Estimate of soybean defoliation via digital image processing in software<sup/>

Michels, Roger Nabeyama; Canteri, Marcelo Giovanetti; Silva, Marcelo Augusto de Aguiar e; Câmara, Carlos Alberto Paulinetti da; Bertozzi, Janksyn; Bosco, Tatiane Cristina Dal

doi:10.5935/1806-6690.20220029

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Scientific Article • Rev. Ciênc. Agron. 53 • 2022 • https://doi.org/10.5935/1806-6690.20220029 linkcopy

Estimate of soybean defoliation via digital image processing in software¹

Estimativa na desfolha da soja via processamento digital de imagens em software

Authorship SCIMAGO INSTITUTIONS RANKINGS

This study aimed to develop and validate the digital image processing software to quantify leaf coverage, employing the correlation of defoliation values and NDVI with various gradients of defoliation severity of the Asian soybean rust pathosystem. The digital images were obtained from the experiment conducted in 2013/2014. To conduct the experiment, 4 treatments (3 replicates) were adopted, considering the useful floor area of each plot (4 linear meters, 3 lines spaced at 0.45 m). The gradients of defoliation were obtained by treatment with fungicide to control Asian soybean rust. The quantification of the disease severity was performed through diagrammatic scale. The NDVI values were obtained using the GreenSeeker®, conducting the equipment above the plants. The digital photos were obtained in three heights and subsequently processed in software. Then the defoliation sampling was held in 10 plants through treatment. The image processing data correlated with defoliation (94.22%) and with NDVI (89.27%), and we also observed the correlation of defoliation with NDVI (96.12%). These data suggests the use of digital images as an alternative to quantify the vegetation cover, with the advantage of being a dynamic and fast method that does not require experience from the assessor to quantify soybean defoliation.

Key words:
Phakopsora pachyrhizi; NDVI; Reflectance; Leaf coverage; RGB

Height	41 DAE V5	58 DAE R2	65 DAE R3	72 DAE R4	79 DAE R5	86 DAE R6	92 DAE R7	102 DAE R7-R8
Without Spraying
1,20 m	75,17a	88,48a	83,30a	76,17a	82,67a	89,90a	45,29a	4,82a
2,00 m	77,73a	89,51a	83,37a	77,49a	82,59a	90,22a	43,55a	4,35a
3,00 m	78,96a	91,54a	83,39a	78,23a	89,62a	92,38a	40,35a	3,44a
6 Sprays
1,20 m	78,42a	90,09a	92,70a	79,55a	89,06a	92,87a	67,31a	21,06a
2,00 m	80,44a	89,52a	89,92a	80,51a	89,75a	93,40a	64,69a	20,20a
3,00 m	84,77a	91,21a	89,05a	81,19a	90,73a	94,56a	65,10a	18,48a
4 Sprays
1,20 m	94,44a	99,15a	94,54a	87,90a	91,36a	96,96a	61,80a	17,82a
2,00 m	93,98a	99,25a	95,57a	88,81a	92,98a	97,94a	64,11a	17,90a
3,00 m	94,23a	99,45a	95,14a	90,27a	93,69a	98,33a	66,69a	16,47a
3 Sprays
1,20 m	84,61a	87,81a	78,75a	78,82a	80,34a	84,36a	48,84a	7,93a
2,00 m	83,08a	88,41a	80,13a	79,61a	80,46a	86,82a	49,75a	7,84a
3,00 m	81,83a	89,10a	83,18a	81,97a	83,92a	86,20a	54,02a	8,14a

Spraying	6	4	3	0	Average
NDVI	0,777±0,034	0,965±0,004	0,926±0,003	0,903±0,005	0,893
Leaf Coverage	0,856±0,015	0,987±0,002	0,956±0,002	0,970±0,005	0,942

Treatment	6	4	3	0	Average
Disease	-0,953±0,003	-0,945±0,010	-0,938±0,010	-0,927±0,009	-0,941
NDVI	0,948±0,007	0,975±0,008	0,967±0,011	0,955±0,010	0,961

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E-mail: ccarev@ufc.br

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Estimate of soybean defoliation via digital image processing in software1

Estimativa na desfolha da soja via processamento digital de imagens em software

Estimate of soybean defoliation via digital image processing in software¹