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.
We present a model for research and development (R&D) investment in food innovations based on new plant engineering techniques (NPETs) and traditional hybridization methods. The framework combines uncertain and costly food innovation with consumers' willingness to pay (WTP) for the new food. The framework is applied with elicited WTP of French and US consumers for new improved apples. NPETs may be socially beneficial under full information and when the probability of success under NPETs is relatively high. Otherwise, the traditional hybridization is socially optimal.
Agricultural production systems are a composite of philosophy, adoptability, and careful analysis of risks and rewards. The two dominant typologies include conventional and organics, while biotechnology (GM) and Integrated Pest Management (IPM) represent situational modifiers. We conducted a systematic review to weigh the economic merits—as well as intangibles through an economic lens—of each standalone system and system plus modifier, where applicable. Overall, 17,485 articles were found between ScienceDirect and Google Scholar, with 213 initially screened based on putative relevance.
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%.
CONTEXT: Adoption and diffusion of digital farming technologies are expected to help transform current agricultural systems towards sustainability. To enable and steer transformation we need to understand the mechanisms of adoption and diffusion holistically. Our current understanding is mainly informed by empirical farm-level adoption studies and by agent-based models simulating systemic diffusion mechanisms. These two approaches are weakly integrated.
Scaling is a ubiquitous concept in agricultural research in the global south as donors require their research grantees to prove that their results can be scaled to impact upon the livelihoods of a large number of beneficiaries. Recent studies on scaling have brought critical perspectives to the rather technocratic tendencies in the agricultural innovations scaling literature.
La crise économique et sanitaire due à la Covid-19 interpelle les trajectoires de reconfiguration des systèmes alimentaires en République du Congo. Elle questionne la capacité des mesures de régulation prises par les pouvoirs publics et des stratégies d’adaptation des acteurs à induire des inflexions dans la gouvernance structurelle du système alimentaire du pays. L’article analyse les stratégies d’adaptation à la crise en mobilisant des données secondaires et des expériences d’accompagnement de politiques publiques agricoles et alimentaires conduites par les auteurs.