Resilience Of Agricultural Systems Research Articles

Motivating factors of farmers’ adaptation behaviors to climate change in China: A meta-analysis

Adapting to climate change is critical to building sustainable and resilient agricultural systems. Understanding farmers' perceptions of climate change has become the key to the effective implementation of climate change adaptation policies. This research draws multidisciplinary attention to how farmers participate in decision-making on adaptation behaviors and provides useful insights for realizing synergies between environmental change and agricultural production. In this work, we conducted a meta-analysis of 63 quantitative studies on Chinese farmers' adaptation to climate change to assess the relationship between motivational factors and adaptation behavior. Our analysis highlights that farmers' perceptions of precipitation changes are often inaccurate; however, other psychological factors, such as perception, experience, and risk attitude, significantly positively impact their adaptation behavior. In addition, different climate regions are the main source of high heterogeneity in inter-study comparisons of climate change perception, and the effect of climate regions may therefore constitute a moderating factor that weakens the positive relationship between climate change perception and adaptive behavior. Furthermore, this study highlights the need to intervene at the household level to enhance farmers' adaptability to climate change, which includes providing support through income diversification, early warning information services, training, assistance, credit, subsidies, and other resources. In the future, research on how perception, experience, and risk interact to affect adaptive behavior should be strengthened.

Imitating the “breeder's eye”: Predicting grain yield from measurements of non‐yield traits

AbstractPlant breeding relies on information gathered from field trials to select promising new crop varieties for release to farmers and to develop genomic prediction models that can enhance the efficiency of genetic improvement in future breeding cycles. However, generating the genetic marker data required to apply genomic prediction at the early stages of a breeding program remains costly for many public‐sector breeding programs as well as for many plant breeders operating in developing countries. As the pace of climate change intensifies, the time lag of developing and deploying new crop varieties requires plant breeders to make selection decisions without knowing the future environments those crop varieties will encounter in farmers’ fields. Therefore, both lower cost and higher accuracy methods for prediction of crop performance are essential for creating and maintaining resilient agricultural systems in the latter half of the 21st century. To address this challenge, we conducted linked yield trials of 752 public maize (Zea mays) genotypes in two distinct environments. We developed and trained a phenotypic prediction model to predict yield from manually scored plant traits. The phenotypic prediction approach we employed outperformed genomic prediction in predicting yields in a second environment, with 8.7%–63% higher R2 and 4%–13% less root mean square error than the genomic prediction. The phenotypic prediction has the potential to be applied to a wider range of breeding programs, including those that lack the resources to genotype large populations, such as programs in the developing world, breeding programs for specialty crops, and public sector programs.

The Influence of Trees on Crop Yields in Temperate Zone Alley Cropping Systems: A Review

Agroforestry is a multifunctional land use system that represents a promising approach to mitigate the environmental impact of agriculture while enhancing the resilience of agricultural systems and ensuring sustainable food production. However, the tree rows in agroforestry systems, particularly in alley cropping systems (ACS), can affect crop productivity on adjacent agricultural fields through various mechanisms. Hence, concerns about declining yields and reduced farm profitability persist and explain the reluctance of farmers to implement ACS on their land. In this review, we examine the available literature on the effects of temperate ACS on yields of various agricultural crops to evaluate if and to what extent crop yields in ACS are affected by tree presence. We identified that ACS crop yields often vary substantially across different species, geographical locations, weather conditions and ACS designs. Our analysis also revealed that several parameters are modified in ACS by the presence of tree rows affecting crop yields positively or negatively and that ACS design aspects play a crucial role in determining crop productivity.

Mapping the race between crop phenology and climate risks for wheat in France under climate change.

Climate change threatens food security by affecting the productivity of major cereal crops. To date, agroclimatic risk projections through indicators have focused on expected hazards exposure during the crop's current vulnerable seasons, without considering the non-stationarity of their phenology under evolving climatic conditions. We propose a new method for spatially classifying agroclimatic risks for wheat, combining high-resolution climatic data with a wheat's phenological model. The method is implemented for French wheat involving three GCM-RCM model pairs and two emission scenarios. We found that the precocity of phenological stages allows wheat to avoid periods of water deficit in the near future. Nevertheless, in the coming decades the emergence of heat stress and increasing water deficit will deteriorate wheat cultivation over the French territory. Projections show the appearance of combined risks of heat and water deficit up to 4years per decade under the RCP 8.5 scenario. The proposed method provides a deep level of information that enables regional adaptation strategies: the nature of the risk, its temporal and spatial occurrence, and its potential combination with other risks. It's a first step towards identifying potential sites for breeding crop varieties to increase the resilience of agricultural systems.

Research priorities to leverage smart digital technologies for sustainable crop production

Agriculture faces several challenges including climate change and biodiversity loss while, at the same time, the demand for food, feed, biofuels, and fiber is increasing. Sustainable intensification aims to increase productivity and input-use efficiency while enhancing the resilience of agricultural systems to adverse environmental conditions through improved management and technology. Recent advances in sensing, machine learning, modeling, and robotics offer opportunities for novel smart digital technologies to enable sustainable intensification. However, developing smart digital technologies and putting them into agricultural practice, requires closing major research gaps, related in particular to (1) the utilization of multi-scale multi-sensor monitoring in space and time, (2) using artificial intelligence for linking process and data-driven methods, (3) improving decision making and intervention in plant production, and finally (4) modeling conditions and consequences of farmers acceptance. Closing these gaps requires an interdisciplinary approach. Here, we present a research agenda and steps forward to steer research efforts, highlighting research priorities, and identifying required interdisciplinary research collaboration. Following this agenda will leverage the full potential of smart digital technologies for sustainable crop production.

IoT Based Crop Prediction using Machine Learning

To enhance agricultural productivity and resource allocation. Leveraging historical data encompassing various agricultural factors such as soil composition, weather conditions, and crop types, a predictive model is developed to forecast crop yields. Machine learning techniques, including regression and classification algorithms, are employed to analyze the intricate relationships within the dataset and predict the most likely outcomes for specific crops in different regions. The model is trained on a diverse dataset, considering variations in climate and soil characteristics, ensuring robustness and adaptability across different agricultural environments . The proposed crop prediction system not only provides accurate yield forecasts but also assists farmers in making informed decisions regarding crop selection and resource optimization. By harnessing the power of machine learning, this research contributes to sustainable agriculture by promoting precision farming practices. The integration of technology in crop prediction not only improves yield predictions but also supports the overall resilience of agricultural systems, fostering a data-driven approach that aligns with the evolving needs of the agricultural sector in a rapidly changing world.

A framework for improved predictions of the climate impacts on potential yields of UK winter wheat and its applicability to other UK crops

Changes in the frequency of extreme weather events related to climate change potentially pose significant challenges to UK agricultural production. There is a need for improved climate change risk assessments to support adaptation strategies and to ensure security of food production in future.We describe an innovative and practical framework for spatially explicit modelling of climate change impacts on crop yields, based on the UKCP18 climate projections. Our approach allows the integration of relatively simple crop growth models with high spatial and temporal resolution Earth Observation datasets, describing changes in crop growth parameters within year and over the longer term. We focus on modelling winter wheat, a commercially important crop. We evaluate the results of the model against precision yield data collected from 719 fields. We show that the assimilation of leaf area index data from Sentinel-2 satellite observations improves the agreement of the modelled yields with those observed. Our national-scale results indicate that wheat production initially becomes more favourable under climate change across much of the UK with the projected increase in temperature. From 2050 onwards, yields increase northwards, whilst they decline in South East England as the decrease in precipitation offsets the benefits of rising temperature.Our framework can readily accommodate growth models for other crops and LAI retrievals from other satellite sensors. The ability to explore impacts of crop yields at fine spatial resolutions is an important part of assessing the potential risks of climate change to UK agriculture and of designing more climate resilient agricultural systems.

High environmental quality label proposal

Our idea aims to evolve agricultural models and face the growing challenge of resilience of agricultural systems. We offer a high environmental quality label that encourages farmers in developing countries to optimize inputs. It will encourage them to reduce the consumption of pesticides, fertilizers and irrigation water. At present, many decision support tools are widely used in modern agriculture, notably soil tensiometers to control irrigation, the nitrogen balance in the management of fertilization and the I-PHY indicator of pesticide use in the field of plant protection. The use of these three tools is inexpensive and technically affordable by farmers. We offer a framework based on these decision-making tools and agricultural techniques which will allow farmers to have a High Environmental Quality Label.

From Field to Feed trough: Examining the Drivers of Feed and Fodder Technologies Uptake among Pastoral Beef Farmers in Kenya

Adoption of technologies and effective management practices in the pastoral beef systems are necessary for improved productivity and resilient agricultural systems. This study examined the factors influencing the adoption of Technology Innovations and Management Practices (TIMPs) among pastoral beef farmers in Isiolo and Kajiado counties. Employing a cross-sectional approach and utilizing the Seemingly Unrelated Regression (SURe) model, the research explores the intricate dynamics that shape farmers' decisions regarding three key TIMPs; planted fodder, feed supplementation, and fodder conservation. Using a systematic sampling technique, a sample size of 619 pastoral farmers was adopted. This research seeks to uncover the underlying motivations and barriers, understanding the complex relationships between resource accessibility, socio-economic considerations, and the role of extension services in facilitating technology adoption. The research underscores the importance of addressing specific barriers, including limited access to resources and socio-economic constraints faced by these farmers. The evidence-based strategies derived from this research paves the way for scientifically informed interventions to propel the livestock sector in Kenya towards a sustainable future. The study's recommendations emphasize the need for targeted policies that prioritize market accessibility, technology awareness and information access, thus effectively supporting the adoption of TIMPs among pastoral beef farmers. Implementing these recommendations contributes to strengthening of resilience of the livestock sector and the advancement of sustainable agricultural practices in Kenya.

Nano-elicitation and hydroponics: a synergism to enhance plant productivity and secondary metabolism.

This review has explored the importance of using a synergistic approach of nano-elicitation and hydroponics to improve plant growth and metabolite production. Furthermore, it emphasizes the significance of green nanotechnology and eco-friendly practices while utilizing this approach to promote the development of a sustainable agriculture system. Nano-elicitation stimulates metabolic processes in plants using nanoparticles (NPs) as elicitors. The stimulation of these biochemical processes can enhance plant yield and productivity, along with the production of secondary metabolites. Nanoparticles have garnered the attention of scientific community because of their unique characteristics, such as incredibly small size and large surface-to-volume ratio, which make them effective elicitors. Hydroponic systems, which optimize growing conditions to increase plant production, are typically used to study the effect of elicitors. By integrating these two approaches, the qualitative and quantitative output of plants can be increased while employing minimal resources. As the global demand for high-quality crops and bioactive compounds surges, embracing this synergistic approach alongside sustainable farming practices can pave the way for resilient agricultural systems, ensuring food security and fostering an eco-friendly environment.

Seed Priming: A Strategy to Mitigate Flooding Stress in Pulses

Aim: This study delves into the multifaceted role of seed priming in mitigating flooding stress, with a specific focus on its applications in pulse crops.
 Area of Study: Through controlled hydration-dehydration cycles and the utilization of specific priming agents, seed priming emerges as a powerful tool to enhance germination seedling vigor and stress tolerance. The impact of flooding stress on pulse plants, encompassing morphological changes, physiological alterations, and yield reduction, underscores the urgency of developing effective mitigation strategies. Seed priming mechanisms, including enhanced nutrient uptake, activation of antioxidant defenses and hormonal modulation, are explored in detail. The study not only provides insights into the integration of seed priming into crop management practices but also offers practical recommendations for farmers and agricultural practitioners. The implications for agriculture and food security are significant, as seed-primed crops demonstrate increased resilience to environmental stresses, ensuring more stable yields. The economic implications for farmers, coupled with the potential for sustainable agricultural practices, highlight the transformative potential of seed priming in addressing global challenges.
 Conclusion: The dissemination of knowledge and implementation efforts are crucial for bridging the gap between research findings and on-field applications. Policymakers and stakeholders are urged to support and incentivize the adoption of seed priming technologies, contributing to the long-term resilience of crops, and ensuring global food security. In conclusion, seed priming stands as a promising solution, offering a pathway towards sustainable and resilient agricultural systems in the face of environmental challenges.

Forecasting agricultures security indices: Evidence from transformers method

AbstractIn recent years, ensuring food security has become a global concern, necessitating accurate forecasting of agriculture security to aid in policymaking and resource allocation. This article proposes the utilization of transformers, a powerful deep learning technique, for predicting the Agriculture Security Index ( ). The is a comprehensive metric that evaluates the stability and resilience of agricultural systems. By harnessing the temporal dependencies and complex patterns present in historical data, transformers offer a promising approach for accurate and reliable forecasting. The transformer architecture, renowned for its ability to capture long‐range dependencies, is tailored to suit the forecasting task. The model is trained using a combination of supervised learning and attention mechanisms to identify salient features and capture intricate relationships within the data. To evaluate the performance of the proposed method, various evaluation metrics, including mean absolute error, root mean square error, and coefficient of determination, are employed to assess the accuracy, robustness, and generalizability of the transformer‐based forecasting approach. The results obtained demonstrate the efficacy of transformers in forecasting the , outperforming traditional time series forecasting methods. The transformer model showcases its ability to capture both short‐term fluctuations and long‐term trends in the , allowing policymakers and stakeholders to make informed decisions. Additionally, the study identifies key factors that significantly influence agriculture security, providing valuable insights for proactive intervention and resource allocation.

Assessing the Economic Viability of Climate-Resilient Crop Varieties for Smallholder Farmers in Sub-Saharan Africa

The adoption of climate-resilient crop varieties holds immense promise as a strategy to enhance the resilience of agricultural systems in the face of changing climatic conditions. This research delves into the intricate dynamics of farmer decision-making, socioeconomic impacts, and the interplay of policy and market contexts in the context of adopting climate-resilient crop varieties. Through a comprehensive analysis, this study unveils the multifaceted factors that influence farmers' choices, ranging from economic considerations and risk perceptions to access to resources and market dynamics. The socioeconomic impacts resulting from the adoption of climate-resilient crop varieties transcend conventional productivity gains. Improved incomes, heightened food security, resilience to climate shocks, reduced environmental pressures, gender empowerment, and expanded market opportunities collectively contribute to a more holistic and sustainable agricultural landscape. Furthermore, the research underscores the inseparable relationship between effective policy frameworks and responsive market dynamics. Policies that promote research and development, support extension services, and provide incentives are aligned with market demand, enhancing the potential for successful adoption. The findings of this research have far-reaching implications for policy development, agricultural extension services, and development programs aimed at fostering climate resilience. By recognizing the diverse motivations and constraints that farmers face, policymakers and practitioners can tailor interventions that resonate with local realities. The integration of climate adaptation and resilience strategies into national policies and alignment with broader climate agendas is underscored as a crucial pathway toward sustainable agriculture.

Ethnoecology and Climate Change Adaptation in Agriculture

Ethnoecology, the study of how different cultures perceive and interact with their environments, plays a critical role in understanding climate change adaptation in agriculture. This article explores the relationship between ethnoecology and climate change adaptation strategies employed in agricultural practices. Utilizing a qualitative approach, this study conducts an extensive review of literature and library research to examine the intersection of ethnoecology and climate change adaptation in agricultural contexts. Through the synthesis of existing literature, the article identifies various indigenous knowledge systems, traditional agricultural practices, and local adaptations that communities have developed over generations to cope with changing climatic conditions. Additionally, the study analyzes the effectiveness and limitations of ethnoecological approaches in enhancing agricultural resilience to climate change impacts. Furthermore, the article discusses the importance of integrating indigenous knowledge with scientific research and modern technologies to develop holistic and context-specific adaptation strategies. The findings underscore the significance of ethnoecology as a valuable source of knowledge for informing climate change adaptation policies and practices in agriculture. By recognizing and incorporating traditional ecological knowledge into adaptation initiatives, stakeholders can enhance the resilience of agricultural systems and promote sustainable livelihoods for communities vulnerable to climate change. This study contributes to advancing understanding of the role of ethnoecology in climate change adaptation and underscores the importance of interdisciplinary approaches in addressing complex environmental challenges.

Renewable energy consumption and its impacts on agriculturalization under climate neutrality targets

Improvements in energy efficiency, cost savings, and environmental advantages are possible effects of adopting and using renewable energy in agriculture. However, whether renewable energy consumption (REC) has any impact on agricultural productivity is a research question that this analysis tries to answer. Previous research neglected to consider the influence of REC on agriculture. The primary objective of the analysis is to analyze the role of REC in sustainable agriculture in Asia, America, Africa, and Europe with the help latest econometric technique of the CS-ARDL model. The findings show that REC and technological capital (TC) improve long-run agriculturalization in the full sample, Asia, Africa, America, and Europe. The results infer that a 1% increase in REC causes agriculturalization to boost by 1.512% in the full sample, 1.254% in Asia, 1.654% in Africa, 0.897% in America, and 1.325% in Europe. In addition, financial development favorably influences long-run agricultural productivity in the full sample, Africa, America, and Europe, and population growth only impacts agricultural productivity in the long run. In contrast, the long-run agricultural productivity is negatively impacted by environmental pollution globally and in Asia. On the other hand, in the short run, TC positively impacts agricultural productivity in all samples, while other short-run estimates are insignificant in most samples. These findings suggest that renewable energy utilization may lead to more effective and resilient agricultural systems by supplying clean and dependable electricity, lowering greenhouse gas emissions, and supporting sustainable resource management.

The role of microorganisms in sustainable agriculture: a review

Sustainable agriculture is an agricultural production system that seeks to balance food production with the preservation of natural resources, minimizing environmental impacts, and promoting soil health. Microorganisms play a crucial role in agriculture, directly influencing soil quality, plant nutrition, and, therefore, agricultural productivity. This complex interaction between microorganisms and agricultural systems is an ever-expanding area of research. The presence of beneficial microorganisms contributes to the formation of soil aggregates, improving its structure and aeration. This favors root development and the efficient absorption of nutrients by plants. In summary, microorganisms play a vital role in promoting sustainable agriculture, contributing to the efficiency of resource use, reducing dependence on chemical inputs, and preserving the health of the agricultural ecosystem. Therefore, integrating practices that promote microbial activity in the soil is essential for the development of more sustainable and resilient agricultural systems.

Assessing the Role of Green Finance in Enhancing Rural Economic Resilience and Environmental Sustainability

Green finance plays a key role in enhancing the resilience of rural economies and environmental sustainability. Rural economies have traditionally relied on natural resources, which makes them particularly vulnerable to climate change and environmental degradation. By providing the necessary financial support, green finance can help rural areas invest in sustainable agricultural practices, upgrade aging infrastructure, implement resource conservation projects, and adopt clean energy and energy-efficient technologies. Green finance can facilitate shifts in agricultural practices, such as supporting organic farming, precision farming and conservation tillage. These practices help to increase land productivity, reduce the use of chemical fertilizers and pesticides, and conserve biodiversity, while increasing the resilience of agricultural systems to climate change. Green finance supports the sustainable transformation of rural infrastructure, such as the efficiency improvement of irrigation systems, the recycling of agricultural waste and the green transformation of rural energy, which helps to reduce environmental pollution and improve resource efficiency. The development of green finance also requires the support of relevant policies, including the establishment of a sound green financial system, the improvement of financial institutions’ awareness and assessment capacity of green projects, policy tools to incentivize green investment and credit, and the enhancement of rural communities’ awareness and acceptance of green finance.

Assessment by bioeconomic modeling water price scenarios of the resilience of agricultural production systems in a semi-arid region: Case of Baalbeck El Hermel – Lebanon

Baalbeck El Hermel Governorate, particularly the semi-arid region is increasingly threatened by climate change. These disturbances, more specifically, concerning the limit in water resources generate problems for the agricultural systems constituting the principle source of families’ subsistence in this zone. This study was established to evaluate, via a bioeconomic modeling approach, the resilience of agricultural systems in Baalbeck El Hermel and perceive their adaptation techniques under conditions of water scarcity. In this context, we have selected three typical farms representative of the driest northern zone receiving the least precipitation.
 Several behaviors and levels of resilience of these farms were showed after analysis of the results: 1) farms specializing in market gardening or perennial crops are very sensitive to drought conditions and are not resilient in the face of water limit conditions; 2) the diversified farm with olive tree dominance is less sensitive and more resilient. The analysis of the water pricing scenario showed an improvement in water management but a limit in the adaptive capacity of farmers, hence the necessity to adapt resilience-building strategies for the targeted zone.

Irrigation Scheduling and Cultivar Management for Increasing Water Productivity under Dryland Condition: A Review

In Dryland environments with limited water resources, irrigation scheduling and cultivar management are play pivotal roles in enhancing water productivity. Effective irrigation scheduling involves the judicious timing and amount of water application, considering factors such as soil moisture levels and crop growth stages. Utilizing advanced technologies, such as soil moisture sensors and remote sensing, facilitates precise irrigation management. This approach not only conserves water but also prevents waterlogging and salinity issues, promoting optimal plant growth. Cultivar selection is another critical aspect, focusing on identifying and cultivating crops that are well-adapted to arid conditions. Drought-resistant cultivars with traits like deep root systems and efficient water use contribute significantly to water productivity. Integrating modern breeding techniques and genetic engineering enhances the development of cultivars with improved drought tolerance, ensuring resilience in dryland agriculture. Furthermore, the implementation of agro ecological practices, such as conservation tillage and organic farming, complements irrigation scheduling and cultivar management. These practices enhance soil structure, water retention, and overall ecosystem health, fostering a more sustainable and resilient agricultural system. Adopting a comprehensive approach that combines precise irrigation scheduling, resilient cultivar selection and agro ecological practices holds great potential for increasing water productivity in dryland conditions. This integrated strategy not only addresses the challenges posed by water scarcity but also contributes to the long-term viability of agriculture in arid regions.

Assessing the Influence of Climate Change on Agricultural Yields and Crafting Farmer-Centric Adaptation Strategies: A Policy-oriented Agricultural Analysis

This journal article critically examines the influence of climate change on agricultural yields and proposes farmer-centric adaptation strategies through a policy-oriented agricultural analysis. The research employs a comprehensive approach, integrating climate science, agricultural economics, and policy studies to assess the multifaceted impacts of climate change on global agricultural productivity.
 The study analyzes empirical data on changing climate patterns, extreme weather events, and temperature variations, emphasizing their significant consequences for agricultural yields. By utilizing statistical models and econometric techniques, the research quantifies the extent of yield variations across diverse crops, providing a nuanced understanding of the challenges faced by farmers.
 In response to these challenges, the research proposes adaptation strategies centered on the needs and capacities of farmers. These strategies encompass the development and dissemination of climate-resilient crop varieties, the enhancement of irrigation infrastructure, and the implementation of precision agriculture techniques. Moreover, the study investigates the role of agricultural policies in promoting adaptive practices and explores potential policy frameworks to incentivize climate-smart agriculture.
 The findings highlight the importance of tailoring adaptation strategies to local contexts and engaging farmers in the decision-making process. The research underscores the need for policies that empower farmers, providing them with the knowledge, resources, and incentives to adapt to changing climatic conditions effectively.
 In conclusion, this article contributes to the discourse on climate change adaptation in agriculture by offering a policy-oriented perspective. It advocates for a holistic approach that integrates scientific insights, economic considerations, and farmer participation, aiming to enhance the resilience of agricultural systems in the face of climate change.