Remote monitoring of chlorophyll content in soybean crops in the conditions of the Ryazan region

• Published in: BIO web of conferences 2023-01, Vol.71, p.1090
• Main Authors: Gureeva, E.V., Levakova, O.V.
• Format: Article
• Language: English
• ISSN: 2117-4458; 2117-4458
• DOI: 10.1051/bioconf/20237101090

The article considers research on the supervision of soybean crops, conducted in 2021 on the fields of the Institute of Seed Production and Agrotechnologies (a branch of the Federal State Budget Scientific Institution “Federal Scientific Agroengineering Center VIM”). The purpose of the research is to analyze and collect data on the photosynthetic state (PSS) of soybean plants (using the chlorophyll content as an example) and their impact on yield and quality indicators. The object of research is the early ripe varieties Kasatka, Mageva, Georgiy and Svetlaya. The study used a DJI Phantom 4 pro quadcopter, ground-based scanning - an N-tester express diagnostic device. Monitoring was carried out in three stages: 1st stage - phase R5 (beginning of seed formation); 2nd stage - phase R6 (seed filling); 3rd stage - phase R7 (beginning of ripeness). It has been established that with the use of UAV aerial photography, a reproducible picture of the spatial distribution of the ClGreen chlorophyll index is achieved, which is highly consistent with the results of ground-based scanning. It was revealed that varieties Kasatka, Mageva and Georgiya gradually reduce the chlorophyll content, starting from the R6 phase (with an average chlorophyll content of 511-588 units of the device) to the R7 phase, the chlorophyll content decreases by 44.8-56.1% (comprising 258 - 282 units of the device). A close positive relationship (r=+0.893) with the state of chlorophyll in the R6 phase with yield was established, an average (r=+0.597) - with oil content; significant negative relationship (r=-0.728) with protein content. Thus, when monitoring the UAV and the obtained ground information on the content of chlorophyll in the soybean seed filling phase (R6), it is possible to obtain predictable data on the yield and quality indicators of the future crop in advance.