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Balwinder-Singh Meha Jain (2023, [Artículo])
One way to meet growing food demand is to increase yields in regions that have large yield gaps, including smallholder systems. To do this, it is important to quantify yield gaps, their persistence, and their drivers at large spatio-temporal scales. Here we use microsatellite data to map field-level yields from 2014 to 2018 in Bihar, India and use these data to assess the magnitude, persistence, and drivers of yield gaps at the landscape scale. We find that overall yield gaps are large (33% of mean yields), but only 17% of yields are persistent across time. We find that sowing date, plot area, and weather are the factors that most explain variation in yield gaps across our study region, with earlier sowing associated with significantly higher yield values. Simulations suggest that if all farmers were able to adopt ideal management strategies, including earlier sowing and more irrigation use, yield gaps could be closed by up to 42%. These results highlight the ability of micro-satellite data to understand yield gaps and their drivers, and can be used to help identify ways to increase production in smallholder systems across the globe.
Yield Drivers Yield Mapping CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MICROSATELLITES YIELD GAP SMALLHOLDERS FOOD PRODUCTION YIELD INCREASES
Menas Wuta Isaiah Nyagumbo (2021, [Artículo])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE DRY SPELLS RAINWATER HARVESTING CROP PRODUCTION TECHNOLOGY
Sistemas de producción sostenibles y redes de innovación
Jelle Van Loon (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PRODUCTION SYSTEMS INNOVATION PRODUCTION SYSTEMS AGRIFOOD SYSTEMS
sridhar bhavani (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT VARIETY TRIALS PRODUCTION DATA
MLN disease diagnostics, surveillance, MLN disease-free seed production, and MLN disease management
Suresh L.M. (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISEASES DISEASE MANAGEMENT SEED PRODUCTION MAIZE NECROSIS YIELD LOSSES ECONOMIC IMPACT SURVEILLANCE SYSTEMS TRAINING
Suresh L.M. (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE DISEASES SEED PRODUCTION MONITORING SYSTEMS TRAINING
Nurul Islam (1995, [Libro])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FOOD POLICIES FOOD PRODUCTION FOOD SUPPLY FORECASTING
Remote sensing of quality traits in cereal and arable production systems: A review
Zhenhai Li xiuliang jin Gerald Blasch James Taylor (2024, [Artículo])
Cereal is an essential source of calories and protein for the global population. Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers, grading harvest and categorised storage for enterprises, future trading prices, and policy planning. The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits. Many studies have also proposed models and methods for predicting such traits based on multi-platform remote sensing data. In this paper, the key quality traits that are of interest to producers and consumers are introduced. The literature related to grain quality prediction was analyzed in detail, and a review was conducted on remote sensing platforms, commonly used methods, potential gaps, and future trends in crop quality prediction. This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.
Quality Traits Grain Protein CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA REMOTE SENSING QUALITY GRAIN PROTEINS CEREALS PRODUCTION SYSTEMS
Carlo Montes Anton Urfels Eunjin Han Balwinder-Singh (2023, [Artículo])
Rainy Season TIMESAT APSIM Agricultural Production Systems Simulator Climate Adaptation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RICE WHEAT MONSOONS WET SEASON CROP MODELLING CLIMATE CHANGE ADAPTATION
Brendan Brown Pragya Timsina Emma Karki (2023, [Artículo])
While crop diversification has many benefits and is a stated government objective across the Eastern Gangetic Plains (EGP) of South Asia, the complexity of assessment has led to a rather limited understanding on the progress towards, and status of, smallholder crop diversification. Most studies focus on specific commodities or report as part of a singular index, use outdated secondary data, or implement highly localized studies, leading to broad generalisations and a lack of regional comparison. We collected representative primary data with more than 5000 households in 55 communities in Eastern Nepal, West Bengal (India) and Northwest Bangladesh to explore seasonally based diversification experiences and applied novel metrics to understand the nuanced status of farm diversification. While 66 crops were commercially grown across the region, only five crops and three crop families were widely grown (Poaceae, Malvaceae, and Brassicaceae). Non-cereal diversification across the region was limited (1.5 crops per household), though regional differentiation were evident particularly relating to livestock and off-farm activities, highlighting the importance of cross border studies. In terms of farmer's largest commercial plots, 20% of systems contained only rice, and 57% contained only rice/wheat/maize, with substantial regional diversity present. This raises concerns regarding the extent of commercially oriented high value and non-cereal diversification, alongside opportunities for diversification in the under-diversified pre-monsoon and monsoon seasons. Future promotional efforts may need to focus particularly on legumes to ensure the future sustainability and viability of farming systems.
Agricultural Production Systems Farming Systems Change CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRODUCTION CROPPING SYSTEMS DIVERSIFICATION FARMING SYSTEMS SUSTAINABLE INTENSIFICATION