Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)

Overview of attention for article published in Plant Methods, June 2020

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In the top 5% of all research outputs scored by Altmetric
One of the highest-scoring outputs from this source (#6 of 1,096)
High Attention Score compared to outputs of the same age (96th percentile)
High Attention Score compared to outputs of the same age and source (97th percentile)

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news: 7 news outlets
blogs: 3 blogs

twitter: 45 tweeters

Citations

dimensions_citation: 28 Dimensions

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mendeley: 94 Mendeley

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So far, Altmetric has seen 73 tweets from 45 users, with an upper bound of 230,444 followers.

RT @sci_plant: Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above a…

01 Jun 2021

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RT @sci_plant: Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above a…

01 Jun 2021

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Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz) https://t.co/JMIAxoKK8g #plantscience ♻️ https://t.co/846CzDkS6b

31 May 2021

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Pheno-i (https://t.co/K8F1CIKyCw) is a simple web based application to analyses aerial images to give the decision support to plant breeders. Validated so far in rice, Cassava, beans, Palm, Brachiaria. @BiovIntCIAT_eng @eia2030 @CGIAR_EiB @RTB_CGIAR ht

01 May 2021

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