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Selecciona los temas de tu interés y recibe en tu correo las publicaciones más actuales
Menas Wuta Isaiah Nyagumbo (2021, [Artículo])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE DRY SPELLS RAINWATER HARVESTING CROP PRODUCTION TECHNOLOGY
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
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
Principles of field experimentation
Berhanu Tadesse Ertiro (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FIELD EXPERIMENTATION EXPERIMENTAL DESIGN RANDOMIZED BLOCK DESIGN LATTICE DESIGN PLANT BREEDING
Modelo de optimización de recursos para un distrito de riego
Model for the optimization of resources for an irrigation district
DAVID ORTEGA GAUCIN ENRIQUE MEJIA SAENZ ENRIQUE PALACIOS VELEZ LUIS RENDON PIMENTEL ADOLFO ANTENOR EXEBIO GARCIA (2008, [Artículo])
Mediante el uso de técnicas de programación lineal se desarrolló un modelo de optimización de recursos hídricos para el distrito de riego 005, localizado en Delicias, Chihuahua,México. El modelo planteado permitió estimar la superficie de riego y el patrón de cultivos óptimo para incrementar los beneficios netos de los productores. Se analizaron cuatro escenarios posibles, tomando en cuenta la disponibilidad de volúmenes clave en las fuentes de abastecimiento de agua, así como dos eficiencias de conducción de la red de canales. Los resultados indicaron que la superficie sembrada en el distrito fue de 70 459 ha. La superficie estimada por el modelo fue menor de 9643 ha con respecto a la superficie regable actualmente; por lo cual se concluye que es conveniente establecer estrategias para que, en situaciones próximas, la superficie excedente sea desincorporada del distrito de riego, o bien, reducir la concesión de agua con la finalidad de lograr la sustentabilidad de los módulos.
Using linear programming techniques, a model for optimizing water resources was developed for the Irrigation District 005, located in Delicias, Chihuahua, Mexico. The proposed model allowed estimation of the irrigation area and optimal cropping pattern needed to increase net benefits for growers. Four possible scenarios were analyzed, considering the availability of key volumes in water supply sources, as well as two conduction efficiencies for the network of irrigation channels. The results indicated that the area cultivated in the Irrigation District was 79 459 ha. The area estimated by the model was 9643 ha less than the area currently irrigation. It is thus concluded that it would be recommendable to establish strategies for withdrawing the excess area from the Irrigation District or for reducing water concessions in order to achieve sustainability of the modules.
Agricultura Productividad agrícola Programas de computación Programación lineal INGENIERÍA Y TECNOLOGÍA
Agricultural lime value chain efficiency for reducing soil acidity in Ethiopia
Moti Jaleta (2023, [Artículo])
Soil acidity is challenging agricultural production in Ethiopia. Above 43% of the farmland is under soil acidity problem and it leads to low crop yields and production losses. Ag-lime is widely considered as an effective remedy for amending soil acidity. This study assesses the current structure of ag-lime value chain and its functionality focusing on central parts of Ethiopia where lime is produced and channeled to acidity affected areas. The study uses Ethiopia as a case study and applies qualitative methods such as key informant interviews and focus group discussions to collect data from different actors in the ag-lime value chain. Key findings indicate that both public and private ag-lime producing factories are operating below their capacity. Due to limited enabling environments, the engagement of private sector in ag-lime value chain is minimal. In addition, farmers have a good awareness of soil acidity problem on their farms, and its causes and mitigation strategies in all regions. However, the adoption of ag-lime by smallholders was minimal. Overall, the current structure of the ag-lime value chain appears fragmented and needs improvement. Addressing soil acidity challenge through efficient ag-lime value chain could narrow lime supply-demand mismatches and increase widespread adoption by farmers to enhance crop productivity and food security in acidity-prone areas of the country.
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LIMES PRODUCTION COSTS VALUE CHAINS SOIL PH
Manish Kakraliya madhu choudhary Mahesh Gathala Parbodh Chander Sharma ML JAT (2024, [Artículo])
The future of South Asia’s major production system (rice–wheat rotation) is at stake due to continuously aggravating pressure on groundwater aquifers and other natural resources which will further intensify with climate change. Traditional practices, conventional tillage (CT) residue burning, and indiscriminate use of groundwater with flood irrigation are the major drivers of the non-sustainability of rice–wheat (RW) system in northwest (NW) India. For designing sustainable practices in intensive cereal systems, we conducted a study on bundled practices (zero tillage, residue mulch, precise irrigation, and mung bean integration) based on multi-indicator (system productivity, profitability, and efficiency of water, nitrogen, and energy) analysis in RW system. The study showed that bundling conservation agriculture (CA) practices with subsurface drip irrigation (SDI) saved ~70 and 45% (3-year mean) of irrigation water in rice and wheat, respectively, compared to farmers’ practice/CT practice (pooled data of Sc1 and Sc2; 1,035 and 318 mm ha−1). On a 3-year system basis, CA with SDI scenarios (mean of Sc5–Sc8) saved 35.4% irrigation water under RW systems compared to their respective CA with flood irrigation (FI) scenarios (mean of Sc3 and Sc4) during the investigation irrespective of residue management. CA with FI system increased the water productivity (WPi) and its use efficiency (WUE) by ~52 and 12.3% (3-year mean), whereas SDI improved by 221.2 and 39.2% compared to farmers practice (Sc1; 0.69 kg grain m−3 and 21.39 kg grain ha−1 cm−1), respectively. Based on the 3-year mean, CA with SDI (mean of Sc5–Sc8) recorded −2.5% rice yield, whereas wheat yield was +25% compared to farmers practice (Sc1; 5.44 and 3.79 Mg ha−1) and rice and wheat yield under CA with flood irrigation were increased by +7 and + 11%, compared to their respective CT practices. Mung bean integration in Sc7 and Sc8 contributed to ~26% in crop productivity and profitability compared to farmers’ practice (Sc1) as SDI facilitated advancing the sowing time by 1 week. On a system basis, CA with SDI improved energy use efficiency (EUE) by ~70% and partial factor productivity of N by 18.4% compared to CT practices. In the RW system of NW India, CA with SDI for precise water and N management proved to be a profitable solution to address the problems of groundwater, residue burning, sustainable intensification, and input (water and energy) use with the potential for replication in large areas in NW India.
Direct Seeded Rice Subsurface Drip Irrigation Economic Profitability Energy and Nitrogen Efficiency CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CONSERVATION AGRICULTURE RICE SUBSURFACE IRRIGATION IRRIGATION SYSTEMS WATER PRODUCTIVITY ECONOMIC VIABILITY ENERGY EFFICIENCY NITROGEN-USE EFFICIENCY