Controlled Environment Agriculture (CEA) is the production of plants, fish, insects, or animals inside structures such as greenhouses, vertical farms, and growth chambers, in which environmental parameters such as humidity, light, temperature and CO2 can be controlled to create optimal growing conditions.
The CGIAR is the leading global agriculture research institution working towards creating sustainable agricultural practices a reality through research and innovation. The CGIAR 2030
Agricultural innovation has played a critical role in the economic transformation of developing East Asian countries over the past half century. This transformation began with the diffusion and adoption of high-yielding seed varieties, modern fertilizers, and other agricultural technologies (for example, pesticides, machinery), commonly known as the Green Revolution.
Social learning processes can be the basis of a method of agricultural innovation that involves expert and empirical knowledge. In this sense, the objective of this study was to determine the effectiveness and sustainability of an innovation process, understood as social learning, in a group of small farmers in the southern highlands of Peru. Innovative proposals and its permanence three years after the process finished were evaluated. It was observed that innovation processes generated are maintained over time; however, new innovations are not subsequently generated
Many smallholder farmers in developing countries grow multiple crop species on their farms, maintaining de facto crop diversity. Rarely do agricultural development strategies consider this crop diversity as an entry point for fostering agricultural innovation. This paper presents a case study, from an agricultural research-for-development project in northern Ghana, which examines the relationship between crop diversity and self-consumption of food crops, and cash income from crops sold by smallholder farmers in the target areas.
This study uses 344 women and men survey respondents involved in conservation agriculture (CA) and small-scale irrigation schemes (SSIS) as data sources for examining the effect of gendered constraints for adopting climate-smart agriculture amongst women in three areas in Ethiopia. Qualitative and quantitative data collections were applied using survey, in-depth interviews and focus group discussions. Quantitative data were analyzed using descriptive statistics, Pearson's chi-square test and binary logistic regression using statistical software for the social sciences (SPSS) version 24.
Agriculture remains the mainstay of Indian economy and major source of livelihood of rural household, predominantly by small and marginal farmers, and securing the food and nutritional security. This paper describes the reality of small and marginal farmers in India. These farmers face several problems of credit, input supply, proper linkage with market as so on. Women farmers are lagging behind in adopting the drudgery reduction technologies followed by health and nutrition of farm families.
Relying on cross-sectional data from 300 smallholder rice farmers, the study examined the effects of agricultural extension on improved rice variety adoption and farm income in northern Ghana. A recursive bivariate probit (RBP) model was used to assess the effect of agricultural extension on adoption while regression with endogenous treatment effect model (RETEM) was adopted to evaluate the effect of agricultural extension on farm income. The results indicate a statistically significant effect of agricultural extension on both adoption and farm income.
Agricultural mechanization in developing countries has taken at least two contested innovation pathways—the “incumbent trajectory” that promotes industrial agriculture, and an “alternative pathway” that supports small-scale mechanization for sustainable development of hillside farming systems.
Many indigenous vegetables are generally underutilized across different cultures, but they remain alternatives to exotic vegetables that often are expensive. This study investigated effects of participation in indigenous vegetable production on livelihood of farmers. Multistaged sampling was used to collect data from 222 vegetable farmers sampled from using a semi-structured questionnaire. Principal component analysis and endogenous switching regression (ESR) were employed for analysis