Participatory action research (PAR) has been around for years, and can add significant value to agriculture research for development projects. The use of PAR in climate-smart villages (CSVs) is no different. This review aimed to assess the impact that PAR approaches had on the adoption of CSA practices and technologies, with an emphasis on gender and social inclusion. Through a portfolio review, interviews with regional CSV teams, and surveys sent to local partners, this report demonstrates the benefit of PAR use in the implementation of the CSV approach.
Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks.
The aim of this survey is to identify and characterize new products in plant biotechnology since 2015, especially in relation to the advent of New Breeding Techniques (NBTs) such as gene editing based on the CRISPR-Cas system. Transgenic (gene transfer or gene silencing) and gene edited traits which are approved or marketed in at least one country, or which have a non-regulated status in the USA, are collected, as well as related patents worldwide. In addition, to shed light on potential innovation for Africa, field trials on the continent are examined.
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.
This study established physicochemical and sensory characteristics of virgin olive oils (VOOs) and linked them to consumers’ liking using external preference mapping. We used five Tunisian and two foreign VOO varieties produced by two processing systems: discontinuous (sp) and continuous three-phase decanter (3p). The samples were analyzed and evaluated by a panel of 274 consumers. The external preference mapping revealed five VOO clusters with a consumer preference scores rating from 40% to 65%.