Cropping Pattern Research Articles

Multi-objective cropping pattern optimization and comparative assessment with the food-energy-water nexus

ABSTRACT Agriculture is the largest consumer of water, accounting for nearly 70% of global freshwater consumption, and it also uses about 30% of the world's energy. This creates an increasing challenge for the efficient use of water and energy resources while adequately meeting food demand. Therefore, understanding the interrelations between food, energy, and water resources is crucial. In this study, a multi-objective linear programming model was employed to identify alternative scenarios for optimal cropping areas that minimize water use in agriculture and maximize agricultural income. Different weight coefficients were assigned to these objective functions to generate various cropping scenarios. Once the optimal cropping patterns for each scenario were determined, parameters such as water use, energy requirements, agricultural revenue, and carbon dioxide emissions were calculated based on the food-energy-water nexus. The results for each alternative crop pattern scenario were then analyzed. The results indicate that prioritizing the objective of minimizing water use leads to an average reduction of 3.35% in water use, 1.18% in energy demand, and 0.26% in carbon dioxide emissions, while agricultural income increases by an average of 1% compared to the base scenario. Conversely, when maximizing agricultural income is prioritized, there is an average increase of 2.05% in agricultural income.

A robust multi-objective optimization model for grid-scale design of sustainable cropping patterns: A case study

In the face of growing population, water scarcity, and increasing food demand, there is a pressing need to shift towards optimized, resource-efficient, climate-resilient, and sustainable agricultural practices. In light of that, designing a sustainable cropping pattern that considers the procedure of resource allocation based on land capabilities and crop features is vital for ensuring long-term food production and safeguarding the delicate balance of ecosystems. Motivated by this imperative, this study proposes a comprehensive framework that integrates Geographic Information System (GIS), System Dynamics (SD), and optimization to address the sustainable design of cropping patterns. The framework assesses grid-scale land suitability, models dynamic water resource interactions, and optimizes resource allocation based on crop calendar considerations. For the first time, a dynamic crop inventory is integrated into the cropping pattern optimization process, addressing food security concerns in a comprehensive manner. In order to evaluate the effect of uncertainties on the designed system, a robust optimization model is developed based on convex sets. The results demonstrate the advantages of the robust model in situations with uncertainty. Despite a 5% reduction in profit compared to the deterministic solution, the robust design achieves a 25% decrease in irrigation, highlighting the cost of ensuring sustainability. The deterministic approach prioritizes crops based on their economic value, whereas the robust solution considers the volume of irrigation required for a sustainable design. The managerial implications emphasize the importance of prioritizing water-efficient and climate-resilient agricultural practices to guarantee long-term food security.

Optimization of A Dynamic Program for Water Resources Utilization in the Mambal Irrigation Area

The Irrigation Area (D. I.) Mambal, which passes through Badung Regency, Denpasar City, and Tabanan Regency, is the largest irrigation water supplied by the Ayung River, covering an area of 5.963 Ha. Despite the Ayung River’s substantial water potential, the D. I. Mambal experiences water shortages during certain months. This research aims to improve the effectiveness and efficiency of irrigation water use based on the Global Planting Management Plan (RTTG) using simulation methods and dynamic program optimization. Simulations were carried out under low conditions, normal and sufficient dependable discharges, using both existing and alternative RTTG. The objective function of the dynamic optimization seeks to maximize revenue gain from the applied RTTG. The existing cropping pattern at the beginning of planting in October showed an average proportion of fulfillment of water irrigation needs at 85%. Under the Alternative I condition, with planting beginning in November, the average proportion of fulfillment of irrigation water needs was 89%. In Alternative II conditions, with planting beginning in December, the average proportion of fulfillment of irrigation water needs was 87%. By optimizing the water discharge using the dynamic program, the irrigation profit for the existing cropping pattern (October) amounted to IDR 491,816,154,938. The highest profit was obtained using the Alternative II cropping pattern (December), totaling IDR 606,675,369,830. Meanwhile, the lowest profit was obtained in the Alternative I cropping pattern (November), which was IDR 360,767,292,361. The analysis showed that the Alternative II cropping pattern, starting with the first rice planting period in December, yields the most optimal results. The analysis considers the optimized air allocation and irrigation benefits obtained from the third cropping pattern.

OPTIMASI DISTRIBUSI AIR IRIGASI MELALUI SISTEM GOLONGAN (STUDI KASUS DAERAH IRIGASI RONGKONG SELUAS 27.000 HA)

<p class="Abstract"><em>The utilization of river water to support activities in the agricultural sector includes constructing water structures that function to channel or supply water to rice fields through weirs. The water required for rice fields is referred to as irrigation water demand. The amount of water needed in irrigated areas varies, necessitating a water distribution management system, one of which involves creating a crop planting schedule with a technical/rotational system, ensuring the water balance of an irrigation area is well managed. The aim of this research is to achieve the most efficient planting and water distribution plan for an irrigation area, considering the water balance as an indicator of the water management system in fulfilling irrigation water needs. The method used involves comparing the water balance of irrigation areas where water is supplied using a rotational system versus without. The research results show that the appropriate cropping pattern for an irrigation area of more than 25,000 hectares (ha) is to use a rotational system. For the Rongkong Irrigation Area (DI) with a size of 27,947 ha, it is divided into two groups: Group 1 includes: Rongkong Right Irrigation Area with 4,198.38 ha and Rongkong Left Irrigation Area with 6,497.56 ha; Group 2 includes: Rongkong Right Irrigation Area with 7,501.22 ha and Rongkong Left Irrigation Area with 9,749.22 ha. Before using the rotational system, a water deficit occurred in the first week of October, amounting to 0.22 m³/second. However, after implementing the rotational system, the water balance in the Rongkong Irrigation Area no longer showed any water demand deficit.</em><strong></strong></p>

Agricultural Land Rental Arrangements in Nepal: Incidence, Forms, Determinants, and the Current Legal Provisions

Given the fragmented and small size of land holdings in Nepal, the viability of crop production is a pressing concern. Rental or tenancy arrangements, which equalise marginal returns from factors of production across households, offer a solution to this viability crisis. In this context, our study is unique as it not only examines the incidence and forms of tenancy, but also identifies the determinants of the land leasing decision of rural households, and discusses their implications for agrarian development in Nepal. Drawing on primary survey data from 350 households in six districts of plains and hills, we provide evidence of the widespread prevalence of informal tenancy in Nepal. Despite locational variations explained by the location-specific cropping patterns, sharecropping and fixed-rent are found to be the primary forms of tenancy contracts. A Tobit regression analysis identifies certain household level, farm level, and location-specific characteristics as important factors influencing land leasing decisions. Our analysis suggests that the land supply in the land lease market may increase in the future, and therefore, it is pertinent to examine the legal provisions that govern the use of such lands. Hence, we also examine the legal provisions concerning tenancy relations.

Geospatially Informed Water Pricing for Sustainability: A Mixed Methods Approach to the Increasing Block Tariff Model for Groundwater Management in Arid Regions of Northwest Bangladesh

Groundwater depletion in arid regions poses a significant threat to agricultural sustainability and rural livelihoods. This study employs geospatial analysis and economic modeling to address groundwater depletion in the arid Barind region of Northwest Bangladesh, where 84% of the rural population depends on agriculture. Using remote sensing and GIS, we developed an elevation map revealing areas up to 60 m above sea level, exacerbating evaporation and aquifer dryness. Field data collected through Participatory Rural Appraisal tools showed farmers exhibiting “ignorant myopic” behavior, prioritizing short-term profits over resource conservation. To address this, an Increasing Block Tariff (IBT) water pricing model was developed, dividing water usage into three blocks based on irrigation hours: 1–275 h, 276–550 h, and 551+ h. The proposed IBT model significantly increases water prices across the three blocks: 117 BDT/hour for the first block (from current 100–110 BDT/hour), 120 BDT/hour for the second block, and 138 BDT/hour for the third block. A demand function (y = −0.1178x + 241.8) was formulated to evaluate the model’s impact. The results show potential reductions in groundwater consumption: 59 h in the first block, 26 h in the second block, and 158 h in the third block. These reductions align with the principles of integrated water resource management (IWRM): social equity, economic efficiency, and environmental integration. The model incorporates economic externalities (e.g., well lifting costs) and environmental externalities (e.g., crop pattern shifts), with total costs reaching 92,709,049 BDT for environmental factors. This research provides a framework for sustainable groundwater management in arid regions, potentially reducing overextraction while maintaining agricultural productivity. The proposed IBT model offers a locally driven solution to balance resource conservation with the livelihood needs of farming communities in the Barind tract. By combining remote sensing, GIS, and economic modeling, this research provides a framework for sustainable groundwater management in arid regions, demonstrating the power of geospatial technologies in addressing complex water resource challenges.

Optimum Combination of Spectral Variables for Crop Mapping in Heterogeneous Landscapes based on Sentinel-2 Time Series and Machine Learning

Abstract. This article aimed to determine a workflow for more efficient large-scale crop mapping using a time series of images from the Sentinel-2 Satellite, statistical methods of attribute selection, and machine learning. The proposed methodology explores the best possible combination of spectral variables related to vegetation (16 vegetation indices in the RGB, NIR, SWIR, and Red Edge regions) to characterize different spectro-temporal profiles of Land Use and Land Cover (LULC) in spatially heterogeneous landscapes. First, we applied a data dimensionality reduction analysis using the PCA (Principal Component Analysis) method. Subsequently, the variables that showed the highest statistical correlation between each other were used in the spectro-temporal classification process, using the Random Forest, TempCNN, and LightTAE algorithms, following three different strategies: C1 (ALL), C2 (BE + IV (Red Edge)) and C3 (BE + IV (without Red Edge)), where ALL – All variables; BE – Spectral Bands; IV – Vegetation Indices. Given the results found, the C2 classification scenario (with bands B3, B4, B5, B6, B7, B8, and B8A and the NDRE1, RESI, and MSR indexes) demonstrated the best LULC classification accuracy at the crop pattern level, compared to the other scenarios, with average values of 0.91, 0.88, 0.91, 0.89, and 0.89 (Global Accuracy, Producer Accuracy, User Accuracy, Kappa index, and F1-Score, respectively, for the TempCNN model), the which emphasized the importance of both qualitative and quantitative variability of sampling data and variables based on the Red Edge region for improving LULC classification processes in large-scale heterogeneous landscapes.

Crop Pattern, Waterlogging and Salinity Nexus in Semi-Arid Region of Punjab, India

Crop Pattern, Waterlogging and Salinity Nexus in Semi-Arid Region of Punjab, India

Shifting agricultural land use and its unintended water consumption in the North China Plain

Agricultural land use (ALU) critically influences food production and water resource allocation. This study examines the dynamics of ALU in the North China Plain (NCP), a region characterized by intensive agriculture and severe groundwater over-exploitation, focusing on the multidimensional drivers and their implications for water resource management. By employing an elaborate classification scheme based on satellite imagery and extensive first-hand field data, we identified significant shifts in crop patterns. From 2013 to 2017, there was a notable transition from double crops (primarily wheat-maize) to single crops (primarily maize), covering 4600 km2 and accounting for 42% of single crops in 2013. From 2017 to 2022, there was a shift from single crops to economic forests, encompassing 3600 km2 and 22% of economic forests in 2017, including orchards, timber trees, and shelter forest belts. These shifts resulted in an 11% decrease in grain acreage (6800 km2) but an 11% increase in crop water consumption (6.3 km3) during 2013–2022. Notably, water consumption by economic forests increased by 126% (9.4 km3) during this period. This study highlights the critical need to balance competing demands for food and water security, providing valuable insights applicable to other agriculturally intensive regions worldwide.

Stakeholder-based management of ecosystem services in agricultural areas: Integrating the leader-follower game and a conflict resolution model

Given the substantial effects of agricultural practices on the environment, this paper introduces a novel stakeholder-based framework for assessing the ecosystem services (ESs) provided by agricultural areas. Ecosystem services include essential functions such as water supply, food production, carbon storage, soil erosion control, and habitat support. In addition to ESs, water footprint is also taken into account to evaluate the impacts of agricultural activities on water resources. Some of the mentioned ESs are assessed using the Soil and Water Assessment Tool (SWAT). Then, by extending and combining the Conflict Resolution Model with the Composition of Probabilistic Preferences (CRMCPP) method and the leader-follower game (LFG), while considering the hierarchical structure of decision-makers, the best scenario for enhancing the ESs is selected.The Zarrinehroud River Basin (ZRB) in Iran has been chosen as a case study to evaluate the performance of the proposed framework, as this basin is vital for supplying water to Lake Urmia, the largest hypersaline lake in the Middle East. In this paper, 16 Water and Environmental Resources Management (WERM) scenarios have been defined according to the Urmia Lake Restoration National Committee (ULRNC) projects. Then, the mentioned ESs have been evaluated under different WERM scenarios. Ultimately, by utilizing the CRMCPP-LFG method and taking into account the hierarchical structure of decision-makers, we can identify the optimal WERM scenario. The criteria for making this decision include various factors, such as ecosystem services and the costs involved in implementing the WERM scenarios. In the selected scenario, the average water inflow into Lake Urmia is projected to rise to 1329 million cubic meters per year, which is 6.3% more than the average inflow in the current condition. Key initiatives in this scenario include reducing cultivated areas, altering irrigation methods, changing crop patterns, and incorporating water-efficient plant species.

Performance Indicators for Improving Irrigation Management in Aegean District

Water is vital for agriculture and its effective use has become imperative. The largest share of freshwater use in the world is in the agricultural sector with a rate of approximately 70%. Therefore, the evaluation of irrigation schemes is of great importance. In Turkiye, irrigation schemes are managed and distributed by organizations such as water user associations, municipalities, and irrigation cooperatives. In Türkiye, irrigation schemes with an service area of 500 ha or more are managed by water user associations. In this study, Ahmetli, Salihli and Menemen water user associations’ irrigation schemes, where the Gediz River is used as a water source, were chosen as materials. The selected irrigation schemes service area constitutes 60% of the total service area in the region (DSI (General Directorate of State Hydraulic Works) 2nd Region(Aegean region)). The service area of Ahmetli irrigation scheme is 50,532 ha, 22,797 ha in Salihli and 22,865 ha in Menemen. The main crop pattern of the irrigation area is vineyards, corn and cotton. These irrigation schemes were evaluated using performance indicators such as water supply, irrigation rate, and amount of irrigation water used per unit area. The raw data sets obtained from DSI cover the years 2007 and 2021. As a result, when looking at the average performance, relative water supply, irrigation rate and amount of irrigation water used per unit area were found to be 0.70, 57.99 and 7682.45 m3 ha-1, respectively. Although 70% of the irrigation water need can be met with the water diversion to the system, the irrigation ratio was approximately 58% indicating the problems in transferring water to the system and the irrigation techniques used by farmers on the field are not modern. In addition, the main reasons for the unirrigated areas, are social and economic reasons (137 ha in the Menemen WUA) and the lack of water supply in the Salihli and Ahmetli WUAs, respectively, 2319 ha and 11320 ha cannot be irrigated, respectively. Modernization seems inevitable for more effective use of our water resources. The most effective techniques in this modernization are land consolidation, renewal of irrigation channels, extension and consultancy services to farmers, and making water fees according to volume can be counted.

Rice Under Dry Cultivation-Maize Intercropping Improves Soil Environment and Increases Total Yield by Regulating Belowground Root Growth.

Under the one-season-a-year cropping pattern in Northeast China, continuous cropping is one of the main factors contributing to the degradation of black soil. Previous studies (on maize-soybean, maize-peanut, and maize-wheat intercropping) have shown that intercropping can alleviate this problem. However, it is not known whether intercropping is feasible for maize and rice under dry cultivation, and its effects on yield and soil fertility are unknown. A three-year field-orientation experiment was conducted at Jilin Agricultural University in Changchun city, Jilin Province, China, consisting of three cropping regimes, namely rice under dry cultivation-maize intercropping (IRM), sole rice under dry cultivation (SR), and sole maize (SM). All straw was fully returned to the field after mechanical harvesting. Rice under dry cultivation-maize intercropping with a land-equivalent ratio of 1.05 (the average of three years values) increased the total yield by 8.63% compared to the monoculture system. The aggressivity (A), relative crowding coefficient (K), time-area-equivalent ratio (ATER), and competition ratio (CR) value were positive or ≥1, also indicating that the rice under dry cultivation-maize intercropping had a yield advantage of the overall intercropping system. This is because the intercropped maize root length density (RLD) increased by 33.94-102.84% in the 0-40 cm soil layer, which contributed to an increase in the soil porosity (SP) of 5.58-10.10% in the 0-30 cm soil layer, an increase in the mean weight diameter of soil aggregates (MWD) of 3.00-15.69%, an increase in the geometric mean diameter of soil aggregates (GMD) of 8.16-26.42%, a decrease in the soil bulk density (SBD) of 4.02-7.35%, and an increase in the soil organic matter content (SOM) of 0.60-4.35%. This increased the water permeability and aeration of the soil and facilitated the absorption of nutrients and water by the root system and their transportation above ground, and the plant nitrogen, phosphorus, and potassium accumulation in the intercropping system were significantly higher than that in monoculture treatment, further promoting the total yield of intercropping. This suggests that rice under a dry cultivation-maize intercropping system is feasible in Northeast China, mainly because it promotes belowground root growth, improves the soil environment, and increases the total yield of intercropping.

The Impact of Climate Change on Cropping Patterns in the Jurang Sate Hulu Irrigation Area

For many years, the active management of the Jurang Sate Hulu Irrigation Area has provided significant benefits to cropping patterns. However, the impacts of climate change on water availability and temperature variations present critical challenges to crop productivity. Therefore, an analysis of the effects of climate change is essential. The methods employed in the analysis of climate change include correlation and regression methods. This study uses nine variables of global climate change. The correlation method is applied to determine the extent of the influence of global climate variables, represented by Global Circulation Model (GCM) data, on rainfall and climate in the Jurang Sate Hulu Irrigation Area. The regression method is used to validate the prediction model for rainfall from 2024 to 2100. In the cropping pattern analysis, the Penman-Monteith method is used to calculate evapotranspiration, while the F.J. Mock method is used to calculate flow discharge. Based on the analysis, the global climate variables that most significantly influence rainfall in the Jurang Sate Hulu Irrigation Area are air temperature, wind speed, eastward wind, and surface temperature, with maximum correlation values of 0.551, 0.540, 0.589, and 0.625, respectively. In contrast, local climate variables have less influence, as they yield correlation values below 0.500. The regression analysis showed an average validation result for the selected model using two goodness-of-fit parameters: Root Mean Square Error (RMSE) of 124.371 and Nash-Sutcliffe Efficiency (NSE) of 0.403. The highest irrigation water requirement occurs during the third planting period, from 2051 to 2075, at 0.465 m³/s. The planned cropping pattern is paddy-paddy-second crops, with planting areas of 3,807 hectares for the period from 2024 to 2050, 3,595 hectares for the period from 2051 to 2075, and 3,383 hectares for the period from 2076 to 2100, with a total planting intensity of 300% during each period.

Improving crop type mapping by integrating LSTM with temporal random masking and pixel-set spatial information

Accurate and timely crop type classification is essential for effective agricultural monitoring, cropland management, and yield estimation. Unfortunately, the complicated temporal patterns of different crops, combined with gaps and noise in satellite observations caused by clouds and rain, restrict crop classification accuracy, particularly during early seasons with limited temporal information. Although deep learning-based methods have exhibited great potential for improving crop type mapping, insufficient and noisy training data may lead them to overlook more generalizable features and derive inferior classification performance. To address these challenges, we developed a Mask Pixel-set SpatioTemporal Integration Network (Mask-PSTIN), which integrates a temporal random masking technique and a novel PSTIN model. Temporal random masking augments the training data by selectively removing certain temporal information to improve data variability, enforcing the model to learn more generalized features. The PSTIN, comprising a pixel-set aggregation encoder (PSAE) and long short-term memory (LSTM) module, effectively captures comprehensive spatiotemporal features from time-series satellite images. The effectiveness of Mask-PSTIN was evaluated across three regions with different landscapes and cropping systems. Results demonstrated that the addition of PSAE in PSTIN significantly improved crop classification accuracy compared to a basic LSTM, with average overall accuracy (OA) increasing from 80.9% to 83.9%, and the mean F1-Score (mF1) rising from 0.781 to 0.818. Incorporating temporal random masking in training led to further improvements, increasing average OA and mF1 to 87.4% and 0.865, respectively. The Mask-PSTIN significantly outperformed traditional machine learning and deep learning methods (i.e., RF, SVM, Transformer, and CNN-LSTM) in crop type mapping across all three regions. Furthermore, Mask-PSTIN enabled earlier and more accurate crop type identification before or during their developing stages compared to machine learning models. Feature importance analysis based on the gradient backpropagation algorithm revealed that Mask-PSTIN effectively leveraged multi-temporal features, exhibiting broader attention across various time steps and capturing critical crop phenological characteristics. These results suggest that Mask-PSTIN is a promising approach for improving both post-harvest and early-season crop type classification, with potential applications in agricultural management and monitoring.

Enhancing agricultural sustainability with water and crop management strategies in modern irrigation and drainage networks

Improving global food security hinges on achieving sustainable agricultural production within independent irrigation and drainage units, considering the availability of sustainable water resources. This study investigated the potential for enhancing the sustainability of agricultural production in a modern irrigation and drainage network (TIDN) area and evaluated the network's performance under various strategies. These strategies included mulching, transitioning from traditional to drip irrigation, combining mulching with drip irrigation (IDM), and reducing the crop yield gap. Utilizing 2009–2018 data and the AquaCrop model, which was both calibrated and validated, the green and blue water footprints (GWF and BWF) of dominant crops in the region's cropping pattern were assessed. The crop cultivation was prioritized based on the total and unit unsustainable BWF. The performance of TIDN was evaluated using indicators of reliability, vulnerability, system deficiency, flexibility, and sustainability. The drip irrigation had the most significant impact on reducing BWF, while mulching was more effective in decreasing GWF. The adoption of IDM led to a total annual water savings of 382.4 m3 ha−1. The 10-year average reductions in BWF from May to August ranged from 1.7 to 3.1 MCM, with approximately 88–93 % of these savings attributed to decreased water consumption in rice fields. Mulch, drip, and IDM decreased the BWF by 3.3 %, 9.4 %, and 10.2 %, respectively, compared to current conditions. The study revealed that the expansion of rice cultivation under conventional flooding irrigation was incompatible with the sustainable blue water resources available, and replacing rice with wheat could reduce the unsustainable BWF by 95–100 %. Compared to current conditions, IDM improved network sustainability by 1.2 %, while closing the yield gap improved the indicator by 24 %. The findings suggest that combining infrastructural solutions, such as updating irrigation systems, with farm management solutions, such as reducing crop yield gaps and implementing mulching, can significantly enhance the sustainability of production in intensively agricultural areas.

Productivity and Profitability of Four Crops Based cropping Pattern in Jhenaidah District of Bangladesh

A field experiment was carried out at the farmers' field in the Kaliganj upazila for two consecutive years (2021-22, 2022-23). The experiment carried out in a multi-location testing site in the Jhenaidah district, under the Jashore region. The objective of the experiment was to enhance cropping intensity and productivity by incorporating T. Aus into the existing cropping pattern. The current cropping sequence consisted of T. Aman-Mustard-Mungbean, while the suggested cropping sequence included T. Aman- Mustard-Mungbean-T. Aus. The research findings showed that the rice equivalent yield (REY) in the suggested cropping pattern was 21 t ha-1, representing a 31.25% increased over the yield of existing pattern (16 t ha-1). The greater gross return (Tk. ha-1), gross margin (Tk. ha-1), and slightly higher marginal benefit cost ratio obtained from this four-crop-based cropping pattern suggest that the proposed pattern could be recommended for higher productivity and economic benefit in other parts of the Jashore region. Bangladesh J. Nuclear Agric, 38(1): 93-100, 2024

Transformation of Cropping Pattern through the Intervention of Potato Variety ACI Alu-10 (Valencia) to Ensure Food Security in Bangladesh

To transform the cropping pattern or add a new potato variety like ACI Alu-10 (Valencia) to the existing cropping pattern, it is essential to have adequate farmers’ knowledge and a favorable attitude towards that variety. In addition, the better performance of the variety in comparison to other market leader varieties is also necessary. Against such a backdrop, the present study determined farmers’ knowledge and attitude towards the potato variety (Valencia) and compare the selling price, yield, harvesting period, and cost of production of this variety with other potato varieties. Data were collected from randomly selected 139 farmers of Bogura and Joypurhat districts. A face-to-face interview followed by a structured questionnaire were used to collect data. The survey revealed that the Valencia users had higher knowledge and a more favorable attitude towards the variety than the non-Valencia users. The t-test showed a significant difference between Valencia users and non-Valencia users regarding the price, harvesting period, and cost of production, indicating that Valencia has a shorter harvesting period, higher selling price, and lower production cost. On the other hand, the result indicates that 62 days Valencia yield was almost near to the 74 days of other check potato varieties yield. By getting early and higher cash through selling Valencia, farmers can utilize the amount to improve their livelihood and solve problems. The findings may be helpful to policymakers in the decision to include Valencia in the current cropping pattern to increase potato production and food security in Bangladesh.

Change in leaf C:N:P stoichiometry and its correlations with soil available nutrients and dry matter yield in common vetch/oat intercropping under N fertilization

AbstractC, N, and P concentrations and stoichiometric ratios of the leaf are important for adaptive plant growth and nutrient utilization. However, our knowledge of how these traits change with N fertilization in intercropping systems remains limited. Hence, a 2‐year experiment was conducted with four cropping patterns, including two‐row common vetch (Vicia sativa L.) intercropping with one‐row oat (Avena sativa L.), one‐row common vetch intercropping with two‐row oat as well as sole oat and common vetch cropping with 0, 50, and 100 kg N/ha fertilization. Leaf total nitrogen (LTN) and phosphorus (LTP) concentrations and C:N:P stoichiometric ratios were measured and their linkages with soil nutrient availability were analysed. N fertilization significantly increased LTN, N:P, and C:P, while significantly decreasing LTP and C:N. Intercropping affected leaf nutrient concentrations and stoichiometric ratios, which were affected by N fertilization, basic soil fertility, and crop species. Intercropping and N fertilization affected soil nitrate nitrogen (SNN), available phosphorus (SAP) content, and dry matter (DM) yield. There were strong correlations between the leaf nutritional traits of oats and SNN, SAP, and DM, but few correlations were observed with common vetch. In conclusion, intercropping led to contrasting changes in leaf nutrient concentrations and stoichiometric ratios, which varied with N fertilization and crop species. We failed to reveal solid and direct effects of intercropping ratio on leaf nutritional traits. These findings contribute to a better understanding of crop nutritional traits and the link between leaves and soil in response to intercropping and N fertilization.

Estimation of Nutrient Uptake and Available Nutrient Status of Rabi Safflower Through Soil Test Crop Response in Rainfed Ecosystem

Background: Adoption of SSNM is directly affected by cost of fertilizer. Soil test crop response (STCR) concept attribute to contribution of soil and targeted yield level for fertilizer recommendation for a selected crop. This approach is also known as prescription based fertilizer recommendations. It is specific type of soil, climatic condition and specific location. Nutrient requirement is differ for different crops. The available soil nutrients efficient used and added to those available soil nutrients through fertilizers is different for different type of soil geography under a particular set of climatic conditions. Methods: A research experiment was carried out during rabi 2017-18, 2018-19 and 2019-20 at Research Farm of Agronomy, Dr. P.D.K.V, Akola (Maharashtra). Fertilizers were applied based on uptake pattern of crop, target yield levels and soil test values. The experiment was laid out in FRBD-Factorial randomized block design with two factors. Total 15 treatment combinations were formed which replication 4 times. Result: Significantly greater uptake of nitrogen (62.76, 74.67 and 81.89 kg ha-1), phosphorus (19.15, 24.32 and 29.38 kg ha-1), potassium (80.32, 92.14 and 99.18 kg ha-1), sulphur (18.46, 24.10 and 26.03 kg ha-1) and zinc (493.97, 571.01 and 620.91 g ha-1) recorded in treatment where crop supplied with farm yard manure @ 5 t ha-1 than rest of treatments during 2017-18, 2018-19 and 2019-20, respectively. A similar trend was observed in respect of soil nutrient status such as available N, P2O5, K2O, S and Zn. Application of fertilizers through soil test crop response equation with zinc sulphate @ 25 kg ha-1 and Sulphur @ 10 kg ha-1 registered maximum total uptake of nitrogen (66.89, 78.99 and 90.06 kg ha-1), phosphorus (20.78, 25.31 and 31.96 kg ha-1), potassium (86.05, 97.99 and 109.09 kg ha-1), sulphur (20.27, 26.39 and 29.80 kg ha-1) and zinc (537.78, 618.06 and 696.21 g ha-1) than rest of nutrient management treatments during three years of field experiment, respectively. The same trend was observed with respect to available N, P2O5, K2O, S and Zn under respective treatment during three years of experimentation.

Seeking a multi‐dimensional approach to understand agricultural commodity expansion in Asian tropics

AbstractAgricultural commodity expansion into natural and semi‐natural ecosystems in Asia is a multi‐dimensional sustainability challenge posing a threat to natural and human capital. At the symposium pertaining to agricultural commodity landscapes organized at the 59th meeting of the Association for Tropical Biology and Conservation, we aimed to identify key aspects that require further attention to address the negative impacts of commodity‐driven agricultural expansion in the Asian tropics. Using a combination of insights obtained both from participants' research and those that developed organically in the symposium, we identified five key themes: (1) Robust land use suitability assessments to determine the viability of agricultural expansion or other competing demands on productive land in given landscapes; (2) the need for plot‐level studies of soil biodiversity and ecological functions for commodity crops; (3) Irrigation for commodity crops with blue and green water and evaluating co‐dependent drivers and outcomes; (4) an improved understanding of local producer motivations and supply chains and (5) the analysis of co‐benefits, trade‐offs and synergies in agro‐commodity systems. These themes include the various steps involved in agricultural commodity expansion, right from land selection and crop patterns to aspects pertaining to the post‐harvest value chain. These themes are inter‐connected and span across multiple local and regional spatial scales in tropical Asia but hold relevance to agricultural landscapes elsewhere too. Immediate and sustained attention on these themes would secure multiple goals of sustainable land use, biodiversity conservation, climate change mitigation and human well‐being.