Estimation of spikelet number per area by UAV-acquired vegetation index in rice (Oryza sativa L.)

Abstract

The objectives of this study were to find the best vegetation index (VI) associated with plant nitrogen content at the reproductive stage in rice, to associate the number of spikelets with this VI and solar radiation, and to estimate the number of spikelets. Rice cultivars Ishikawa 65 and Koshihikari were grown in the field in 2019 and 2020 at various nitrogen application rates and transplanting densities. From 30 days before heading to just after heading, the field was imaged with a multispectral camera. The images were processed with predefined ground control point data to create VI maps. From the maps, VI data were retrieved from the canopy area where plants were harvested for the determination of plant nitrogen content at the reproductive stage and of the number of spikelets at maturity. Among 6 VIs tested, the chlorophyll index green (CI green ) had the highest coefficient of determination (R 2 ) with plant nitrogen content at the reproductive stage and was the only VI with a linear relation with plant nitrogen content. The number of spikelets per unit area was well explained by multiple regression with CI green at 15 days before heading (CIG15) and cumulative solar radiation in the 15 days before heading (CSR15) as independent variables. A higher CIG15 would increase the number of spikelets differentiated and a higher CSR15 would reduce the rate of degeneration by increasing dry matter production.

Farmer’s considerations of grain quality based on government policy: Hutabayu Raja District, Simalungun Regency, North Sumatera Province

“…The following study does not consider factors that influence grain quality when selling products such [7] the organization, number of livestock, of the head of the household, farmed land, availability to irrigation, and cost of seeds and [8] found factors that influence agricultural sales performance include geographic location, land area, grain business expertise, farming background, grain storage practices, and application of crop insurance, and [9] demonstrates that grain quality in Ethiopia is influenced by grain moisture content, temperature, initial conditions, insects, pests and fungi [10]. Studies on factors that influence the quality of grain/rice from a cultivation perspective include [11] and in terms of the application of shade, the application of N to panicles on the application of rice quality and [12] stated that the chlorophyll index at heading (CIG0) is an acceptable indicator of grain quality in rice. The indicator of rice grain quality uses the percentage of several kinds of imperfect grains and grain protein content (GPC).…”