Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.
Capacity development interventions are considered critical entry points for advancing gender equality in agricultural research systems. However, the impacts of capacity development programs are often difficult to track. Academic reviews highlight that insufficient attention is paid to the suitability of gender training programs to increase capacity and limited evidence is available on their longer-term impacts.
The 2021 Global Report on Food Crises (GRFC 2021) highlights the remarkably high severity and numbers of people in Crisis or worse (IPC/CH Phase 3 or above) or equivalent in 55 countries/territories, driven by persistent conflict, pre-existing and COVID-19-related economic shocks, and weather extremes. The number identified in the 2021 edition is the highest in the report’s five-year existence. The report is produced by the Global Network against Food Crises (which includes WFP), an international alliance working to address the root causes of extreme hunger.
Agricultural innovation has played a critical role in the economic transformation of developing East Asian countries over the past half century. The Green Revolution—in the form of modern seed varieties, chemical fertilizers, pesticides, and modern machinery—has contributed to increased crop yields and farm incomes, and decreased poverty across the region. Although policy makers’ traditional focus on expanding and intensifying agricultural production has brought many benefits, the focus on productivity has come at a rising cost.
The national assessment of the agricultural innovation system (AIS) in Malawi was conducted using a framework of four types of analyses: functional, structural, capacity and enabling environment analysis. The approach included five case studies that addressed three methods including the use of indigenous methods for fall armyworm (FAW) control in Farmer Field Schools (FFS), livestock transfer programs, and a horticulture marketing innovation platform in Mzimba, Ntchisi, Balaka, and Thyolo districts.
This report introduces the reader to the concept of agricultural innovation systems (AIS) and the TAP-AIS project being implemented by FAO in nine countries, including Lao People's Democratic Republic (Lao PDR). The results of the AIS assessment for Lao PDR are presented, highlighting key barriers and opportunities for agricultural innovation in the country.
This working paper summarizes the findings of a portfolio review conducted to explore the gender and youth responsiveness of climate-smart agriculture technologies tested across climate-smart villages. The innovative and integrative aspect of the Climate-Smart Village (CSV) approach can provide useful insights into how to decrease the gender gap in the context of climate change.
Le CCAFS Afrique de l’Ouest met en œuvre un projet de « développement de chaînes de valeur et paysage climato-intelligents pour accroitre la résilience des moyens de subsistance en Afrique de l’Ouest ».
Participatory action research (PAR) has been around for years, and can add significant value to agriculture research for development projects. The use of PAR in climate-smart villages (CSVs) is no different. This review aimed to assess the impact that PAR approaches had on the adoption of CSA practices and technologies, with an emphasis on gender and social inclusion. Through a portfolio review, interviews with regional CSV teams, and surveys sent to local partners, this report demonstrates the benefit of PAR use in the implementation of the CSV approach.