Role of Crop Research and Development in food Security of Africa

Food security is the main concern in Africa as the production and productivity of crops are under continuous threat. Indigenous crops also known as orphan- or as underutilized- crops provide key contributions to food security under the present scenario of increasing world population and changing climate. Hence, these crops which belong to the major categories of cereals, legumes, fruits and root crops play a key role in the livelihood of the resource-poor farmers and consumers since they perform better than the major world crops under extreme soil and climate conditions prevalent in the continent. These indigenous crops have the major advantage that they fit well into the general socio-economic and ecological context of the region. However, despite their huge importance, African crops have generally received little attention by the global scientific community. With the current production systems, only a fraction of yield potential was achieved for most of these crops. In order to devise strategies towards boosting crop productivity in Africa, the current production constraints should be investigated and properly addressed. Key traits known to increase productivity and/or improve nutrition and diverse conventional and modern crop improvement techniques need to be implemented. Commitments in the value-chain from the research, production, marketing to distribution of improved seeds are required by relevant national and international institutions as well as African governments to promote food security in a sustainable manner. The review also presents major achievements and suggestions for stakeholders interested in African agriculture.

Soils, agriculture and food security: The interplay between ecosystem functioning and human well-being

Healthy soils are critical to agriculture, and both are essential to enabling food security. Soil-related challenges include using soils and other natural resources sustainably, combating land and soil degradation, avoiding further reduction of soil-related ecosystem services, and ensuring that all agricultural land is managed sustainably. Agricultural challenges include improving the quantity and quality of agricultural outputs to satisfy rising human needs, also in a 2 degrees world; maintaining diversity in agricultural systems while supporting those farms with the highest potential for closing existing yield gaps; and providing a livelihood for about 2.6 billion mostly poor land users. The greatest needs and potentials lie in small-scale farming, although there as elsewhere, trade-offs must be negotiated within the nexus of water, energy, land and food, including the role of soil therein.

Food Recognition for Dietary Assessment Using Deep Convolutional Neural Networks

Diet management is a key factor for the prevention and treatment of diet-related chronic diseases. Computer vision systems aim to provide automated food intake assessment using meal images. We propose a method for the recognition of already segmented food items in meal images. The method uses a 6-layer deep convolutional neural network to classify food image patches. For each food item, overlapping patches are extracted and classified and the class with the majority of votes is assigned to it. Experiments on a manually annotated dataset with 573 food items justified the choice of the involved components and proved the effectiveness of the proposed system yielding an overall accuracy of 84.9%.