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38 resultados, página 3 de 4

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

Avances en Agricultura Sustentable : Resultados de plataformas de investigación Hub Pacífico Norte 2010-2021

Simon Fonteyne Nele Verhulst (2022, [Libro])

Esta edición presenta los resultados de la red de plataformas en el Hub Pacífico Norte, misma que resulta de la colaboración entre el CIMMYT; el Patronato para la Investigación y Experimentación Agrícola del Estado de Sonora A.C. (PIEAES); el Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP); la Asociación de Agricultores del Río Sinaloa Poniente (AARSP); la Asociación de Agricultores del Río Fuerte Sur (AARFS); la Asociación de Agricultores del Río Culiacán (AARC); la Universidad Autónoma de Sinaloa (UAS); Servicios Agrofinancieros del Norte S.A. de C.V. (SAFINSA); el Club de Labranza de Conservación del Valle del Évora; Granera del Noroeste S.A. de C.V; y el Instituto de Ciencias Agrícolas de la Universidad Autónoma de Baja California (ICA-UABC). Los lectores podrán encontrar en este libro los resultados de las plataformas con más tiempo de operación, en donde ya se han podido generar suficientes datos para sacar conclusiones basadas en evidencias sólidas. Esperamos que el libro pueda servir de inspiración a los productores para que busquen que sus actividades en el campo sean más productivas, rentables y sustentables.

Plataformas de Investigación Maíz Amarillo Pulgón Áreas de extensión Módulos demostrativos Autosuficiencia Alimentaria Uso de Insumos Ganancias para el Productor Nodos de Innovación CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURA DE CONSERVACIÓN COSTOS DE PRODUCCIÓN EUTROFIZACIÓN MONOCULTIVO DEGRADACIÓN DEL SUELO CONTAMINACIÓN PLAGUICIDAS CAMBIO CLIMÁTICO PLATAFORMAS DE INNOVACIÓN EXTENSIÓN AGRÍCOLA AUTOSUFICIENCIA INSUMOS AGRÍCOLAS CONSERVATION AGRICULTURE PRODUCTION COSTS EUTROPHICATION MONOCULTURE SOIL DEGRADATION CONTAMINATION PESTICIDES CLIMATE CHANGE INNOVATION PLATFORMS AGRICULTURAL EXTENSION SELF-SUFFICIENCY FARM INPUTS

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