Suitable Cultivation Areas Research Articles

Predicting potential biomass production by geospatial modelling: The case study of citrus in a Mediterranean area

Residual biomass from agricultural production and processing, such as citrus pulp and olive pomace, is an important resource for energy production. In particular, this is the case in regions where transformation industries are concentrated.Current biomass estimates often focus on actual production data, that may not fully capture the biomass potential across all suitable cultivation areas. To bridge this gap, the study predicts the overall potential biomass available for energy production, taking into account the total area suitable for citrus cultivation.The research is focused on the study of citrus species in the province of Syracuse, Sicily, Italy. The methodology combines Geographic Information System (GIS) tools, for data interpolation and map overlays, with Software for Assisted Habitat Modelling (SAHM) for local level simulations.The results of the different models showed accurate and spatially coherent predictions, with AUC values ranging from 0.85 to 0.90, and highest potentialities in the northern and eastern regions of the study area. The results highlighted potential citrus cultivation on 47,706 ha and estimated 184,340 t of biomass, 16,461,520.82 Nm3 of biogas, and 8110 t of digestate. The results of the study identified potential areas for both increasing biomass production and optimising the distribution of digestate, thus demonstrating the utility of these thematic maps as a decision support tool for land management. The simulations and the methodology applied in this study indicated potential economic and environmental benefits to be gained from sustainable by-product management. This approach facilitates the optimisation of decision-making processes for land planning, thereby contributing to the broader objective of improving resource efficiency and sustainability in the agricultural production and processing sectors.

Alterations in Suitable Cultivation Area for Scutellaria baicalensis under Future Climatic Scenarios in China: Geodetector-Based Prediction

The dried roots of Scutellaria baicalensis (S. baicalensis) have been widely used as a traditional medicine. Recently, climate change and human activities have caused the degeneration of its wildlife habitat. However, there is rare knowledge on the effect and interactive effect of different variables on the spatial heterogeneity of S. baicalensis and how the pattern of suitable cultivation area in China would shift in response to climate change. Based on the Geodetector and Habitat Suitability Index (HSI) method, we proposed an assessment model to identify the critical environmental variable(s) affecting the distribution of suitable cultivation area for S. baicalensis in China and to project its shift under climate change. The results showed that soil and mean annual temperature are two determining variables in its spatial heterogeneity in China. Compared to 1981–2010, future climate change may result in a decrease in its suitable area, and yet may result in an increase in the extremely suitable area (about 1.00–1.35 million km2). S. baicalensis in the southern and northwestern part of its current distribution and the southwestern part and small area of northern China may experience expansion during the 21st century, while S. baicalensis in southern China, the Huang-Huai-Hai plain, and the midwest of northwestern China may experience contractions. Meanwhile, climate warming is expected to shift its distribution northwest through an expansion at the northern (at least 84 km) and western (at least 62 km) boundary and contraction at the southern (at least 529 km) boundary, respectively. These results could provide valuable information to policy-makers for the conservation and scientific introduction of S. baicalensis.

Ecological niche modeling to identify cultivation areas for pineapple in the Republic of Benin

Pineapple is one of the most important tropical fruit species, widely cultivated and economically important in Benin. This study aimed to identify potentially favorable areas for the cultivation of pineapple under current and future environmental conditions in Benin. The two cultivars of pineapple grown in Benin were separately considered: Sugarloaf and Smooth Cayenne. Five (05) modeling algorithms such as Maxent, Random Forest (RF), Support-Vector Machines (SVM), Boosted Regression Trees (BRT) and Generalized Linear Model (GLM) were compared using the criteria: area under the curve (AUC), sensitivity, specificity, Cohen’s Kappa, deviance and True Skill Statistic (TSS). The future climate models available for Africa at horizon 2055 were used under the “Representative Concentration Pathways” scenario 4.5 and 8.5. Results suggested that pineapple suitable areas were governed by a combination of effects of climate (temperature and precipitation) and soils characteristics. Indeed, soil pH, temperature seasonality and precipitation of driest quarter were the main variables driving pineapple production in Benin. Results also indicated that RF was the most suitable technique to model the distribution of pineapples regardless of the variety. The current potential range of favorable areas for the two varieties was mainly found in the central and southern parts of the country. In the future, following the RCP4.5 scenario, there will be an increase in the area favorable for the cultivation of Smooth Cayenne variety by 5.28% compared to the current situation whereas, the area favorable for the cultivation of the Sugarloaf variety will be increased by 7.7%. However, suitable areas for cultivation of Smooth Cayenne and Sugarloaf following the RCP8.5 scenario will be increased, respectively by 21.82% and 31.64%. The low and medium suitability areas for the cultivation of smooth cayenne will decrease by 15.57% and 2.93%, respectively at the horizon 2055 with future conditions under RCP4.5, and 15.48% and 4.97%, respectively at the horizon 2055 with future conditions under RCP8.5. For sugarloaf, the low and medium suitable cultivation areas will decrease by 1.59% and 14.24, respectively at the horizon 2055 with future conditions under RCP4.5. According to RCP8.5, the low suitable areas will decrease by 5.08%. This study constitutes an initial step towards a sustainable scheme for planning exploration of the possibility of extending pineapple cultivation in Benin. Key words: Climate change, modeling, algorithms, pineapple, potential area distribution

Global prospects for cultivating Centella asiatica: An ecological niche modeling approach under current and future climatic scenarios

Centella asiatica is a medicinal plant recognized for its various benefits contributed by its metabolites and has been used as a food supplement since prehistorical times across various cultures. Due to the reliance on natural populations of C. asiatica and the impacts of environmental factors on its yield and centelloside production, there is a need to identify suitable cultivation areas for this species. We employed ecological niche modelling with bioclimatic and soil variables to evaluate the suitability of cultivation under current and future climatic scenarios. Our results identified suitable areas for cultivating C. asiatica worldwide, indicating its potential for global commercial cultivation. However, the niche reconstruction of highly concentrated centelloside was restricted to South and Southeast Asia due to the lack of available data. When we projected the modelled niche of centelloside in these regions, we observed a lower occurrence probability in some areas, suggesting potential challenges in cost-effectiveness. Nevertheless, our results suggest a consistent future distribution for this species when we projected the modelled niche under future climates based on various socio-economic scenarios. This study not only identifies suitable areas to develop commercial cultivation for C. asiatica with highly concentrated centelloside, but also provides supporting evidence of the consistency of these areas, which can increase its sustainability.

Assessing the potential for seaweed cultivation in EU seas through an integrated modelling approach

The potential of large-scale seaweed cultivation to contribute to achieving ambitious EU-wide objectives, such as food security, energy independence, carbon neutrality and ecosystems restoration, is widely recognized. However, there is a lack of information on the suitability of EU marine regions for the installation of floating macro-algae cultivation infrastructures. In this study, we utilize the World Offshore Macro Algae Production Potential (WOMAPP) model in conjunction with state-of-the-art coupled hydrodynamic-biogeochemical models, to assess the environmental suitability of EU marine regions for seaweed cultivation. Our analysis reveals that the EU Atlantic regions are the most suitable areas for seaweed cultivation, particularly for cold-water and intermediate-water species. The potential cultivation area is extensive, spanning over 1 million km2, and even taking a precautionary approach by occupying only 1% of that area could yield a yearly production of over 30 million tonnes dry weight. Adding logistical constraints (water depth and distance to coast) further limit the potential production to 5 million tonnes per year, only considering EU member states' waters. Furthermore, we discuss the opportunity to use integrated multi-trophic aquaculture (IMTA), to increase the potential for seaweed cultivation.

Effects of different culture methods on growth, meat yield, and nutritional composition of Mediterranean mussels (Mytilus galloprovincialis), south side of Marmara Sea, Türkiye

This study, conducted between February 2016 and October 2017 on the coast of Erdek in the Marmara Sea, established two longline systems (buoy and pipe). Monthly growth rates of juvenile mussels placed in polyethylene and polyamide nets within these systems were monitored. The monthly chemical composition and meat yield of mussels that reached harvest size were analyzed in both systems. Environmental parameters were measured monthly to assess environmental conditions. The highest meat yield of harvested mussels was recorded in January, with values of 36.99 ± 0.72% for mussels cultured in the pipe system and 31.43 ± 1.82% for those cultured in the buoy system. The highest growth in mussels was achieved in the group cultured in the pipe system within polyamide nets. The December sample showed the highest moisture content of 83.98% and the highest ash content of 2.34%. The highest crude fat content was found in the September sample. The June sample had the highest protein content. The Black Sea, Sea of Marmara, and Aegean Sea offer suitable areas for mussel cultivation. Currently, mussel farming is conducted in these areas, producing tens of thousands of tons annually. This publication contributes to the expansion of the production process.

The optimized Maxent model reveals the pattern of distribution and changes in the suitable cultivation areas for Reaumuria songarica being driven by climate change.

Reaumuria songarica, a drought-resistant shrub, is widely distributed and plays a crucial role in the northern deserts of China. It is a key species for desert rehabilitation and afforestation efforts. Using the Maxent model to predict suitable planting areas for R. songarica is an important strategy for combating desertification. With 184 occurrence points of R. songarica and 13 environmental variables, the optimized Maxent model has identified the main limiting factors for its distribution. Distribution patterns and variation trends of R. songarica were projected for current and future climates (2030s, 2050s, 2070s, and 2090s) and different scenarios (ssp_126, ssp_370, and ssp_585). Results show that setting parameters to RM (regulation multiplier) = 4 and FC (feature combination) = LQHPT yields a model with good accuracy and high reliability. Currently, R. songarica is primarily suitable for desert control in eight provinces and autonomous regions, including Inner Mongolia, Xinjiang, Qinghai, and Ningxia. The total suitable planting area is 148.80 × 104 km2, representing 15.45% of China's land area. Precipitation (Precipitation of the wettest month, Precipitation of the warmest quarter, and Annual precipitation) and Ultraviolet-B seasonality are the primary environmental factors limiting the growth and distribution of R. songarica. Mean temperature of the warmest quarter is the primary factor driving changes in the distribution of suitable areas for R. songarica under future climate scenarios. In future climate scenarios, the suitable planting area of R. songarica will shrink, and the distribution center will shift towards higher latitude, potentially indicate further desertification. The area of highly suitable habitat has increased, while moderately and less suitable habitat areas have decreased. Increased precipitation within R. songarica's water tolerance range is favorable for its growth and reproduction. With changes in the suitable cultivation area for R. songarica, priority should be given to exploring and utilizing its germplasm resources. Introduction and cultivation can be conducted in expanding regions, while scientifically effective measures should be implemented to protect germplasm resources in contracting regions. The findings of this study provide a theoretical basis for addressing desertification resulting from climate change and offer practical insights for the development, utilization, introduction, and cultivation of R. songarica germplasm resources.

Weather Extremes Shock Maize Production: Current Approaches and Future Research Directions in Africa.

Extreme weather events have led to widespread yield losses and significant global economic damage in recent decades. African agriculture is particularly vulnerable due to its harsh environments and limited adaptation capacity. This systematic review analyzes 96 articles from Web of Science, Science Direct, and Google Scholar, focusing on biophysical studies related to maize in Africa and worldwide. We investigated the observed and projected extreme weather events in Africa, their impacts on maize production, and the approaches used to assess these effects. Our analysis reveals that drought, heatwaves, and floods are major threats to African maize production, impacting yields, suitable cultivation areas, and farmers' livelihoods. While studies have employed various methods, including field experiments, statistical models, and process-based modeling, African research is often limited by data gaps and technological constraints. We identify three main gaps: (i) lack of reliable long-term experimental and empirical data, (ii) limited access to advanced climate change adaptation technologies, and (iii) insufficient knowledge about specific extreme weather patterns and their interactions with management regimes. This review highlights the urgent need for targeted research in Africa to improve understanding of extreme weather impacts and formulate effective adaptation strategies. We advocate for focused research on data collection, technology transfer, and integration of local knowledge with new technologies to bolster maize resilience and food security in Africa.

Predicting potential and quality distribution of Anisodus tanguticus (Maxim.) Pascher under different climatic conditions in the Qinghai-Tibet plateau.

Anisodus tanguticus (Maxim.) Pascher, a distinctive medicinal plant native to the Qinghai-Tibet Plateau, China, has garnered attention due to increasing market demand. This study explores the impact of environmental factors on the distribution and levels of active compounds namely anisodamine, anisodine, and atropine within A. tanguticus. Our goal was to identify suitable cultivation areas for this plant. This study employs the maximum entropy model to simulate the suitable area of A. tanguticus under current conditions and three climate change scenarios during the 2050s and 2070s. The finding revealed that altitude, precipitation in the warmest season (Bio 18), the average annual temperature (Bio 1) exerted significant influences on the distribution of A. tanguticus. Among the environmental factors considered, temperature difference between day and night (Bio 2) had the most substantial impact on the distribution of anisodamine, temperature seasonal variation variance (Bio 4) predominantly influenced anisodine distribution, and Bio 1 had the greatest effected on the distribution of atropine. The suitable areas primarily exist in the eastern Qinghai-Tibet Plateau in China, encompassing a total area of 30.78 × 104 km2. Under the climate scenarios for the future, the suitable areas exhibit increasing trends of approximately 30.2%, 30.3%, and 39.8% by the 2050s, and 25.1%, 48.8%, and 60.1% by the 2070s. This research would provide theoretical suggestions for the protection, and cultivation management of A. tanguticus resources to face the challenge of global climate change.

Comparison of Extraction accuracy of Sugarcane from different resolution satellite images using Deep lab V3+ Mode

Abstract. Sugarcane is an annual or perennial persistent rooted tropical and subtropical herb that grows in tropical and subtropical regions. As China's production ranks among the world's leading, sugarcane industry is an important part of agricultural economy in China. As the largest sugarcane production center in China, Guangxi is one of the most suitable areas for sugarcane cultivation in China and even in the world. Sugarcane industry, as an agricultural advantageous industry in Guangxi, not only has a significant image to the national economy of the region, but also is closely related to the issue of security of national sugar supply. Continuous cropping of sugarcane is very common in Guangxi, which is very helpful for the concentration selection of sugarcane samples. The wide application of satellite remote sensing monitoring technology has become an indispensable means of natural resources monitoring. Using optical satellite remote sensing image to identify and extract sugarcane planting areas is of great significance to quickly and conveniently grasp the information of sugarcane distribution and yield. In this paper, the precision of sugarcane extraction from GF1 and GF2 satellite images is analyzed by using deeplab V3 + model, the effect of optical remote sensing images with different resolution on sugarcane extraction accuracy was studied to provide better data support for dynamic monitoring of sugarcane planting.

Predicting the suitable cultivation areas of breadfruit crops Artocarpus altilis (Moraceae) under future climate scenarios in Central Java, Indonesia.

Artocarpus altilis, commonly known as breadfruit, is a potential crop adapted to a wide variety of climates and widely spread, including in Indonesia. However, information on how this species can adapt to climate change, in particular in Central Java, is still limited. In Indonesia, Central Java is the center for cultivation areas for many crop species to support the 145 million people living on Java Island. One of the potential crops being developed in Central Java is breadfruit. To assess the suitable cultivation areas for breadfruit, species distribution modeling (SDM) was used to predict the current and future (2050-2070) distribution of breadfruit. Two climate change scenarios, including optimistic RCP2.6 and pessimistic RCP8.5 models, were considered to represent future climate change impacts. Based on the results for both optimistic and pessimistic scenarios, the breadfruit's suitable cultivation areas will expand eastward. Implementing a mitigation climate change scenario and limiting the temperature increase to only 1°C under RCP2.6 will provide 270.967 km2 more of suitable cultivation areas for breadfruit in 2050 and 133.296 km2 in 2070. To conclude, this study provides important information on the status and potential cultivation areas for breadfruit, mainly in the Southeast Asia region. The identification of suitable areas will guide land conservation for breadfruit to support food security in this region.

Risk of climate change to sweet potato cultivation in the American continent

ABSTRACT Sweet potato, Ipomoea potatoes L., is an essential crop for food security in various countries. However, the effects of climate change could reduce or increase the yield and profitability of this crop, especially for small farmers. Thus, we developed species distribution models for the current and six climate change scenarios based on environmental variables, species occurrence, and global climate change model. Also, we identified the most relevant environmental variables for cultivation. Future scenarios showed gradual shifts in suitable areas for cultivation. Losses in suitable areas were more relevant than gains at the low concentration of greenhouse gas emissions (RCP 2.6). This trend is maintained in the worst scenario of a high concentration of greenhouse gas emissions (RCP 8.5) with more significant losses of suitable areas. The temperature and precipitation of warmest and wettest quarters, temperature seasonality, and isothermality are the most critical variables for sweet potato cultivation. The cultivation is expected to expand the suitable areas in some regions and retract in others due to climate change. Knowledge about climate change effects in cultivated areas is essential for developing management plans that could mitigate the adverse effects of climate change.

Climate change impacts on coffee production in Indonesia: A review

Indonesia is ranked in the top 5 coffee production countries in the world with the largest production being Arabica and Robusta coffee beans. Approximately ninety percent of coffee produced in Indonesia is being exported and as the trend in local consumption increases, the demand for coffee is escalating. However, future coffee production is challenged by climate change. Background: This paper outlines the impacts of climate change variables including environmental stressors on coffee production quality and quantity of Arabica and Robusta species, discusses the influences on suitable areas for coffee cultivation and the coffee pests related to coffee productivity, as well as suggests mitigation and adaptation approaches in Indonesia. Methods: The literature review approach was utilized to complete this paper which involves collecting, analyzing, and correlating the findings of prior studies. The paper only considered literature with the following terms in the title; climate change impact, coffee production, mitigation, adaptation, and Indonesia. Finding: Increasing temperature degrades coffee production both in Arabica and Robusta coffee beans. The overall suitable area for cultivating coffee is shifting towards higher altitudes However, Indonesia is projected to lose more than half of the suitable area for cultivating Arabica by the year 2050. Climate change improves coffee pests' thermal tolerance and enables them to grow in warm temperatures. Conclusion: Common mitigation approaches include shade plantation and soil moisturization control which both improve coffee productivity. Another strategy is the cultivation calendar modified the coffee life cycle with climate prediction.

Engineering design and economic analysis of offshore seaweed farm

As global demand for sustainable biomass and need to mitigate global warming begin to rise, cultivation of seaweed has gained significant attention in recent years due to its potential for carbon recycling. However, limited availability of suitable coastal areas for large-scale seaweed cultivation has led to exploration of offshore environments as a viable alternative. The nature of many offshore environments often exposes seaweed farming systems to harsh environmental conditions, including strong waves, currents, and wind. These factors can lead to structural failures, kelp losses, and significant financial losses for seaweed farmers. The main objective of this study is to present a robust design and numerical analysis of an economically viable floating offshore kelp farm facility, and evaluate its stability and mooring system performance. A numerical method of preliminary designs of the offshore aquaculture systems were developed using the OrcaFlex software. The models were subjected to a series of dynamic environmental loading scenarios representing extreme events. These simulations aimed to forecast the overall dynamic response of an offshore kelp farm at a depth of 50m and to determine the best possible farm design with structural integrity for a selected offshore environment. Furthermore, to assess the economic feasibility of establishing offshore seaweed farms, a comprehensive capital expenses analysis was conducted. The results revealed that, in terms of the kelp farms with the same number of the kelp cultivating lines, the cost of building kelp farms will be strongly affected by the cost of mooring lines. The present study may help to understand the dynamic response and economic feasibility of offshore kelp farms.

Ultra-fine bubble irrigation promotes coffee (Coffea arabica) seedling growth under repeated drought stresses

ABSTRACT Coffee plants are likely to be highly susceptible to changes in climate, and several statistical studies based on projections of altered precipitation patterns have predicted negative effects on coffee growth including the loss of suitable cultivation areas in most coffee-producing countries. Increased drought occurrences owing to climate change are expected to be a new challenge for stable coffee production, because coffee production relies heavily on stable rainfall conditions. In recent years, ultra-fine bubble (UFB) water has been reported to be effective in alleviating environmental stresses for plant growth, especially drought stress. The objective of the present study was to determine the effect of UFB water irrigation on the growth of coffee seedlings to mitigate the stress of repeated droughts. To simulate an environment with frequent droughts, six pot experiments were conducted over 3 years by applying repeated drought stress to coffee plants in a greenhouse. The results showed that UFB water had a remarkable growth-promoting effect on coffee seedlings under drought conditions. In contrast, no significant effect on coffee growth was observed in the environment with sufficient nutrients, in which additional fertilizer was used. UFB water significantly increases the root length and surface area of coffee plants, which may promote water absorption and prevent leaf senescence (leaf cell collapse) under drought conditions. This leads to coffee plants adapting to drought conditions. Therefore, UFB water irrigation may be an effective measure to promote coffee growth in drought conditions.

The estimated suitability of land for hemp cultivation in the western region of Romania

In any region of the globe, the cultivation of industrial crops, including hemp, imposes certain conditions related to relief, climate, hydrology, or soil. The interrelations between these factors lead to differentiations regarding the establishment of cultivation zones and implicitly in terms of productivity. This study aimed to identify suitable areas for hemp cultivation and generate favorability maps in western Romania, based on GIS and MCDA techniques. Ten factors, significantly important for hemp cultivation, related to relief, climatic conditions, soil, and human intervention were considered. Following spatial analyses using the Weighted Overlay Analysis (WOA) method, the territory was classified into four zones: Zone I, with highly suitable lands (26%), located in the western half, overlapping with plain areas and river valleys; Zone II, with moderately suitable lands (28%), located in regions of high plains and hilly areas; Zone III, with marginal lands (3%), located in some depression areas, hilly areas, or at the contact with pre-mountainous areas; Zone IV, with unsuitable lands for hemp cultivation, in mountainous areas, under restrictive environmental conditions. The obtained results can be used in land management strategies or by farmers for estimating available land resources.

Global ocean spatial suitability for macroalgae offshore cultivation and sinking

Macroalgae offshore cultivation and sinking is considered a potentially practical approach for ocean-based carbon dioxide removal. However, several considerations need to be resolved to assess the effectiveness and sustainability of this approach. Currently, several studies focus on the area required for climate-relevant carbon sequestration through macroalgae cultivation and sinking without considering realistic, global spatial limitations. This study uses a spatially-explicit suitability assessment model for optimised open-ocean afforestation and sinking site designation. By applying specific maritime, ecological and industrial constraints, two maps are produced: a) suitable areas for macroalgae offshore cultivation and sinking, and b) suitable areas for macroalgae sinking only (for sequestration purposes). These data provide a more realistic approach to quantifying the ocean surface (including the corresponding depths) required for macroalgae offshore cultivation and sinking within a spatially sustainable framework. The resulting maps estimate the respective suitability areas within the EEZs of the world countries. A total area suitable for macroalgae offshore cultivation and sinking is calculated at 10.8M km2, whereas sinking-only areas account for 32.8M km2 of the offshore ocean. The implications of spatial suitability patterns at global and national levels are discussed. We suggest that the concept of ‘grow nearshore, sink offshore’ should be explored as an alternative to offshore cultivation.

The potential for mitigating greenhouse gas emissions and minimizing yield losses using the negative pressure irrigation system

Efficient strategies for reducing agricultural greenhouse gas (GHG) emissions without yield penalties are crucial for sustainable agricultural development in the context of population increases and global warming. This study investigates the efficacy of negative pressure irrigation (NPI) in mitigating GHG emissions, as well as its impact on crop yield, global warming potential (GWP), and GHG emission intensity (GHGI), using surface irrigation (CK) as the control. The NPI system operated at three water pressure levels: NPI1 (-2 kPa), NPI2 (-4 kPa), and NPI3 (-6 kPa). The results revealed a notable pattern under NPI: a single peak in GHG emissions that remained consistently, and much lower than CK for the majority of the vegetable season, directly results in the lower cumulative GHG emissions and GWP from NPI than those from CK. Notably, the central region, located near the emitter, exhibited significantly lower GWP compared to the edge region, accompanied by higher yields, leading to a lower GHGI. Based on the findings, the -2 kPa water pressure level demonstrated the optimal performance in sustaining crop yields for Chinese chives while effectively reducing GWP and GHGI. Additionally, regions situated 20 cm on both sides of the emitter under -2 kPa NPI were identified as suitable areas for crop cultivation, offering higher yields and lower GWP and GHGI compared to CK. These results emphasize the win-win situation by balancing vegetable yield while reduced GHG emissions.

Estimation of the Impact of Climate Change on Spinach Cultivation Areas in Türkiye

Climate change is one of the most important problems that needs to be dealt with in Türkiye and worldwide. One of the sectors that will be most affected by climate change is the agriculture sector. For this reason, it is very important to adapt to changing climatic conditions, take the necessary precautions, and ensure sustainability in the agricultural sector today. The land suitability for spinach (Spinacia oleracea L.) cultivation, a vegetable that is rich in nutrients, has never been investigated in Türkiye. Therefore, it is important to investigate the suitability of spinach cultivation areas in Türkiye in the case of possible climatic changes in future years. The most important original value of this research is that three separate climate change prediction models were used, as opposed to using only a single climate change prediction model, to determine the land suitability for spinach cultivation. The aim of this study is to determine the land suitability for spinach in line with possible climate change prediction models and scenarios in Türkiye and its evaluation by comparing it with the current model. To achieve this goal, HADGEM2_ES, CNRM_CM5, and MPI_ESM_LR climate models and RCP 4.5 and RCP8.5 scenarios were used, and land suitability was determined and evaluated with the help of Ecocrop integrated into DIVA-GIS for spinach in Türkiye currently and in the 2050s. The results found that there will be decreases in suitable, very suitable, and excellent areas for spinach cultivation and increases in not-suited, very marginal, and marginal areas. Considering the possible temperature and precipitation changes, it has been observed that the areas in which spinach can be grown in Türkiye in the 2050s will be negatively affected by climate change due to the increasing temperature and decreasing precipitation in general, and solutions are proposed in this study to ensure sustainability.

A Study on Analyses of the Production Data of Feed Crops and Vulnerability to Climate Impacts According to Climate Change in Republic of Korea

According to the climate change scenario, climate change in the Korean Peninsula is expected to worsen due to extreme temperatures, with effects such as rising average temperatures, heat waves, and droughts. In Republic of Korea, which relies on foreign countries for the supply of forage crops, a decrease in the productivity of forage crops is expected to cause increased damage to the domestic livestock industry. In this paper, to solve the issue of climate vulnerability for forage crops, we performed a study to predict the productivity of forage crops in relation to climate change. We surveyed and compiled not only forage crop production data from various regions, but also experimental cultivation production data over several years from reports of the Korea Institute of Animal Science and Technology. Then, we crawled related climate data from the Korea Meteorological Administration. Therefore, we were able to construct a basic database for forage crop production data and related climate data. Using the database, a production prediction model was implemented, applying a multivariate regression analysis and deep learning regression. The key factors were determined as a result of analyzing the changes in forage crop production due to climate change. Using the prediction model, it could be possible to forecast the shifting locations of suitable cultivation areas. As a result of our study, we were able to construct electromagnetic climate maps for forage crops in Republic of Korea. It can be used to present region-specific agricultural insights and guidelines for cultivation technology for forage crops against climate change.