Dynamics of Maize Consumption and its Implication in Maize Technology Demand in Nepal

Shriniwas Gautam Dyutiman Choudhary (2018, [Capítulo de libro])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE TECHNOLOGY VARIETIES

Farmers’ perspectives as determinants for adoption of conservation agriculture practices in Indo-Gangetic Plains of India

Ajay Kumar Mishra ML JAT (2022, [Artículo])

Understanding the farmer's perspective has traditionally been critical to influencing the adoption and out-scaling of CA-based climate-resilient practices. The objective of this study was to investigate the biophysical, socio-economic, and technical constraints in the adoption of CA by farmers in the Western- and Eastern-IGP, i.e., Karnal, Haryana, and Samastipur, Bihar, respectively. A pre-tested structured questionnaire was administered to 50 households practicing CA in Western- and Eastern-IGP. Smallholder farmers (<2 ha of landholding) in Karnal are 10% and Samastipur 66%. About 46% and 8% of households test soil periodically in Karnal and Samastipur, respectively. Results of PCA suggest economic profitability and soil health as core components from the farmer's motivational perspective in Karnal and Samastipur, respectively. Promotion and scaling up of CA technologies should be targeted per site-specific requirements, emphasizing biophysical resource availability, socio-economic constraints, and future impacts of such technology.

Smallholder Farmers Agents of Change Technology Diffusion Climate-Smart Practices CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SMALLHOLDERS SOCIAL STRUCTURE IRRIGATION MANAGEMENT TECHNOLOGY CLIMATE-SMART AGRICULTURE CONSERVATION AGRICULTURE

Sustainable maize intensification through site-specific nutrient management advice: Experimental evidence from Nigeria

Miet Maertens Oyakhilomen Oyinbo Tahirou Abdoulaye Jordan Chamberlin (2023, [Artículo])

There is growing evidence on the impacts of site-specific nutrient management (SSNM) from Asia. The evidence for Sub-Saharan Africa (SSA), where SSNM developments are more recent and where conditions concerning soil fertility and fertilizer use differ importantly from those in Asia, is extremely scarce. We evaluate a SSNM advisory tool that allows extension agents to generate fertilizer recommendations tailored to the specific situation of an individual farmer’s field, using a three-year randomized controlled trial with 792 smallholder farmers in the maize belt of northern Nigeria. Two treatment arms were implemented: T1 and T2 both provide SSNM information on nutrient use and management, but T2 provides additional information on maize price distributions and the associated variability of expected returns to fertilizer use. We estimate average and heterogenous intent-to-treat effects on agronomic, economic and environmental plot-level outcomes. We find that T1 and T2 lead to substantial increases (up to 116%) in the adoption of good fertilizer management practices and T2 leads to incremental increases (up to 18%) in nutrient application rates, yields and revenues. Both treatments improve low levels of nutrient use efficiency and reduce high levels of greenhouse gas emission intensity, after two years of treatment. Our findings underscore the possibility of a more gradual and sustainable intensification of smallholder agriculture in SSA, as compared with the Asian Green Revolution, through increased fertilizer use accompanied by improved fertilizer management.

Randomized Controlled Trial CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TECHNOLOGY ADOPTION AGRICULTURAL EXTENSION GREEN REVOLUTION FERTILIZERS GREENHOUSE GAS EMISSIONS

Distance learning for farmers: Experience during the pandemic

Andrea Gardeazabal (2023, [Documento de trabajo])

In response to the COVID-19 pandemic's disruption of farmer training—a crucial component for enhancing the resilience and livelihoods of smallholder farmers—CIMMYT innovated educational solutions to sustain capacity building in agri-food systems. Addressing the challenges of limited mobile device access, poor internet connectivity, and digital illiteracy, CIMMYT implemented two pilot projects in Mexico. These projects facilitated distance learning for adult farmers in rural areas, employing both internet-based and non-internet methods. The non-internet approach utilized traditional media like print, while the internet-based approach leveraged WhatsApp for educational content delivery. Building on these experiences, CIMMYT expanded its offerings by creating micro -courses delivered through WhatsApp, hosted on the Co-LAB's new Learning Network platform, specifically targeting farmers. This paper delves into the various strategies, methods, and techniques adopted, documenting the learning outcomes, results, and key conclusions drawn from these innovative training initiatives.

Distance Learning Digital Inclusion Innovative Training CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISTANCE EDUCATION CAPACITY DEVELOPMENT METHODS COMMUNICATION TECHNOLOGY

Genetic diversity and genome-wide association study for the phenology response of winter wheats of North America, Western Asia, and Europe

Susanne Dreisigacker Marta Lopes Miguel Sanchez-Garcia (2023, [Artículo])

Winter Wheat Panel Precision Phenology Effective Markers CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC DIVERSITY (AS RESOURCE) GENOME-WIDE ASSOCIATION STUDIES PHENOLOGY PHOTOPERIODICITY POPULATION STRUCTURE VERNALIZATION WINTER WHEAT

Radiative transfer model inversion using high-resolution hyperspectral airborne imagery – Retrieving maize LAI to access biomass and grain yield

Ahmed Kayad Francelino Rodrigues Marco Sozzi Francesco Pirotti Francesco Marinello Urs Schulthess Bruno Gerard Marie Weiss (2022, [Artículo])

PROSAIL Vegetation Indices Field Variability Digital Farming CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PRECISION AGRICULTURE MAIZE GRAIN YIELD BIOMASS VEGETATION VEGETATION INDEX

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Teacher training in the state of Chihuahua: Between the health challenge and teacher resilience

Evangelina Cervantes Holguín Pavel Roel Gutiérrez Sandoval Cely Celene Ronquillo Chávez (2023, [Artículo, Artículo])

The article proposes to recover the response of the Teacher Training and Updating Institutions in the state of Chihuahua regarding the various challenges imposed by the Coronavirus Disease (COVID-19). The qualitative exercise analyzes the experience of 10 institutions based on the voice of their students, teachers, and principals regarding changes in academic, administrative, and organizational processes. It is concluded that the pandemic has affected each institution in different ways and with diverse intensity. Despite the achievements, the experience analyzed reveals the relative success of the using virtual platforms in the face of three basic conditions: connectivity, technological competencies, and socio-emotional skills of the teaching staff. It highlights the importance of implementing tutoring, resilience, or awareness actions of teachers and students' needs, feelings, and sufferings. It is opportune to recover the experiences of other institutions and to question especially students, thesis students and graduates.

Acceso a la educación Aprendizaje en línea Educación a distancia Formación de docentes Tecnología educacional HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Access to education online learning distance education teacher education educational technology

The generation challenge programme platform: Semantic standards and workbench for crop science

Richard Bruskiewich Guy Davenport Mathieu Rouard Reinhard Simon Samart Wanchana Trushar Shah Victor Jun Ulat Andrew Farmer Pankaj Jaiswal Mark Wilkinson David Marshall Alyssa Collins (2008, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP IMPROVEMENT GENETIC RESOURCES PLANT BREEDING BIODIVERSITY COMPUTER APPLICATIONS DIGITAL TECHNOLOGY DATA PROCESSING

Risk aversion, impatience, and adoption of conservation agriculture practices among smallholders in Zambia

Hambulo Ngoma João Vasco Silva Frédéric Baudron Isaiah Nyagumbo Christian Thierfelder (2024, [Artículo])

Sustainable agricultural practices such as conservation agriculture have been promoted in southern Africa for nearly three decades, but their adoption remains low. It is of policy interest to unpack behavioural drivers of adoption to understand why adoption remains lower than anticipated. This paper assesses the effects of risk aversion and impatience on the extent and intensity of the adoption of conservation agriculture using panel data collected from 646 households in 2021 and 2022 in Zambia. We find that 12% and 18% of the smallholders were impatient and risk averse, respectively. There are two main empirical findings based on panel data Probit and Tobit models. First, on the extensive margin, being impatient is correlated with a decreased likelihood of adopting combined minimum-tillage (MT) and rotation by 2.9 percentage points and being risk averse is associated with a decreased propensity of adopting combined minimum tillage (MT) and mulching by 3.2 percentage points. Being risk averse is correlated with a decreased chance of adopting basins by 2.8 percentage points. Second, on the intensive margin, impatience and risk aversion are significantly correlated with reduced adoption intensity of basins, ripping, minimum tillage (MT), and combined MT and rotation by 0.02–0.22 ha. These findings imply a need to embed risk management (e.g., through crop yield insurance) in the scaling of sustainable agricultural practices to incentivise adoption. This can help to nudge initial adoption and to protect farmers from yield penalties that are common in experimentation stages.

Risk and Time Preferences CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TECHNOLOGY ADOPTION RISK SUSTAINABLE INTENSIFICATION SMALLHOLDERS