Food Security Management Research Articles

Earthworms as Catalysts for Climate-Resilient Agriculture: Enhancing Food Security and Water Management in the Face of Climate Change

Earthworms as Catalysts for Climate-Resilient Agriculture: Enhancing Food Security and Water Management in the Face of Climate Change

Digital mapping of dates of transplanting and accumulated thermal requirement of rice (Oryza sativa L.) in the subtropics of North Eastern Hill Region, India

ABSTRACT Accurate and timely mapping of rice areas is crucial for effective agricultural planning and food security management in the North Eastern Hill Region of India, especially amid changing climate conditions. This study developed a method to estimate rice transplanting dates by utilizing VH polarized backscattering-coefficients rom Sentinel-1A SAR data and also assessed thermal requirements for rice productivity in Ri-Bhoi district, Meghalaya during kharif 2021. The methodology involved 3 steps- (i) preprocessing data to construct time-series SAR images (ii) rule-based classification of SAR data integrating phenological and topographical information to identify transplanting windows (iii) assessing mapping accuracy. The results when compared with field data, revealed five distinct transplanting windows from early June to early August across 9031 ha of rice area. Overall accuracy was 85%, with a kappa coefficient of 0.74. User and producer accuracies ranged from 0.74 to 0.93 and 0.75 to 0.92, respectively for various transplanting windows. GDD varied between 1432.8°C day and 3290.4°C day, with higher values corresponding to earlier planting dates. This study formulates a robust methodology for rice mapping in hilly, small-field landscapes with multiple transplanting dates by integrating Sentinel-1A SAR data with ancillary and crop phenology information, contributing to improved crop management and climate change adaptations.

Fisheries management for food security in the Maldives

Purpose. The goal of the study was to assess trends in providing food security with a special emphasis on efficiency of the local fisheries and offer evidence-based improvements, which can improve resource management and protect disadvantaged population in the Maldives from nutrition insecurity aggravated by strong import dependency. Methodology / approach. The methodological basis of this study was a set of modern qualitative economic and quantitative mathematical methods including factor analyses, econometric and optimisation modelling. This approach ensured holistic research and reasonable recommendations on providing food security and maintaining efficient fisheries management compared to international experience and intrinsic aspects that determine a fish catch and consumption in the Maldives. Results. The conclusions of the paper relate to the further development of fisheries to combat the identified negative trends in domestic fish consumption and an unstable fish catch by atoll in the Maldives. The conducted factor analysis detected relationships between a fish catch, fishing trips, engaged vessels, fish species, and fishing methods. The study findings proved the optimal locations where it is advisable to establish additional fish storages and ice plants taking into account indicators of a poverty rate, a share of children, and a population density. The research conclusions allow the authors to state that the outlined scientific proposals can essentially improve food security in the Maldives, which is threatened by land shortage and overpopulation. Originality / scientific novelty. The scientific novelty of the work is in presenting a clarified picture of challenges that Maldivian fishermen face nowadays. The scientific novelty lies in the identification of weaknesses in fisheries management and the proposals of areas of potential growth that are crucial for ensuring food security not only on poor islands but for the whole country. Practical value / implications. The main practical value of the research results is the development of recommendations for increasing fish catch and organising post-harvest processing, which are vital for the Maldivian fishery, as it is the country's main export sector. In addition, the study contributes to food security in the Maldives through proposed interventions aimed at supporting the most disadvantaged populations in the scattered atolls.

Community perception of watershed management as a strategy for food security improvement: Case study of Qersa District, Ethiopia

The importance of community-based watershed management for food security and rural development is increasingly recognized. However, the comprehensive nature of the strategy is not well understood. The study examined the perspectives of different stakeholders and their level of coordination in implementing the watershed approach. Data was collected from 63 individuals with diverse professional backgrounds at different organizational hierarchies and 337 farmers from three different micro watersheds. The findings of the study showed that professionals and farmers have different views. About 36.0% of professionals and 12.6% of farmers see it as a holistic strategy for rural development, 7.0% of professionals and 40.0% of farmers see it as a way to conserve soil and water, and the rest see it as natural resource management. The chi-square test analysis revealed significant correlations between organizational affiliation, hierarchies, work experience, and field of study among professionals at significance levels of 0.05 and 0.01, with no significant differences observed among farmers in the three micro watersheds. The diverse viewpoints of professionals and farmers highlight the inadequate understanding and lack of consensus among stakeholders regarding watershed management principles, hindering the transformation of this strategy into a comprehensive food security initiative. The study also revealed limited collaboration among various organizations and departments in supporting the management of local watersheds, which can be attributed to the lack of accountability. This highlighted the need for improved collaboration and communication among different groups involved in implementing watershed management plans. The study also identified the need for capacity-building to enhance the knowledge and skills of professionals and farmers involved in watershed management. To effectively use the watershed approach as a holistic strategy to address food security, fostering greater coordination and communication among stakeholders, robust institutional arrangement, education, and awareness-creation initiatives must be strengthened at all levels.

Improved Winter Wheat Yield Estimation by Combining Remote Sensing Data, Machine Learning, and Phenological Metrics

Accurate yield prediction is essential for global food security and effective agricultural management. Traditional empirical statistical models and crop models face significant limitations, including high computational demands and dependency on high-resolution soil and daily weather data, that restrict their scalability across different temporal and spatial scales. Moreover, the lack of sufficient observational data further hinders the broad application of these methods. In this study, building on the SCYM method, we propose an integrated framework that combines crop models and machine learning techniques to optimize crop yield modeling methods and the selection of vegetation indices. We evaluated three commonly used vegetation indices and three widely applied ML techniques. Additionally, we assessed the impact of combining meteorological and phenological variables on yield estimation accuracy. The results indicated that the green chlorophyll vegetation index (GCVI) outperformed the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) in linear models, achieving an R2 of 0.31 and an RMSE of 396 kg/ha. Non-linear ML methods, particularly LightGBM, demonstrated superior performance, with an R2 of 0.42 and RMSE of 365 kg/ha for GCVI. The combination of GCVI with meteorological and phenological data provided the best results, with an R2 of 0.60 and an RMSE of 295 kg/ha. Our proposed framework significantly enhances the accuracy and efficiency of winter wheat yield estimation, supporting more effective agricultural management and policymaking.

Food insecurity versus public health? Social resilience.

The health problems of low-income communities and their relationship to food insecurity are a widespread problem worldwide. Understanding the complex relationship between these two conditions of food insecurity and health outcomes is the focus of this study. In addressing these issues, managing food security and adopting comprehensive strategies that consider the broader public health of the poor and socially vulnerable requires a multi-pronged approach that integrates sustainable food systems, social protection interventions, community engagement, and nutrition-specific interventions. This study is useful for improving our understanding of the relationship between food insecurity and health outcomes, which ultimately contributes to better health and social resilience strategies.

Participatory leadership and supportive organisational culture Panacea for job satisfaction regulatory role of work-life balance

This study examines the direct influence of participatory leadership (PL) and supportive organisational culture (SOC) on employee job satisfaction (JC). Additionally, the research delves into the mediating role of work-life balance in the relationship between PL, SOC, and job satisfaction. Data was collected using 450 questionnaires through random sampling from hotels managing food security in Saudi Arabia. These findings indicate a direct correlation between participatory leadership, supportive organisational culture, and job satisfaction. Furthermore, work-life balance was found to mediate the relationship between PL, SOC, and job satisfaction. Given the importance of a supportive organisational culture for robustness, this study suggests that hotels, particularly those managing food security in Saudi Arabia, should prioritise fostering a supportive culture. They should also encourage democratic leadership and formulate strategies to help employees achieve work-life balance (WLB), leading to enhanced job satisfaction.

Predicting the impact of climate change on crop water footprint using CMIP6 in the Shule River Basin, China

Quantitatively predicting the impacts of climate change on water demands of various crops is essential for developing measures to ensure food security, sustainable agriculture, and water resources management, especially in arid regions. This study explored the water footprints (WFs) of nine major crops in the middle and downstream areas of Shule River Basin, Northwest China, from 1989 to 2020 using the WF theory and CROPWAT model and predicted the future WFs of these crops under four emission and socio-economic pathway (SSPs-RCPs) scenarios, which provides scientific support for actively responding to the negative impacts of climate change in arid regions. Results indicated: (1) an increasing trend of the overall crop WF, with blue WF accounting for 80.31–99.33% of the total WF in the last 30 years. Owing to differences of planting structure, water-conservation technologies, and other factors, the multi-year average WF per unit area of crops was 0.75 × 104 m3 hm−2 in downstream area, which was higher than that in midstream area (0.57 × 104 m3 hm−2) in the last 30 years; therefore agricultural water use efficiency in the downstream area was lower than that in the midstream area, implying that the midstream area has more efficient agricultural water utilization. (2) an initial increase and then decrease of crop WFs in the study area under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios by the end of the century, reaching their peak in 2030s which was higher than that from 1989 to 2020; with the maximum growth rates in the midstream area ranging from −0.85% in SSP5-8.5 to 5.33% in SSP2-4.5 and 29.74% in SSP5-8.5 to 34.71% in SSP2-4.5 in the downstream area. The local agricultural water demand would continue to increase and water scarcity issues would be more severe in the next 10–20 years, affecting downstream areas more. Under the SSP3-7.0 scenario, crop WF values of the midstream and downstream regions will be 2.63 × 108 m3 and 4.22 × 108 m3 in 2030, respectively, which is significantly higher than those of other scenarios and show a long-term growth trend. The growth rate of the midstream and downstream regions will reach 44.71% and 81.12%, respectively, by the end of this century, so the local agricultural water use would be facing more strain if this scenario materializes in the future. Therefore, the Shule River Basin should encourage development of water-saving irrigation technologies, adjust the planting ratio of high water consuming crops, and identify other measures to improve water resource utilization efficiency to cope with future water resource pressures.

Harnessing Technology for Agricultural Sustainability: Case Studies and Future Directions

Agricultural sustainability has become a critical focus in addressing the challenges of food security, climate change, and resource management. This article explores the role of technology in promoting sustainable agricultural practices through detailed case studies and an analysis of future directions. By examining various technological innovations such as precision agriculture, automated irrigation systems, and biotechnology, the study highlights their impact on increasing crop yields, reducing resource use, and minimizing environmental footprints. The case studies from different regions demonstrate successful implementations and the benefits of integrating technology into farming practices. The research also identifies key barriers to adoption, including high initial costs, lack of technical expertise, and the need for supportive policy frameworks. The findings suggest that while technology has the potential to significantly enhance agricultural sustainability, its success largely depends on the collaboration between stakeholders, including farmers, governments, and tech companies. The study concludes with recommendations for future research and policy development to support the widespread adoption of sustainable technologies in agriculture. Emphasizing the importance of continued innovation and education, this article aims to contribute to the ongoing discourse on sustainable agriculture and provide a roadmap for future efforts.

Governmental approaches to food security management: A bibliometric analysis

The government’s duty is to guarantee unimpeded access to food. Thus, relevant public policies, individual methods and tools, approaches, and strategic decisions are always the focus of attention of scientists, politicians, and government officials. Recognizing the critical importance of this imperative, this study aims to conduct a bibliometric analysis that sheds light on the scientific landscape of strategic public administration of food security. The paper conducts a bibliometric analysis of scientific publications (using VosViewer – from 1990 to February 2024 using Scopus and WoS scientometric databases); monographs/textbooks (using Google Books and Ngram Viewer – for 1990–2019); and trend analysis (using Google Trends – from 2004 to February 2024). The analysis showed an exponential increase in the number of publications since 2000, with peaks in 2008 (financial crisis), 2019–2020 (COVID-19), and 2023 (threat to food security due to military conflicts). The clustering of scientific papers by content showed that the most significant (red) cluster unites research that links food security to agricultural development, sustainable development, climate change, and water supply. The spatial clustering of scientific publications revealed that scientific leadership belongs to scientists from the United States and China. The largest research funders are Chinese scientific institutions. It also reflected regional differences in research focus. In particular, Italy, Switzerland, and France emphasize agricultural innovation and quality standards, while China and Australia focus on increasing yields and food storage technologies.

Multi-criteria GIS-based land suitability analysis for rice cultivation: a case study in Guilan Province, Iran.

Ensuring food security and sustainable resource management has become a paramount global concern, prompting significant attention to land suitability analysis for enhancing agricultural production. In this study, an AHP-weighted overlay method was employed to delineate rice cultivation suitability in Guilan province, Iran, a central hub for rice production. Sixteen climatic, topographic, and soil variables were integrated, and individual maps were reclassified to align with the specific requisites for rice production. The results revealed three suitability classes: including 'very suitable,' 'suitable,' and 'moderately suitable', covering 91%, 6%, and 3% of the land, respectively. Soil attributes, particularly organic matter, significantly influenced suitability (weight value of 0.745), with topographic and soil factors outweighing climate in assessment. While salinity is generally absent, organic matter deficiency affects 44% of the land. Phosphorus imbalances are prevalent, with potassium toxicity observed in 10%. Microelement deficiencies, especially in iron and zinc, are noted. Additionally, the results indicated that topographic and soil attributes played a more significant role than climate-related factors in assessing land suitability for rice cultivation within the study area. This research provides a comprehensive spatial analysis of all variables in the study region, shedding light on the complexities of land suitability for rice cultivation. These findings contribute to the understanding of agricultural sustainability and resource management strategies in the context of food security.

An automatic rice mapping method based on an integrated time-series gradient boosting tree using GF-6 and sentinel-2 images

ABSTRACT Timely and accurate mapping of paddy rice cultivation based on remote sensing technology is crucial and valuable for ensuring food security and sustainable environmental management. In most relevant studies, rice mapping was conducted using time-series images, but conventional rice mapping methods are not specifically designed for time-series data, making it difficult to extract the deep information contained in these data. To address these problems, in this paper, an automatic rice mapping method based on an integrated time-series gradient boosting tree (Auto-ITSGBT) is proposed using GF-6 WFV and Sentinel-2 MSI data. This method accounts for the local and overall shape features of time-series curves, and fully exploits the information related to phenological characteristics between time-series data. The proposed rice mapping method is tested and validated in three typical rice-producing areas, which are located in different provinces of China characterized by diverse climate conditions, planting times or topographies. The results show that the overall accuracy and Kappa coefficient of the method exceeded 95% and 0.93, respectively, at all study sites, respectively. Our method performs better than the existing competing methods, with an overall accuracy improvement of 2% to 4%. To identify the rice planting areas as early as possible, rice mapping was conducted by reducing the number of images one by one. The rice distribution map was obtained in mid-July with an overall accuracy of at least 90%, thus obtaining a spatial distribution map of rice with high accuracy before harvesting.

Optimizing the water-ecosystem-food nexus of avocado plantations

Climate change, food and water security and ecosystem sustainable management are tightly interlinked and require holistic approaches to achieve solutions that do not impact adversely one-another. The objective of this work was to conduct studies, collect data and assess the Water-Ecosystem-Food (WEF) nexus in avocado plantations in the Mediterranean region systematically to minimize the environmental footprint while maximizing the benefits for the farmer and the environment. The study includes two distinct experiments; the first addresses the impact of soil organic amendments addition to optimize the WEF nexus and the second monitors experimentally crop water needs and thus illustrates how irrigation practices aided by technology can reduce substantially water consumption. The results showed that organic amendments addition improves fertility, nutrient sequestration and structure but only had a weak effect on biodiversity by increasing the number of unique species. For the development of an efficient irrigation system it is necessary to determine the radius around the tree, the depth of the roots and the time required for the water to reach the active root zone to determine the amount and duration of irrigation. In this way sufficient water will be added to replenish the soil moisture deficit created due to the evapotranspiration. HYDRUS-1D model was used to simulate soil moisture and the hydrologic budget of an avocado tree located in Koiliaris river basin and confirm the percolation losses to groundwater. The results of this study showed that the actual irrigation needs of avocados in the Mediterranean is less than 2,000 m3/ha which is 75% less than what is recommended and could become the primary measure for the mitigation of climate change impacts especially in semi-arid regions such as the Mediterranean.

A Novel Hybrid Method for Predicting Specific Crop Yield

Predicting crop yields is crucial for economic planning, food security, and agricultural management. Conventional approaches frequently need accurate results regarding the complex interaction between environmental conditions and crop-specific traits. By combining the best features of machine learning algorithms with expert-level domain knowledge, we provide a new hybrid approach to predicting crop yields that is both state- and crop-specific. Our approach integrates historical yield data, satellite imagery, meteorological data, soil properties, and crop-specific information to build robust predictive models. Specifically, we employ ensemble learning techniques, including random forest and gradient boosting, to capture complex nonlinear relationships and improve prediction accuracy. Additionally, we incorporate domain knowledge through feature engineering and selection to enhance model interpretability and generalization. We validate our method using real-world datasets from diverse geographical regions and crops, demonstrating its superior performance compared to traditional approaches. Our proposed hybrid method offers a promising solution for accurate and reliable crop yield prediction, facilitating informed agricultural decision-making.

Cereal-Legume Mixed Residue Addition Increases Yield and Reduces Soil Greenhouse Gas Emissions from Fertilized Winter Wheat in the North China Plain

Incorporating crop residues into the soil is an effective method for improving soil carbon sequestration, fertility, and crop productivity. Such potential benefits, however, may be offset if residue addition leads to a substantial increase in soil greenhouse gas (GHG) emissions. This study aimed to quantify the effect of different crop residues with varying C/N ratios and different nitrogen (N) fertilizers on GHG emissions, yield, and yield-scaled emissions (GHGI) in winter wheat. The field experiment was conducted during the 2018–2019 winter wheat season, comprising of four residue treatments (no residue, maize residue, soybean residue, and maize-soybean mixed residue) and four fertilizer treatments (control, urea, manure, and manure + urea). The experiment followed a randomized split-plot design, with N treatments as the main plot factor and crop residue treatments as the sub-plot factor. Except for the control, all N treatments received 150 kg N ha−1 season−1. The results showed that soils from all treatments acted as a net source of N2O and CO2 fluxes but as a net sink of CH4 fluxes. Soybean residue significantly increased soil N2O emissions, while mixed residue had the lowest N2O emissions among the three residues. However, all residue amendments significantly increased soil CO2 emissions. Furthermore, soybean and mixed residues significantly increased grain yield by 24% and 21%, respectively, compared to no residue amendment. Both soybean and mixed residues reduced GHGI by 25% compared to maize residue. Additionally, the urea and manure + urea treatments exhibited higher N2O emissions among the N treatments, but they contributed to significantly higher grain yields and resulted in lower GHGI. Moreover, crop residue incorporation significantly altered soil N dynamics. In soybean residue-amended soil, both NH4+ and NO3− concentrations were significantly higher (p < 0.05). Conversely, soil NO3− content was notably lower in the maize-soybean mixed residue amendment. Overall, our findings contribute to a comprehensive understanding of how different residue additions from different cropping systems influence soil N dynamics and GHG emissions, offering valuable insights into effective agroecosystems management for long-term food security and soil sustainability while mitigating GHG emissions.

Factors influencing the allocative efficiency of the small-scale tomato (Lycopersicum species) production in Kaduna state, Nigeria: implications for food security and resource management

This study evaluated factors influencing the allocative efficiency of the small-scale tomato (Lycopersicum species) production in Kaduna State, Nigeria: implications for food security and resource management. A multi-stage sampling technique was used to select 120 small-scale tomato farmers. The data from primary sources was collected with the help of a well-structured and well-designed questionnaire. This data was analyzed using descriptive and inferential statistics. The result indicates that the mean age of the small-scale tomato resource farmers is 46 years old; the mean household size of the respondents is 7 persons, while the mean resource farm size is 1.17 ha. The minimum and the maximum allocative efficiency scores of the tomato farmers are 0.30 and 0.93 respectively. The results of the profitability analysis indicate that the tomato production is profitable with a gross margin and a net farm income of N550, 960 per ha and N497, 190 respectively. The gross margin and operating ratios are 0.69 and 0.28 respectively. The resource inputs and socio-economic factors influencing the allocative efficiency of tomato production are the following: age, farm size, household size, gender, marital status, level of education, access to extension services, and membership in a cooperative organization. The study recommends that farmers should be provided with the following resource inputs: improved seeds, chemicals, fertilizer inputs, credit facilities and extension services in order to reduce resource wastages, increase efficiency and productivity. Keywords: allocative efficiency, small-scale tomato production, resource management, food security, Kaduna State, Nigeria

Empowering Economic Development: A Case Study Analysis of Agricultural Commodity Production in Nepal's Local Markets with a Focus on Farmers and Traders (2021/ 22)

For economic development, Agriculture is the ultimate source of production to survive and manage economy and market system both. Nepal is divers with full of opportunities from the agriculture productions with three distinct geography such as hill, mountains and terai. This study aims to find out the role of consumable agriculture production in the economic development of Nepal. A mixed method approach is planned to conduct this research following the secondary data from the Government of Nepal that cross verified with the traders, farmers and various Key Informant persons using primary data collection tools. Study was conducted during 2022-23 and farmers and traders' data from all seven provinces were contracted and interviewed. The results shows that the role of agriculture production plays a vital role managing food security and economic situation of the Country. The local production is not enough to meet the requirement of Nepal. Import from India, China and Other countries supporting and meeting the requirement so the peoples. The study concluded as the GDP value of the local Production significantly plays a role in the positive development of Nations for the growth and sustainability. However, the local production is the ultimate way out to manage long-term sustainability in the study. Researcher suggesting instead of imports from neighbor country. A local production and traders' management is recommending managing local food production availability as well as growth in economic development.

СТРАТЕГИЧЕСКИЕ ПОДХОДЫ К ОБЕСПЕЧЕНИЮ ПРОДОВОЛЬСТВЕННОЙ БЕЗОПАСНОСТИ В УСЛОВИЯХ НЕОПРЕДЕЛЕННОСТИ

The current global situation is characterized by a high degree of uncertainty and risk. Epidemics, natural disasters, economic crises and other factors can dramatically affect food security. Therefore, developing strategies that can adapt to changing conditions becomes an important task. The paper examines the issue of ensuring food security in conditions of uncertainty. The concept of food security strategy and the importance of food market infrastructure in achieving this goal are considered. There are two key approaches to ensuring food security: traditional and flexible. The characteristics and features of each of these strategies are analyzed in detail. Traditional strategy focuses on stability and predictability, while flexible strategy aims to adapt to changing conditions. Particular attention is paid to the proposed algorithm for selecting a food security strategy, which takes into account a number of factors, including the level of risk, degree of uncertainty, product availability and budget constraints. This algorithm provides a scientifically proven method for selecting the optimal strategy, taking into account the context and specifics of the situation. Research is that both approaches, traditional and flexible, have their own unique advantages and can be applied in different contexts depending on the level of uncertainty and degree of risk. The choice between them depends on the specific needs and characteristics of the country or region, allowing for effective management of food security in a changing environment. The author proposes a comprehensive approach to ensuring food security, including the development of strategies, methods and selection algorithms, which makes it an important contribution to the field of food security and risk management.

The Impact of Climate Change on Food Security and Natural Resource Management in Smallholder Crop Farming Systems at Mthonjaneni Local Municipality, Kwazulu-Natal, South Africa

This study assessed the impact of climate change on food security and natural resource management on crop farming systems. Forty-five respondents were interviewed using an open-ended, and structured questionnaire. The open-ended questions allowed respondents to share their thoughts and experiences in their own words, while the structured questions helped to ensure that all respondents were asked the same questions and that the data collected was consistent. The results of this study showed that smallholder farmers perceived an increase in hot days (51.1%), a decrease in rainfall (51.1%), and a decrease in flood occurrence (71.1%). In addition, 95.2% of the respondents indicated that climatic conditions have influenced their farming systems. Natural resource changes noticed by farmers because of climate change include reduced grazing feedlot for livestock farmers (85%), reduced herbaceous cover (80%), decline in volume of water (57.8%), and increased tree damage and land degradation (11.1%). Increased soil erosion (6.7%) and increased bush encroachment (2.2%) were some of the natural resource challenges facing smallholder farmers. Some signs of climate change experienced by farmers included increases in crop pests (71%) and crop disease (8,9%). The adaptation strategies applied included the following: use of water harvesting, use of little soil disturbance techniques, adjusted fertiliser use, application of different planting dates techniques, use of different crop varieties, use of drought tolerant seeds, applied crop diversification, use of techniques that shortened growth length, planting new trees and avoiding planting on sloppy areas, and applied soil conservation techniques. Agriculture extension advisors should address vulnerable systems, including agricultural water and natural resources. In addition, it is important for agriculture extension advisors to strengthen the link between climate change adaptation and key climate change policy processesto improve their effectiveness and ability to deal with the effects of climate change. This will help overcome shortcomings along the food value chain and ensure food security.

Temporally transferable crop mapping with temporal encoding and deep learning augmentations

Detailed maps on the spatial and temporal distribution of crops are key for a better understanding of agricultural practices and for food security management. Multi-temporal remote sensing data and deep learning (DL) have been extensively studied for deriving accurate crop maps. However, strategies to solve the problem of transferring crop classification models over time, e.g., training the model with data for a recent year and mapping back to the past, have not been fully explored. This is due to the lack of a generalized method for aggregating optical data with regard to the irregularity in annual clear sky observations and the scarcity of multi-annual crop reference data to support a more generalized DL model. In this study, we tackled these challenges by introducing a method namely Temporal Encoding (TE) to capture the irregular phenological information. Subsequently, we adapted and integrated two methods, i.e., Random Observations Selection (ROS) and Random Day Shifting (RDS) to simulate the variability of temporal sparsity as well as the shifts of crop phenology over different years. We tested this approach with a 1-dimensional Convolutional Neural Network (1D-CNN) and a Transformer Network models. Our results for both classifiers showed that models trained with crop reference data from 2018 and a dense time series of Landsat 7/8 and Sentinel-2 A/B data can be transferred with little decreases in accuracy to map 12 consecutive years from 2010 to 2021. The Transformer Network was slightly more accurate, while the 1D-CNN was much three times faster. Furthermore, the proposed models could achieve similar performances in the same years with and without fully available satellite information. The TE with ROS and RDS appears well suited for improving temporal transferability to support long term historic crop mapping.