Browsing by Author "Mwaipopo, Beatrice"
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Item Artificial intelligence and deep learning based Technologies for emerging disease recognition and pest Prediction in beans (phaseolus vulgaris l.): A systematic review(African Journal of Agricultural Research, 2023) Mahenge, Michael Pendo John; Mkwazu, Hussein; Madege, Richard Raphael; Mwaipopo, Beatrice; Maro, CarolineArtificial Intelligence (AI) and deep learning have the capacity to reduce losses in crop production, such as low crop yields, food insecurity, and the negative impacts on a country’s economy caused by crop infections. This study aims to find the knowledge and technological gaps associated with the application of AI-based technologies for plant disease detection and pest prediction at an early stage and recommend suitable curative measures. An evidence-based framework known as the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) methodology was used to conduct systematic reviews of the state-of-the-art of AI and deep learning techniques for crop disease identification and pest prediction in developing countries. The results demonstrate that conventional methods for plant disease management face some challenges, such as being costly in terms of labour, having low detection and prediction accuracy, and some are not environmentally friendly. Also, the rapid increase in data-intensive and computational-intensive tasks needed for plant disease classification using traditional machine learning methods poses challenges such as high processing time and storage capacity. Consequently, this paper recommends a deep learning and AI-based strategy to enhance the detection, prediction and prevention of crop diseases. These recommendations will be the starting point for future research.Item Viruses infecting common bean (Phaseolus vulgaris L.) in Tanzania: a review on molecular characterization, detection and disease management options(African Journal of Agricultural Research, 2017) Mwaipopo, Beatrice; Nchimbi-Msolla, Susan; Njau, Paul; Tairo, Fred; William, Magdalena; Binagwa, Papias; Kweka, Elisiana; Mbanzibwa, DeusdedithCommon bean (Phaseolus vulgaris L.) is a major legume crop, serving as a main source of dietary protein and calories and generating income for many Tanzanians. It is produced in nearly all agro ecological zones of Tanzania. However, the average yields are low (<1000 kg/ha), which is attributed to many factors including virus diseases. The most important viruses of common bean in Tanzania are Bean common mosaic virus (BCMV) and Bean common mosaic necrosis virus (BCMNV) but other viruses have also been reported. There has never been a review of common bean virus diseases in the country, and the lack of collated information makes their management difficult. Therefore, this review focuses on (1) occurrence of different viruses of common bean in Tanzania, (2) molecular characterization of these viruses, (3) detection tools for common bean viruses in Tanzania and (4) available options for managing virus diseases in the country. Literature and nucleotide sequence database searches revealed that common bean diseases are inadequately studied and that their causal viruses have not been adequately characterized at the molecular level in Tanzania. Increased awareness on common bean virus diseases in Tanzania is expected to result into informed development of strategies for management of the same and thus increased production, which in turn has implication on nutrition and income