Estimate of soybean defoliation via digital image processing in software

• Autor(a) principal: Michels,Roger Nabeyama
• Data de Publicação: 2022
• Outros Autores: Canteri,Marcelo Giovanetti, Silva,Marcelo Augusto de Aguiar e, Câmara,Carlos Alberto Paulinetti da, Bertozzi,Janksyn, Bosco,Tatiane Cristina Dal
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista ciência agronômica (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902022000100429
• topic: Phakopsora pachyrhizi; NDVI; Reflectance; Leaf coverage; RGB

ABSTRACT 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.