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Welcome to the AgShare.Today Resource Centre

The AgShare.Today Resource Centre brings together a collection of resources related to agriculture. These include open access scientific journals and best practice guides that can be used for background reading and to support research initiatives. The AgShare Featured Resource showcases a new document each month that the AgShare team recommends to all members.

VirusDetect: an automated pipeline for efficient virus discovery using deep sequencing of small RNAs

This research presents VirusDetect, a bioinformatics pipeline that can efficiently analyse large-scale small RNA data sets for both known and novel virus identification.

Published by: Virology, Year: 2017, Pages: 9, File type: External link (1,272 KB)

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Reversing land degradation through grasses: a systematic meta-analysis in the Indian tropics

This study analyses the effect of grasses in reversing the process of land degradation using a systematic review.

Published by: Solid Earth, Year: 2017, Pages: 17, File type: External link (4 MB)

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Rates of return to sorghum and millet research investments: a meta-analysis

This study conducted a meta-analysis of 59 sorghum and millet ROR estimates obtained from 25 sources published between 1958 and 2015.

Published by: PLOS One, Year: 2017, Pages: 17, File type: External link (1.8 MB)

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Unravelling complex mixtures of badnavirus sequences present in yam germplasm

In this study, the molecular diversity of partial reverse transcriptase (RT)-ribonuclease H (RNaseH) sequences from yam badnaviruses was analysed using PCR-dependent denaturing gradient gel electrophoresis.

Published by: Viruses, Year: 2017, Pages: 24, File type: External link (3.8 MB)

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Quantitative trait locus associated with resistance to cassava brown streak and cassava mosaic diseases in a bi-parental cross of two Tanzanian farmer varieties, Namikonga and Albert

In this study, a QTL study was conducted to identify molecular markers linked to resistance against cassava brown streak disease and cassava mosaic disease.

Published by: Theoretical and Applied Genetics, Year: 2017, Pages: 22, File type: External link (2 MB)

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Using transfer learning for image-based cassava disease detection

Using a data set of cassava disease images taken in the field in Tanzania, this study applied transfer learning to train a deep convolutional neural network to identify three diseases and two types of pest damage.

Published by: Frontiers in Plant Science, Year: 2017, Pages: 7, File type: External link (2.2 MB)

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A time series transcriptome analysis of cassava varieties challenged with Ugandan cassava brown streak virus

This study involved a time-course transcriptome analysis of two cassava varieties that are either resistant or susceptible to cassava brown streak disease.

Published by: Scientific Reports, Year: 2017, Pages: 21, File type: PDF (3.7 MB)

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Complete genome sequence of a new member of the genus Badnavirus, Dioscorea bacilliform RT virus 3, reveals the first evidence of recombination in yam badnaviruses

In this article the first complete genome sequence of Dioscorea bacilliform RT virus 3 (DBRTV3) is described.

Published by: Archives of Virology, Year: 2017, Pages: 6, File type: External link (2.8 MB)

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Transgenic Cavendish bananas with resistance to Fusarium wilt tropical race 4

Cavendish banana is under threat from a virulent fungus, Fusarium oxysporum f. sp. cubense tropical race 4 (TR4), for which no acceptable resistant replacement has been identified. This study reports the identification of transgenic Cavendish with resistance to TR4.

Published by: Nature Communications, Year: 2017, Pages: 8, File type: External link (2.1 MB)

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Shaping, adapting and reserving the right to play: responding to uncertainty in high quality cassava flour value chains in Nigeria

This paper aims to explain why the high quality cassava flour (HQCF) value chain in Nigeria has not performed as well as expected.

Published by: Journal of Agribusiness in Developing and Emerging Economies, Year: 2017, Pages: 24, File type: External link (436 KB)

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