The overall objective of the technical workshop was to present the guidelines on AIS and EAS assessments, the results at country level and to design and develop a framework of indicators to complement those assessments. Specific objectives were to:
Esta obra está enmarcada en el Plan de Acción 2018-2021 de la Facultad de Ciencias Agrarias, en el reto “Aportar al Sistema Nacional de Innovación Agropecuaria integrando la investigación y la extensión”, el cual tiene como propósito interconectar la investigación, la extensión y la innovación para mejorar el relacionamiento con el sector productivo, fortalecer las alianzas público-privadas nacionales e internacionales y las redes del conocimiento y gestionar la innovación, por medio de la creación del Centro de Innovación Agropecuaria, con el propósito de mejorar los procesos de gestión de
To determine whether a farmer’s accessibility predicts the delivery of extension services, this study used banana Xanthomonas wilt (BXW) disease-management advisory as a typical case with which to collect extension-delivery information from 690 farmers, distinguished by their respective accessibility. Cost–distance analysis was applied to define each farmer’s accessibility. The results revealed that a farmer’s accessibility does not predict extension delivery to that farmer in all forms of the examined extension parameters.
The national assessment of the agricultural innovation system (AIS) in Malawi was conducted using a framework of four types of analyses: functional, structural, capacity and enabling environment analysis. The approach included five case studies that addressed three methods including the use of indigenous methods for fall armyworm (FAW) control in Farmer Field Schools (FFS), livestock transfer programs, and a horticulture marketing innovation platform in Mzimba, Ntchisi, Balaka, and Thyolo districts.
The impact of global warming on crop growth periods and yields has been evaluated by using crop models, which need to provide various kinds of input datasets and estimate numerous parameters before simulation. Direct studies on the changes of climatic factors on the observed crop growth and yield could provide a more simple and intuitive way for assessing the impact of climate change on crop production.
This work examined the determinants of the adoption of improved Irish potato technologies by farmers in three divisions of the Western Region of Cameroon. Data were collected from 170 farmers from 14 villages in our study area using a mixed-method approach—structured questionnaires, focus group discussion, key informant interviews, and participatory observations with individual farmers and farmers belonging to cooperative and common initiative groups. The study employed descriptive statistics and regression analysis to assess the adoption status of farmers and its determinants.
Soil texture is a key soil property influencing many agronomic practices including fertilization and liming. Therefore, an accurate estimation of soil texture is essential for adopting sustainable soil management practices. In this study, we used different machine learning algorithms trained on vis–NIR spectra from existing soil spectral libraries (ICRAF and LUCAS) to predict soil textural fractions (sand–silt–clay %). In addition, we predicted the soil textural groups (G1: Fine, G2: Medium, and G3: Coarse) using routine chemical characteristics as auxiliary.
Recent Society 5.0 efforts by the Government of Japan are aimed at establishing a sustainable human-centered society by combining new technologies such as sensor networks, edge computing, Internet of Things (IoT) ecosystems, artificial intelligence (AI), big data, and robotics. Many research works have been carried out with an increasing emphasis on the fundamentals of wireless sensor networks (WSN) for different applications; namely precision agriculture, environment, medical care, security, and surveillance.
Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield loss worldwide. Remote sensing can detect and map the presence of weeds in various spectral, spatial, and temporal resolutions. This review aims to show the current and future trends of UAV applications in weed detection in the crop field.
Rice is a primary food for more than three billion people worldwide and cultivated on about 12% of the world’s arable land. However, more than 88% production is observed in Asian countries, including Pakistan. Due to higher population growth and recent climate change scenarios, it is crucial to get timely and accurate rice yield estimates and production forecast of the growing season for governments, planners, and decision makers in formulating policies regarding import/export in the event of shortfall and/or surplus.