Abstract
Brazil is one of the largest producers of maize worldwide. However, this production is threatened due to low soil fertility, especially low levels of potassium (K+). K+ is one of the most important nutrients in plant metabolism, acting on enzymatic activation and also on photosynthetic processes. The identification of its deficiency by using traditional methods is difficult with regard to timely restoration of the nutrient to adequate levels. Therefore, the use of low-cost modified cameras attached to Unmanned Aerial Vehicles (UAVs) are important tools for agricultural monitoring. Nevertheless, there are no reports of studies with the purpose of evaluating the monitoring of K+ deficiency in maize crops using multispectral images captured from UAVs. Therefore, this study aimed at exploring the possibility of identifying K+ deficiency and quantifying the nutrient leaf content by using a Vegetation Index (VI). The experiment was carried out at the National Soybean Research Centre (Embrapa Soja, a branch of the Brazilian Agricultural Research Corporation). The experimental plots were constantly managed in order to obtain different conditions of K+ availability to plants, achieving levels that ranged from severe deficiency to an adequate nutrient level. The following treatments were established: severe potassium deficiency (SPD), moderate potassium deficiency (MPD) and adequate supply of potassium (ASP). The evaluations were performed in the Brazilian maize crop referred to as ‘safrinha, at the V7, V12 and R3 developmental stages, with image capture covering the visible and near-infrared region, using two Fujifilm IS PRO digital cameras attached to an UAV. In these development stages, leaves were collected to determine tissue K+ concentration. The images were radiometrically corrected with the support of calibration targets and reference values, using an Fieldspec 3 Jr. spectroradiometer. The VIs comprised the ratio among the red, green and infrared spectral bands, that is, green normalized difference vegetation index (GNDVI), normalized difference vegetation index (NDVI), ratio between infrared and green (GRVI), ratio between green and infrared (GNIR), ratio between red and infrared (RNIR) and ratio between infrared and red (RVI). Regarding all the treatments assessed, the results showed that foliar K+ was statistically different. The VIs were efficient only in differentiating SPD and ASP treatments at all development stages evaluated. However, none were statistically significant for MPD. The linear regressions showed a high coefficient of determination (R2) and low root mean square error (RMSE) value; the best prediction of K+ concentration obtained was at V12 for regressions with these VIs: GRVI (R2 = 0.79, RMSE 4.50 g kg−1) and RVI (R2 = 0.71, RMSE 4.39 g kg−1). The grain yield values showed that SPD caused an average reduction of 5,645.90 kg ha−1 in relation to the ASP. Considering MPD, the grain yield was 1,242.00 kg ha−1 lower in comparison with ASP. In conclusion, estimating foliar K+ content and identifying its deficiency in maize crops based on the VIs of multispectral images from cameras attached to UAVs is possible, which ensures agility to these evaluations in a non-destructive manner, improving efficiency of K+ fertilization and providing farmers with a new tool.
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Claims 8
Claim · model-written summary
Foliar potassium differed statistically across the three supply treatments.
- Outcome
- foliar K+e0
Zea maysOrganisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Regarding all the treatments assessed, the results showed that foliar K+ was statistically different.”
t0“maize plants”
Claim · model-written summary
Vegetation indices distinguished severe deficiency from adequate potassium supply at all assessed stages.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The VIs were efficient only in differentiating SPD and ASP treatments at all development stages evaluated.”
t0“maize plants”
Claim · model-written summary
Vegetation indices did not distinguish moderate deficiency significantly.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“However, none were statistically significant for MPD.”
t0“maize plants”
Claim · model-written summary
At V12, GRVI predicted leaf potassium concentration with R2 0.79 and RMSE 4.50 g kg−1.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the best prediction of K+ concentration obtained was at V12 for regressions with these VIs: GRVI (R2 = 0.79, RMSE 4.50 g kg−1)”
t0“maize plants”
Claim · model-written summary
At V12, RVI predicted leaf potassium concentration with R2 0.71 and RMSE 4.39 g kg−1.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the best prediction of K+ concentration obtained was at V12 for regressions with these VIs: GRVI (R2 = 0.79, RMSE 4.50 g kg−1) and RVI (R2 = 0.71, RMSE 4.39 g kg−1)”
t0“maize plants”
Claim · model-written summary
Severe potassium deficiency reduced grain yield by 5,645.90 kg ha−1 relative to adequate supply.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The grain yield values showed that SPD caused an average reduction of 5,645.90 kg ha−1 in relation to the ASP”
t0“maize plants”
Claim · model-written summary
Moderate potassium deficiency yielded 1,242.00 kg ha−1 less grain than adequate supply.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Considering MPD, the grain yield was 1,242.00 kg ha−1 lower in comparison with ASP.”
t0“maize plants”
Claim · model-written summary
The authors conclude that UAV multispectral vegetation indices can estimate maize leaf potassium and identify deficiency without destructive sampling.
- Outcome
- estimating foliar K+ content and identifying its deficiencye0
Not reportedComparatorValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“estimating foliar K+ content and identifying its deficiency in maize crops based on the VIs of multispectral images from cameras attached to UAVs is possible”
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