Unverified paper record
Estimating technological parameters and stem productivity of sugarcane treated with rock powder using a proximal spectroradiometer Vis-NIR-SWIR
Industrial Crops & Products. · 1 Oct 2022
Abstract
This study aimed to evaluate the use of proximal Vis-NIR-SWIR spectroscopy to estimate technological parameters and tons of sugarcane per hectare (TSH) with the application of rock powder to the soil. It was carried out in an Arenosol area in Paranavaí , Brazil. The treatments were arranged within a split-plot system, designed in randomized blocks with four repetitions. For the experimental plots, inputs supplying calcium, magnesium, and sulfur were applied, whereas inputs supplying potassium were used for the subplots. The first and second cycles (sugarcane) were completed at 14 and 26 months, respectively, after the inputs application. During both growth cycles, technological parameters of the crop and of the TSH were determined. In addition, the stem spectrum of the crop was collected with a Vis-NIR-SWIR proximal spectroradiometer for later prediction of the parameters and TSH through the Partial Least Square Regression technique. It was possible to adjust models in the prediction phase with R²ₚ > 0.50 and RPDₚ > 1.50 for all evaluated attributes, with emphasis on three variables, namely purity, reducing sugars, and brix, which had R²ₚ and RPDₚ values above 0.86 and 2.75, respectively. The results show that proximal Vis-NIR-SWIR spectroscopy can be used to predict technological parameters and TSH of sugarcane with the application of rock powder. It offers advantages in relation to usual methods, since it is less time-consuming and low-cost, moreover it does not involve the use of toxic reagents.
Plant phenotyping relevance
サトウキビの品質形質と収量を近接Vis-NIR-SWIR分光で推定する手法を開発・評価しており、形質取得と予測モデルが研究の中心である。
abstractthe use of proximal Vis-NIR-SWIR spectroscopy to estimate technological parameters and tons of sugarcane per hectare (TSH)
abstractthe stem spectrum of the crop was collected with a Vis-NIR-SWIR proximal spectroradiometer for later prediction of the parameters and TSH through the Partial Least Square Regression technique
abstractIt was possible to adjust models in the prediction phase with R²ₚ > 0.50 and RPDₚ > 1.50 for all evaluated attributes
Code and data availability
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