Socioeconomic determinants of organic cotton adoption in Benin, West Africa

Organic cotton relies on ecological processes and the use of natural resources to sustain the production system, unlike conventional cotton, mainly characterized by massive utilization of synthesis chemicals. In West Africa, where rural livelihoods are particularly vulnerable, organic cotton is expected to contribute not only to poverty reduction but also to strengthen households’ resilience. The objective of this study was to assess institutional and socioeconomic factors determining farmers’ decisions to adopt organic cotton. For this purpose, we applied a probit model on empirical data collected from producers of the Centre and the Northern parts of Benin. Overall, we found that organic cotton adoption is mainly determined by farmers’ socioeconomic characteristics, the physical distance between farm and house, and contact with extension and advisory services. Organic farming is more attractive to women compared to conventional farming. This because such type of cotton farming enables women to hold a separate cotton farm and thus increase their economic independence, whereas with the conventional system they depend mainly on the farm of the (male) head of the household. Older, less educated and low-income farmers who express environmental concern are more likely to adopt organic cotton. Subsequently, organic cotton should be considered as a prospective policy option to reach the poor and strengthen their livelihoods conditions while contributing to preserve the environment and natural resources. Furthermore, farmers who have their farm near home are more likely to adopt organic farming than those who have the farm far from their home. It also came out that organic farmers have more contacts with advisory and extension services. Finally, the study noted that there is still a need to enhance the extension system by: (1) exploring, designing, and upgrading innovative pedagogic tools such as videos and mobile phone technology to foster learning; and (2) strengthening organic farmer’s organizations and the linkage with agricultural research organizations for technology development

The Fastest Flights in Nature: High-Speed Spore Discharge Mechanisms among Fungi

BACKGROUND: A variety of spore discharge processes have evolved among the fungi. Those with the longest ranges are powered by hydrostatic pressure and include "squirt guns" that are most common in the Ascomycota and Zygomycota. In these fungi, fluid-filled stalks that support single spores or spore-filled sporangia, or cells called asci that contain multiple spores, are pressurized by osmosis. Because spores are discharged at such high speeds, most of the information on launch processes from previous studies has been inferred from mathematical models and is subject to a number of errors. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we have used ultra-high-speed video cameras running at maximum frame rates of 250,000 fps to analyze the entire launch process in four species of fungi that grow on the dung of herbivores. For the first time we have direct measurements of launch speeds and empirical estimates of acceleration in these fungi. Launch speeds ranged from 2 to 25 m s(-1) and corresponding accelerations of 20,000 to 180,000 g propelled spores over distances of up to 2.5 meters. In addition, quantitative spectroscopic methods were used to identify the organic and inorganic osmolytes responsible for generating the turgor pressures that drive spore discharge. CONCLUSIONS/SIGNIFICANCE: The new video data allowed us to test different models for the effect of viscous drag and identify errors in the previous approaches to modeling spore motion. The spectroscopic data show that high speed spore discharge mechanisms in fungi are powered by the same levels of turgor pressure that are characteristic of fungal hyphae and do not require any special mechanisms of osmolyte accumulation

The Influence of Information Sources on Inter- and Intra-Firm Diffusion: Evidence from UK Farming

We study the effect of different information sources on diffusion between and within companies. Our model of economically optimising farmers replicates results from dual process persuasion theory, and predicts that inter-firm diffusion will be primarily affected by reliable, easily accessible information while intra-firm diffusion will be influenced by technical information. The results are tested on UK farming data. Consistent with our model, information from agents, suppliers, farmers, and agricultural magazines influences inter-firm adoption, from buyers influences intra-firm adoption, and from crop consultants, academics, government, and an industry body influences both

Spatial dependence in the adoption of organic drystock farming in ireland

This article analyses spatial dependence in the adoption of organic farming. Bayesian spatial Durbin probit models are applied to survey data of almost 600 Irish drystock farmers. The findings reveal that farmers located in close proximity exhibit similar choice behaviour. In addition, results show the importance of farmer interactions in adoption decisions as social norms and attitudes were identified to have spatial spill-over effects. Overall, the study highlights the importance of accounting for interdependence in farmers' decisions, which emerges as important in the formulation of agricultural policy

Spatial dependence in the adoption of organic drystock farming in ireland

This article analyses spatial dependence in the adoption of organic farming. Bayesian spatial Durbin probit models are applied to survey data of almost 600 Irish drystock farmers. The findings reveal that farmers located in close proximity exhibit similar choice behaviour. In addition, results show the importance of farmer interactions in adoption decisions as social norms and attitudes were identified to have spatial spill-over effects. Overall, the study highlights the importance of accounting for interdependence in farmers\u27 decisions, which emerges as important in the formulation of agricultural policy

A Food System Transformation Framework

Food systems are responsible for about one third of global greenhouse gas (GHG) emissions (Crippa et al., 2021), and the need to reduce these emissions is urgent. We developed a transformation framework outlining how climate change mitigation can be facilitated in the food system