Literature DB >> 30690990

Leaf Doctor: A New Portable Application for Quantifying Plant Disease Severity.

Sarah J Pethybridge1, Scot C Nelson2.   

Abstract

An interactive, iterative smartphone application was used on color images to distinguish diseased from healthy plant tissues and calculate percentage of disease severity. The user touches the application's display screen to select up to eight different colors that represent healthy tissues. The user then moves a threshold slider until only the symptomatic tissues have been transformed into a blue hue. The pixelated image is then analyzed to calculate the disease percentage. This study reports the accuracy, precision, and robustness of Leaf Doctor using six different diseases with typical lesions of varying severity. Estimates of disease severity from Leaf Doctor were highly accurate (R2 ≥ 0.79; Cb ≥ 0.959) compared with estimates obtained from the discipline-standard, Assess. Precision was operationally defined as the ability of a rater to use Leaf Doctor and repeatedly obtain similar percentages of disease severity for the same image. Coefficients of variation were low (0.51 to 14.1%) across all disease datasets but a significant negative relationship was found between the coefficient of variation of estimates and mean disease severity. Other advantages of Leaf Doctor included comparatively less time for image processing, low cost, ease of use, ability to send results by e-mail, and the ability to create realistic standard area diagrams. Leaf Doctor is compatible with iPhone, iPad, and iPod touch and is optimized for iPhone 5. It is available as a free download at the iTunes Store.

Year:  2015        PMID: 30690990     DOI: 10.1094/PDIS-03-15-0319-RE

Source DB:  PubMed          Journal:  Plant Dis        ISSN: 0191-2917            Impact factor:   4.438


  9 in total

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Authors:  Xingguo Zheng; Noah Fahlgren; Arash Abbasi; Jeffrey C Berry; James C Carrington
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Authors:  Rashit I Tarakanov; Anna A Lukianova; Peter V Evseev; Stepan V Toshchakov; Eugene E Kulikov; Alexander N Ignatov; Konstantin A Miroshnikov; Fevzi S-U Dzhalilov
Journal:  Plants (Basel)       Date:  2022-03-30

5.  A system-theoretic approach for image-based infectious plant disease severity estimation.

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8.  A Recognition Method for Rice Plant Diseases and Pests Video Detection Based on Deep Convolutional Neural Network.

Authors:  Dengshan Li; Rujing Wang; Chengjun Xie; Liu Liu; Jie Zhang; Rui Li; Fangyuan Wang; Man Zhou; Wancai Liu
Journal:  Sensors (Basel)       Date:  2020-01-21       Impact factor: 3.576

Review 9.  Strategies to combat the problem of yam anthracnose disease: Status and prospects.

Authors:  Valentine Otang Ntui; Edak Aniedi Uyoh; Effiom Eyo Ita; Aniedi-Abasi Akpan Markson; Jaindra Nath Tripathi; Nkese Ime Okon; Mfon Okon Akpan; Julius Oyohosuho Phillip; Ebiamadon Andi Brisibe; Ene-Obong Effiom Ene-Obong; Leena Tripathi
Journal:  Mol Plant Pathol       Date:  2021-07-17       Impact factor: 5.663

  9 in total

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