Assessment of Chlorophyll Content in Leaves of Crops and Orchards Based on SPAD, Multispectral, and Hyperspectral Techniques - Niaz, Nadia; Gulzar, Salman; Kazmi, Jamil Hasan; Aleem, Sughra Aleem; Pham, Mai-Phuong Pham; Mierzwa-Hersztek, Monika Mierzwa-Hersztek; Riaz Ahmed, Samreen; Lahori, Altaf Hussain; Mushtaq, Zainab Noor (Ecological Questions, 2023)
Strategic planning in developed and developing countries has significantly benefited from early assessment, identification and crop production monitoring. Remote sensing surveillance of crop health has brought significant benefits to farmers regarding early detection of latent issues, such as nutrient deficiencies or crop ailments, and taking remedial action. The study used geospatial techniques to monitor the orchards and crops of Halani in the Pakistani province of Sindh, using GeoEye and Landsat-8 satellite imagery. The absorbance of chlorophyll content in six fruit trees: mango (Mangifera indica L.), banana (Musa acuminata Colla), musambi (Citrus limetta Risso), kino (Citrus aurantium L.), lemon (Citrus limon (L.) Osbeck) and guava (Psidium guajava L.), as well as four crops: maise (Zea mays L.), rice (Oryza sativa L.), cotton (Gossypium herbaceum L.), and sugarcane (Saccharum) were recorded spectrophotometrically using a Beckman Coulter DU-530 single cell module spectrophotometer at 648 nm and 665 nm (homogenised in 100% ethanol), and non-destructive chlorophyll using a SPAD-502 portable chlorophyll meter (Minolta Corporation, New Jersey, USA) showed a strong positive correlation. The results of chlorophyll absorbance showed the same trend in crops through satellite data and laboratory analysis. Chlorophyll content and NDVI showed a positive correlation. The R² value for rice and banana was 0.9925 and 0.9578, respectively, while the SPAD and chlorophyll R² for rice was 0.838 and 0.75 for banana. The overall results indicate high chlorophyll content in the leaves of orchards rather than crops. The study’s outcomes show that satellite data are a potentially reliable and resourceful tool for early assessment of the reliability of agricultural monitoring. The health and growth of crops can be monitored with satellite data, which are ultimately used for yield prediction, consequently helping growers strategically harvest and market.