Cassava (Manihot esculenta Crantz) is one of the oldest root and tuber crops, used by humans to produce food, feed and beverages. Currently, cassava is produced in more than 100 countries and fulfils the daily caloric demands of millions of people living in tropical America, Africa, and Asia. Its importance as a food security crop is high in Western, Central and Eastern Africa due to its ability to produce reasonable yields (~10 t/ha) in poor soils and with minimal inputs. Traditionally a famine reserve and a subsistence crop, the status of cassava is now evolving fast as a cash crop and as raw material in the production of starch (and starch based products), energy (bioethanol) and livestock feed in the major producing countries. Cassava leaves, which are rich in protein and beta-carotenoids, are also used as a vegetable and forage (fresh or dehydrated meal) in various parts of the world. In recent years, some of the problems in the production of cassava have been increasing infection with cassava mosaic disease (CMD), cassava brown streak disease (CBSD) and cassava bacterial blight (CBB). Inherent postharvest physiological disorder (PPD) and cyanogenic glycosides (CG) are some of the most prominent challenges for scientists, producers and consumers in the post-production systems. Collaborative research in participatory plant breeding is ongoing at leading international research institutes such as IITA and CIAT to improve crop resistance to virus diseases, reduce PPD and CG, and improve the overall nutritional characteristics. Further research should also focus on post-production systems by developing enhanced storage and transportation techniques, mechanisation (peeling, size reduction, drying and dewatering) and improved packaging. Moreover, a robust national policy, market development, and dissemination and extension program are required to realise the full potential of innovations and technologies in cassava production and processing.

Posture detection targeted towards providing assessments for the monitoring of health and welfare of pigs has been of great interest to researchers from different disciplines. Existing studies applying machine vision techniques are mostly based on methods using three-dimensional imaging systems, or two-dimensional systems with the limitation of monitoring under controlled conditions. Thus, the main goal of this study was to determine whether a two-dimensional imaging system, along with deep learning approaches, could be utilized to detect the standing and lying (belly and side) postures of pigs under commercial farm conditions. Three deep learning-based detector methods, including faster regions with convolutional neural network features (Faster R-CNN), single shot multibox detector (SSD) and region-based fully convolutional network (R-FCN), combined with Inception V2, Residual Network (ResNet) and Inception ResNet V2 feature extractions of RGB images were proposed. Data from different commercial farms were used for training and validation of the proposed models. The experimental results demonstrated that the R-FCN ResNet101 method was able to detect lying and standing postures with higher average precision (AP) of 0.93, 0.95 and 0.92 for standing, lying on side and lying on belly postures, respectively and mean average precision (mAP) of more than 0.93.

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BackgroundUganda’s banana industry is heavily impeded by the lack of cheap, reliable and sustainable energy mainly needed for processing of banana fruit into pulp and subsequent drying into chips before milling into banana flour that has several uses in the bakery industry, among others. Uganda has one of the lowest electricity access levels, estimated at only 2–3% in rural areas where most of the banana growing is located. In addition, most banana farmers have limited financial capacity to access modern solar energy technologies that can generate sufficient energy for industrial processing. Besides energy scarcity and unreliability, banana production, marketing and industrial processing generate large quantities of organic wastes that are disposed of majorly by unregulated dumping in places such as swamps, thereby forming huge putrefying biomass that emit green house gases (methane and carbon dioxide). On the other hand, the energy content of banana waste, if harnessed through appropriate waste-to-energy technologies, would not only solve the energy requirement for processing of banana pulp, but would also offer an additional benefit of avoiding fossil fuels through the use of renewable energy.Main bodyThe potential waste-to-energy technologies that can be used in valorisation of banana waste can be grouped into three: Thermal (Direct combustion and Incineration), Thermo-chemical (Torrefaction, Plasma treatment, Gasification and Pyrolysis) and Biochemical (Composting, Ethanol fermentation and Anaerobic Digestion). However, due to high moisture content of banana waste, direct application of either thermal or thermo-chemical waste-to-energy technologies is challenging. Although, supercritical water gasification does not require drying of feedstock beforehand and can be a promising thermo-chemical technology for gasification of wet biomass such as banana waste, it is an expensive technology that may not be adopted by banana farmers in Uganda. Biochemical conversion technologies are reported to be more eco-friendly and appropriate for waste biomass with high moisture content such as banana waste.ConclusionUganda’s banana industrialisation is rural based with limited technical knowledge and economic capability to setup modern solar technologies and thermo-conversions for drying banana fruit pulp. This review explored the advantages of various waste-to-energy technologies as well as their shortfalls. Anaerobic digestion stands out as the most feasible and appropriate waste-to-energy technology for solving the energy scarcity and waste burden in banana industry. Finally, potential options for the enhancement of anaerobic digestion of banana waste were also elucidated.

The burden of malnutrition in Africa calls for deeper exploration of underutilized species which are rich in nutrients and have the potential to reduce food and nutrition insecurity. The common staple crops are not able to meet daily requirements for both macro-and micro-nutrients. In order to lessen this burden; protein, calorie and micronutrient deficiencies must be properly addressed for optimal growth and development to be attained. African indigenous underutilized vegetables can play a significant role in the food security of vulnerable groups like under-five children and women in both urban and rural settings. The potential of grain amaranth in meeting the nutrition needs of humans has remained a subject of interest in scientific research. Amaranth is considered one of the most commonly produced and consumed indigenous vegetables on the African continent with high nutritional potentials but yet to be fully exploited. This review therefore aims at discussing the current knowledge of the inherent potentials of grain amaranths, its current application in the food industry and proposes a framework for actions and partnerships required to scale up and improve amaranth value chain

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence Newcastle University ePrints-eprint.ncl.ac.uk

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The effect of air temperature and sample thickness on the color changes and total carotenoids content of carrot slices was investigated. Temperature, exposure time, and moisture levels significantly affected the dynamic changes of total carotenoids and color. A slow and linear decrease in total carotenoids was observed at higher moisture content until reaching an inflection point at around 0.45 g w/ g dm for all temperatures studied . Thereafter, the retention in total carotenoids decreased rapidly. The highest retention for a final product was 66.2% when drying at 60 C while retention was between 42.2 and 51.1% when drying at 50 and 70 C. These changes occurred alongside a noticeable change in color at moisture contents below the inflection point of 0.45 g w /g dm for all drying temperatures. Design of experiment based optimization of the drying process resulted in an ideal temperature of 59.8 C and 3.5 mm slice thickness with the predicted values for La*b*; ΔE of 62.18 ± 5.12, 22.46 ± 1.98, 40.35 ± 6.64, 6.31 ± 4.74; rehydration ratio of 0.48 ± 0.07; and total carotenoids of 163.83 ± 17.38 μg/g or 67.38%, respectively, all at a 95% prediction interval.