose of the subsidies was not entirely realized, and positive impacts were noticeable only in the micro enterprises. This might imply that subsidies contributed to the survival of non-viable enterprises instead of enhancing their competitiveness.

Decellularized banana leaves: eco-friendly scaffolds for cell-based seafood

Cellular agriculture holds the potential to address sustainability, food security, and agricultural resilience. Within the cell-based meat supply chain, one of the key steps is developing sustainable scaffolding. In this study, we evaluated the impact of decellularized banana leaves, various coating materials including soy protein and gelatine, and different cell seeding strategies on cell viability, cell growth, cell alignment, and the response of the materials to thermal processing. Kinetics of the quality degradation of the scaffolds with and without cells were determined through kinetics equations. The efficiency of decellularization was verified through DNA quantification, which decreased from 445 ng/mg in fresh banana leaves to non-detectable levels in the decellularized samples. The alignment of cells on gelatin-coated samples was the highest among the samples, with a dominant orientation of 65.8°, compared to soy-coated and uncoated samples, with dominant orientations of 9.2° and −6.3°, respectively. The kinetics of shrinkage indicated that coating with soy and the presence of cells increased the activation energy due to the higher energy required for protein denaturation. The kinetics of area changes in plain scaffolds without cells followed a first-order pattern, while with seeded cells a second-order pattern was followed. Overall, the results showed that decellularized banana leaves provide sustainable scaffoldings for cellular agriculture applications. In addition, soy coating provided many benefits for decellularized samples by supporting cell adhesion and cell proliferation.

Exploring the potential of silymarin in agriculture: A review

Silymarin, a bioactive compound derived primarily from the seeds and fruit of the milk thistle (Silybum marianum) plant, has garnered increasing attention in recent years due to its potential applications in agriculture. This comprehensive review explores the multifaceted role of silymarin in agricultural practices, shedding light on its chemistry, biological activities, and diverse applications. The chemical structure and properties of silymarin are elucidated, emphasizing its unique solubility, stability, and bioavailability, which render it suitable for agricultural use. A significant portion of the review is dedicated to examining the biological activities of silymarin, which encompasses its antioxidant properties. The underlying mechanisms responsible for these activities are explored, highlighting their potential as a natural solution for mitigating environmental stressors that adversely affect crop health and productivity. Illustrative examples from research studies and practical applications underscore its effectiveness in safeguarding agricultural yields and ensuring food security. Furthermore, the review delves into the potential of silymarin to enhance crop growth, yield, and quality. Mechanisms through which silymarin influences plant physiology and metabolism are examined, providing valuable insights into its role as a growth-promoting agent in agriculture. The review concludes with a forward-looking examination of the prospects of silymarin in agriculture, highlighting emerging trends and areas of innovation that hold promise for sustainable and resilient farming systems. In summary, this review consolidates the current body of knowledge surrounding silymarin’s potential in agriculture. It underscores the versatility of silymarin as a natural tool for crop protection, growth enhancement, and environmental sustainability, offering valuable insights for researchers, practitioners, and policymakers seeking innovative approaches to address the challenges of modern agriculture.

Average Rainfall and Water Requirements of Bundelkhand Region: Causes, Consequences, and Solutions

Abstract: The Bundelkhand region, receiving an annual rainfall of approximately 1000 mm, with nearly 90% occurring during the short span of July and August, is traversed by major rivers. However, this region grapples with a severe water crisis exacerbated by factors such as burgeoning agriculture, population growth, unpredictable rainfall patterns, the impact of climate change, political complexities, water mismanagement, misuse, and environmental negligence, including the neglect of traditional water sources. This abstract provides an overview of a comprehensive study on the shifting water table dynamics within the Bundelkhand region. It explores the multifaceted factors contributing to the alteration of groundwater levels, examines the far-reaching repercussions of these changes on the environment and livelihoods, and proposes sustainable solutions to mitigate the looming water crisis. Through a synthesis of scientific research and on-ground observations, this study sheds light on the intricate web of natural and anthropogenic drivers responsible for the declining water table. Furthermore, it underscores the urgent need for collective action and policy interventions to safeguard water resources, ensure agricultural resilience, and improve the quality of life for the people of Bundelkhand.

The Impact and Mechanism of Digital Villages on Agricultural Resilience in Ecologically Fragile Ethnic Areas: Evidence from China’s Provinces

Ecologically fragile ethnic areas constitute pivotal regions for rural revitalization and the construction of the Beautiful China initiative. The establishment of digital villages is of great significance for enhancing agricultural resilience and achieving common prosperity. Utilizing panel data from ecologically fragile ethnic areas between 2010 and 2020, this study employs a projection pursuit model to calculate scores for digital village levels and agricultural resilience. Building on this, our research employs instrumental variable methods and a mediation effect model to analyze the impact and mechanisms of digital village level on agricultural resilience in ecologically fragile ethnic areas, and heterogeneity analysis is conducted. The findings reveal that digital village level and agricultural resilience scores in ecologically fragile ethnic areas show a trend of initial increase followed by a decrease, exhibiting significant overall fluctuations and unstable growth. The promotion of digital village areas on agricultural resilience is evident, and this conclusion holds even after a series of tests including instrumental variables. Elevating the digital village level can narrow the urban–rural income gap and enhance agricultural resilience. There is significant regional heterogeneity in the impact of digital village levels on local agricultural resilience in ecologically fragile ethnic areas, with digital village development exerting a more pronounced and powerful driving force in areas with lower agricultural resilience. Therefore, leveraging the leadership of advantaged provinces, intensifying investment in digital village infrastructure, and implementing targeted strategies based on the disparities in digital village level and agricultural resilience across areas become imperative.

Modelling the Temperature Inside a Greenhouse Tunnel

Climate-change-induced unpredictable weather patterns are adversely affecting global agricultural productivity, posing a significant threat to sustainability and food security, particularly in developing regions. Wealthier nations can invest substantially in measures to mitigate climate change’s impact on food production, but economically disadvantaged countries face challenges due to limited resources and heightened susceptibility to climate change. To enhance climate resilience in agriculture, technological solutions such as the Internet of Things (IoT) are being explored. This paper introduces a digital twin as a technological solution for monitoring and controlling temperatures in a greenhouse tunnel situated in Stellenbosch, South Africa. The study incorporates an aeroponics trial within the tunnel, analysing temperature variations caused by the fan and wet wall temperature regulatory systems. The research develops an analytical model and employs a support vector regression algorithm as an empirical model, successfully achieving accurate predictions. The analytical model demonstrated a root mean square error (RMSE) of 2.93 °C and an R2 value of 0.8, while the empirical model outperformed it with an RMSE of 1.76 °C and an R2 value of 0.9 for a one-hour-ahead simulation. Potential applications and future work using these modelling techniques are then discussed.

Pembuatan Pestisida Nabati Daun Mimba Untuk Mengendalikan Hama Pada Tanaman Di Desa Rumpet Kecamatan Krueng Barona Jaya Kabupaten Aceh Besar

This activities aim to provide understanding and skills to the community in Rumpet Village, Krueng Barona Jaya Subdistrict, Aceh Besar Regency, on utilizing local resources to naturally control plant pests. The primary focus of this activity is the process of making botanical pesticides from neem leaves as an environmentally friendly solution to sustain agriculture in the region. The activity begins with a socialization on the importance of sustainable pest control and the adverse effects of chemical pesticides. It involves active participation from the community in collecting and identifying neem leaves as the main ingredient. The process of extracting active compounds from neem leaves is also taught to the community, along with formulation techniques and the application of the resulting botanical pesticide. The outcomes of this activity include an increase in community knowledge about natural plant pest control and their empowerment in producing and using botanical pesticides from neem leaves. This community service is expected to make a positive contribution in promoting sustainable and resilient farming practices in Rumpet Village, inspiring surrounding communities to adopt similar approaches in their agricultural management.

Should we consider integrated crop–livestock systems for ecosystem services, carbon sequestration, and agricultural resilience to climate change?

AbstractContemporary agricultural systems can be generalized as highly specialized operations that are fueled by mechanization; supplied with external nutrients to maximize production; crops protected by petrochemicals to fight against weed, disease, and insect pressures; and livestock protected by therapeutics to ward off virus and bacterial infections when managed in confinement. Such specialized systems have led to low levels of diversity, elevated environmental risks from contamination, loss of soil organic matter, ecological instability, and limited adaptability to climate change. More diversified farming systems are possible, but research required to characterize them in a holistic manner as an alternative to contemporary, specialized systems remains challenging to fund and sustain over time, primarily because they require more labor, management skills, and accessible markets to achieve additional ecological, environmental, and social goals. We share some perspectives as to (1) how specialized systems became the norm and (2) what changes could be made to reverse some ecological risks and environmental declines associated with specialization, acknowledging there is no panacea. Strong evidence exists for perennial forages to restore soil organic carbon (C) and nitrogen, but system‐level analyses of the net balance in greenhouse gas emissions remain to be characterized in the myriad of potential integrated crop–livestock systems that might be deployed across the diversity of edaphic, environmental, and socio‐economic conditions. We suggest there are abundant opportunities for more sustainable agricultural production to sequester soil organic C, reduce greenhouse gas emissions, and develop more climate‐resilient agricultural systems that will be needed in a future dominated by climate change issues.

Climatic Shifts and Agricultural Strategies: A thorough Review on Impact of Climate Change on Food Security and Crop Productivity

This comprehensive review delves into the intricate change of climate, assessing its profound impact on global food security and crop productivity. The examination addresses key questions, exploring the consequences of climate change on agriculture, with a specific focus on the challenges encountered in vulnerable regions such as sub-Saharan Africa and South Asia. Emphasizing the urgency of adaptive strategies for sustainable global agriculture, the review navigates through the complexities of mitigating climate-induced disruptions in crop growth patterns. Furthermore, it scrutinizes the implications of climate change on biodiversity, acknowledging the interconnectedness of ecological systems. Highlighting the imperative for innovation, the review underscores the pressing need for transformative farming methods to effectively tackle the multifaceted challenges posed by climate change. The emphasis is on ensuring the resilience of global agriculture in the face of climatic shifts. In conclusion, the review provides a compelling call to action, advocating for the prompt implementation of innovative farming practices to fortify the global agricultural sector against the evolving challenges brought about by climate change, fostering sustainability and adaptability.

Perceptions of climate change-related disasters and impact on household food security in rural farm households in Imo State, Nigeria

This study investigates the perception of climate change-related disasters and their impact on household food security in rural farm households in Imo State, Nigeria. Studies have consistently shown an association between climate change and food insecurity in different parts of the world. However the impact of climate change varies over time and space and therefore cannot be generalized. If household food security is to be secured in Imo State, it becomes imperative to identify the specific climate change related disasters that adversely affect household food security as well as the intervention priorities in specific communities. The study utilizes descriptive analytical tools to analyze the data from 186 farm households across four agricultural communities in the state. Findings reveal that excessive rainfall leading to flooding is the most prevalent climate change-related disaster, followed by excessive heat and irregular rainfall patterns. A significant majority of respondents attribute household food insecurity to these climate change-related disasters at high or very high levels. Various mitigation strategies adopted by households include changes in farming practices, irrigation methods, crop replacement, and land modification techniques. The study also identifies top priorities for government intervention as improving drainage and irrigation systems, establishing community weather forecast centers, and providing fertilizer subsidies. Additionally, enhancing hedging technology and pest/disease control strategies were recognized as important interventions. The study emphasizes the importance of tailored interventions, continuous data collection, and awareness campaigns to enhance agricultural resilience and ensure food security in the face of climate change impacts.