Vegetation index value on chili leaves with symptoms of geminivirus disease (case study in Konda district, Konawe Selatan regency, Southeast Sulawesi)

Abstract

Expression of symptoms on chili plants infected with the Geminivirus can vary. This variation can be determined by viral satellite DNA (alphasatellites, betasatellites, deltasatelites) and the degree of plant resistance. The visual limitations of the human eye become an obstacle in recognizing and assessing the severity of plant virus symptoms in the field. It is hoped that an assessment method based on the normalized difference vegetation index (NDVI) value obtained from the processing of symptomatic plant images is expected to be a solution. No precise information has been found regarding the magnitude of the NDVI value in each variation of virus symptoms in chili plants. It can be an obstacle in the application of this method. The study aimed to measure the value of NDVI for each variation in the symptoms of virus-infected chili plants. Field survey activities accompanied by image recording of symptomatic and asymptomatic plants were carried out in curly chili plantations (as a model plant) in Konda District, South Konawe Regency, Southeast Sulawesi Province. Plant image recording was carried out during the day using a Canon 750D DSLR camera equipped with an NDVI lens filter, followed by image processing using the Fiji-ImageJ application + the Photo Monitoring plugin. The results showed that plants with various symptoms of severe mottle, narrow leaves, uneven leaf surface, mosaic, and stunting had an average NDVI index higher than 0.269 and a lower standard deviation value of 0.024 compared to other variations of symptoms.

Morphometric Analysis of Chili Leaves with Yellow Curly Symptom Using Digital Image Processing Approach and Data Mining Algorithm

“…Terdapat beberapa karakteristik utama citra yang dapat dimanfaatkan dalam analisis tanaman, di antaranya yaitu karakteristik warna (color) dan bentuk (shape) obyek dalam suatu citra (Ibaraki dan Gupta 2015). Pendekatan karakteristik warna untuk mengkaji gejala infeksi virus pada tanaman cukup banyak dikaji, baik berbasis warna RGB (Hasan et al 2022;Dumaria et al 2023) maupun berbasis indeks vegetasi (Hasan et al 2021b;Taufik et al 2023b;Taufik et al 2023a), sedangkan untuk kajian gejala virus pada tanaman menggunakan pendekatan karakteristik bentuk, sampai saat ini belum ditemukan laporannya. Berdasarkan studi literatur, kajian karakteristik bentuk baru sebatas di bidang ilmu bedah (Zdilla et al 2016), serta bidang geologi dan mineral (Szmańda dan Witkowski 2021;Ali et al 2023).…”