122418 research outputs found
Sort by
Validating a novel genetic technology for hybrid maize seed production under management practices associated with resource-poor farmers in Zimbabwe
Get PDFUnderstanding the performance of new genetic technologies in farmers' real-world realities, especially those relevant to resource-poor farmers, is often overlooked but is essential to ensure equitable benefits. A new genetic technology was developed to simplify hybrid maize seed production in sub-Saharan Africa, thereby improving farmers' access to high-quality hybrid seed. Hybrids produced with this technology segregate 50:50 for pollen-producing and non-pollen producing and are designated 50% non-pollen producing (FNP). FNP maize has higher yields in low-input environments. As recycling hybrid maize seed remains a common practice in Zimbabwe, including among resource-poor households, it is important to understand the impact of recycling FNP seed on the yield gains from the FNP technology. The potential impact of recycling FNP hybrid seed was assessed by testing three seed recycling scenarios on-station and on-farm. The extent of hybrid seed recycling and the types of households recycling hybrid maize seed over a 3-year period were also investigated. Hybrid maize seed recycling was associated with resource-poor farmers, although it was not continually practiced across years. Yield gains associated with FNP were retained under recycling practices, albeit reduced. The greatest yield benefit was when seed from only non-pollen-producing plants was used. Yield gains were associated with longer ears and more kernels per ear. While recycling hybrid maize seed reduces potential yields due to inbreeding depression, in the years when farmers cannot afford to plant hybrid maize only, recycling non-pollen-producing hybrid maize seed conferred a yield benefit of 116 kg ha−1
Contribution of local knowledge in cocoa (Theobroma cacao L.) to the well-being of cocoa families in Colombia: A response from the relationship
Get PDFThe concept of well-being of rural families is part of a theory under construction in which new theoretical elements are constantly being incorporated. This research aims to determine the influence of farmers' knowledge on the well being of cocoa growing families in the departments of Santander, Huila, Meta and Caquetá, Colombia. Four categories of farmers were identified with different levels of knowledge in the management of cocoa cultivation obtained through a cluster analysis. The well-being of cocoa farmers, understood as the balance in the capital endowment of rural households, was obtained through the application of a semi-structured interview with 49 variables of human, cultural, social, political, natural, built, and financial capitals. The results show that cocoa knowledge is heterogeneous in the study area, with a slight improvement towards harvesting, post-harvest and transformation links. There is a positive relationship between cocoa knowledge and the well-being of cocoa farming families. Thus, producers with greater integral knowledge, with emphasis on post-harvest and bean transformation links, showed greater well-being. The Random Forest analysis identified that human capital (political, social, human, and cultural) made the greatest contribution to well-being. The findings show that cocoa knowledge contributes to the well-being of rural households to the extent that it favors vertical relationships (linkages with local governments) and horizontal relationships of producers (participation of association managers, sharing knowledge with friends, neighbors and partners, and cocoa training)
Prevention and management of plant protection product transfers within the environment: A review
No full textThe intensification of agriculture has promoted the simplification and specialization of agroecosystems, resulting in negative impacts such as decreasing landscape heterogeneity and increasing use of plant protection products (PPP), with the acceleration of PPP transfers to environmental compartments and loss in biodiversity. In this context, the present work reviews the various levers for action promoting the prevention and management of these transfers in the environment and the available modelling tools. Two main categories of levers were identified: (1) better control of the application, including the reduction of doses and of PPP dispersion during application thanks to appropriate equipment and settings, PPP formulations and consideration of meteorological conditions; (2) reduction of post-application transfers at plot scales (soil cover, low tillage, organic matter management, remediation etc. and at landscape scales using either dry (grassed strips, forest, hedgerows and ditches) or wet (ponds, mangroves and stormwater basins) buffer zones. The management of PPP residues leftover in the spray tanks (biobeds) also represents a lever for limiting point-source PPP pollution. Numerous models have been developed to simulate the transfers of PPPs at plot scales. They are scarce for landscape scales. A few are used for regulatory risk assessment. These models could still be improved, for example, if current agricultural practices (e.g. agro-ecological practices and biopesticides), and their effect on PPP transfers were better described. If operated alone, none of the levers guarantee a zero risk of PPP transfer. However, if levers are applied in a combined manner, PPP transfers could be more easily limited (agricultural practices, landscape organization etc.)
Initiatives and policies for the agroecological transition of food systems: Lessons from ten countries of the Global South. Final report of TAFS project step 1 (national policy survey)
Get PDFThe report analyses the processes of building initiatives and public policies for the Agro-Ecological Transition (AET) of food systems in ten countries of the South. The results come from the first stage of the TAFS project (Agroecological transitions for sustainable food systems: arguments for public policies). The hypotheses were, on the one hand, the weight of political regimes and international cooperation in the translation and emergence of AET and, on the other hand, the fact that the dominant conventional production model is the biggest obstacle to the development of AET. The study consisted of applying the same framework to analyse the processes of building TAE on a national scale, using cross-references and methods from the sociology of public action and political sociology. The results show a diversity of conceptions of AET, of actors, of construction processes and, at the same time, of results in terms of instruments and their implementation
Gaps and overlaps between sustainability science and the environmental humanities
No full textGiven the wicked environmental and sustainability challenges we face today, the need for a cross-disciplinary, science–society approach is increasingly undisputed. Yet, is the development of the distinct research fields of sustainability science (SustSci) and the environmental humanities (EnvHum) another example of academic silos? In this study, we conducted a comprehensive science mapping of the literature to explore the overlap or compartmentalization of these fields. Standardized search strings submitted in the Web of Science allowed us to gather a total of 2076 publications, including 1678 for SustSci and 398 for EnvHum, from which we explored the social, intellectual and conceptual structures of the two fields. The results indicated that SustSci and EnvHum are nourished by distinct research communities (distinct authors and journals) and rely on different epistemological legacies. In addition, results showed that the two research fields focus on similar challenges (e.g. climate change and biodiversity decline), but with contrasting approaches. SustSci combines natural and social sciences to address sustainability as a systemic problem, while EnvHum combines social sciences and the humanities, approaching it as a power and values issue. Nonetheless, a comprehensive analysis suggested that they also share key aims: bridging the nature–culture divide, transforming socio-political relationships, and taking into account values, affects and imaginaries. In light of these results, we finally discuss the opportunities and challenges for mutual enrichment between SustSci and EnvHum around these three shared goals, which might foster a strengthened response to the crises we face
Early selection and genetic analysis of susceptibility to tapping panel dryness by applying an intense harvesting system to a segregating population in Hevea brasiliensis
Get PDFTapping Panel Dryness (TPD) is a physiological syndrome affecting natural rubber production in Hevea brasiliensis that is thought to be exacerbated by climate change stress. TPD is associated with high latex viscosity and agglutination of rubber particles. Although many studies have been carried out on the physiological and molecular mechanisms associated with TPD, little has been done in the way of genetic improvement. Intensive harvesting systems with high tapping frequency and ethephon stimulation of rubber trees are known to induce early TPD occurrence. A harvesting system with daily tapping and monthly ethephon stimulation was applied for one year to a segregating population of 189 individuals obtained from a cross between the TPD-susceptible clone PB 260 and the TPD-tolerant clone SP 217. This treatment induced a dramatic increase in dry cut length after six months for 26 % of the genotypes. Heritability also peaked at 88 % four months after treatment. Of the seven quantitative trait loci identified for the dry cut length, three were uniquely detected after application of the intensive harvesting system, and two quantitative trait loci were only observed after opening of trees under a standard harvesting system. Several genes underlying quantitative trait loci revealed functions previously identified through transcriptomic analyses. These results suggest a complex genetic basis of TPD
Evaluation of geographical distortions in language models
Get PDFLanguage models now constitute essential tools for improving efficiency for many professional tasks such as writing, coding, or learning. For this reason, it is imperative to identify inherent biases. In the field of Natural Language Processing, five sources of bias are well-identified: data, annotation, representation, models, and research design. This study focuses on biases related to geographical knowledge. We explore the connection between geography and language models by highlighting their tendency to misrepresent spatial information, thus leading to distortions in the representation of geographical distances. This study introduces four indicators to assess these distortions, by comparing geographical and semantic distances. Experiments are conducted from these four indicators with eight widely used language models and their implementations are available on github (https://github.com/tetis-nlp/geographical-biases-in-llms). Results underscore the critical necessity of inspecting and rectifying spatial biases in language models to ensure accurate and equitable representations
Evaluating the feasibility of automating dataset retrieval for biodiversity monitoring
Get PDFAim: Effective management strategies for conserving biodiversity and mitigating the impacts of global change rely on access to comprehensive and up-to-date biodiversity data. However, manual search, retrieval, evaluation, and integration of this information into databases present a significant challenge to keeping pace with the rapid influx of large amounts of data, hindering its utility in contemporary decision-making processes. Automating these tasks through advanced algorithms holds immense potential to revolutionize biodiversity monitoring. Innovation: In this study, we investigate the potential for automating the retrieval and evaluation of biodiversity data from Dryad and Zenodo repositories. We have designed an evaluation system based on various criteria, including the type of data provided and its spatio-temporal range, and applied it to manually assess the relevance for biodiversity monitoring of datasets retrieved through an application programming interface (API). We evaluated a supervised classification to identify potentially relevant datasets and investigate the feasibility of automatically ranking the relevance. Additionally, we applied the same appraoch on a scientific literature source, using data from Semantic Scholar for reference. Our evaluation centers on the database utilized by a national biodiversity monitoring system in Quebec, Canada. Main conclusions: We retrieved 89 (55%) relevant datasets for our database, showing the value of automated dataset search in repositories. Additionally, we find that scientific publication sources offer broader temporal coverage and can serve as conduits guiding researchers toward other valuable data sources. Our automated classification system showed moderate performance in detecting relevant datasets (with an F-score up to 0.68) and signs of overfitting, emphasizing the need for further refinement. A key challenge identified in our manual evaluation is the scarcity and uneven distribution of metadata in the texts, especially pertaining to spatial and temporal extents. Our evaluative framework, based on predefined criteria, can be adopted by automated algorithms for streamlined prioritization, and we make our manually evaluated data publicly available, serving as a benchmark for improving classification techniques
A conceptual framework for the contextualization of crop model applications and outputs in participatory research
Get PDFContextualization of generic scientific knowledge to context-specific farmer knowledge is a necessary step in farmers' innovation process, and it can be achieved using crop and farm models. This work explores the possibility to simulate a large number of scenarios based on farmers' descriptions of their environment and practices in order to contextualize the discussion for each participating farmer. It presents a novel framework consisting of six actions divided in three phases, namely, phase I—reaching out to the farmers' world: (i) project initialization; (ii) determination of the agronomical question anchored in farmers' context; (iii) characterization of the environment, the management options, and the indicators to describe the system under consideration; phase II—within researchers' world: (iv) crop model parametrization; (v) translation of model outputs into farmer-proposed indicators; and phase III—back to farmers' world: (vi) exploration of contextualized management options with farmers. Two communication tools are created during the process, one containing the results of simulations to feed the discussions and a second one to create a record of it. The usefulness of the framework is exemplified with the exploration of soil fertility management with manure and compost applications for sorghum production in the smallholder context of Sudano-Sahelian Burkina Faso. The application of the framework with 15 farmers provided evidence of farmers' and agronomists' understanding of options to improve cropping system performance with better organic amendment management. This approach allowed farmers to identify and relate to the scenarios simulated, but highlighted interrogations on how to adapt the crop model outputs to particular situations. Though applied on issues related to tactical change at field level, the framework offers the opportunity to explore broader issues with farmers, such as farm reconfiguration