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.
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.
Rwanda has experienced exceptional economic growth since 2000 despite more than 60% of the predominately-agrarian population living on less than $1.25 a day. Approximately 76% of the country’s working population are engaged in agricultural production, which makes up about one-third of the national economy. Agriculture is also an important source of foreign exchange, making up about 63% of the value of Rwanda’s exports.
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.
This paper reviews the empirical literature on the determinants of farmer adoption of sustainable intensification technologies in maize agri-food systems of the Global South. The attributes of the technology and the dissemination institutions interact with farm/farmer-specific variables, leading to heterogeneous impacts, making the prediction of technology adoption challenging.
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.
This guide explains how to operationalize inclusion of women, Indigenous Peoples and other under-represented groups in multi-stakeholder forums (MSFs).
This paper assesses the relationships between women’s dietary diversity and various indicators of agricultural biodiversity in farms of the Hauts-Bassins, a cotton-growing region in rural western Burkina Faso. A sample of 579 farms representative of the region was surveyed at three different periods of the year. Using a qualitative 24-h dietary recall, we computed a women’s dietary diversity score (WDDS-10) based on ten food groups.
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.