Abstract
Proximal sensing for assessing sugarcane quality information during harvest can be affected by various factors, including the type of sample preparation. The objective of this study was to determine the best sugarcane sample type and analyze the spectral response for the prediction of quality parameters of sugarcane from visible and near-infrared (vis-NIR) spectroscopy. The sampling and spectral data acquisition were performed during the analysis of samples by conventional methods in a sugar mill laboratory. Samples of billets were collected and four modes of scanning and sample preparation were evaluated: outer-surface (‘skin’) (SS), cross-sectional scanning (CSS), defibrated cane (DF), and raw juice (RJ) to analyze the parameters soluble solids content (Brix), saccharose (Pol), fibre, pol of cane and total recoverable sugars (TRS). Predictive models based on Partial Least Square Regression (PLSR) were built with the vis-NIR spectral measurements. There was no significant difference (p-value > 0.05) between the accuracy SS and CSS samples compared to DF and RJ samples for all prediction models. However, DF samples presented the best predictive performance values for the main sugarcane quality parameters, and required only minimal sample preparation. The results contribute to advancing the development of on-board quality monitoring in sugarcane, indicating better sampling strategies.
Highlights
IntroductionNear-Infrared (NIR) spectroscopy is a well-established technique to monitor the quality of raw sugarcane received by sugar mills [1], and for pricing and trading with producers and growers [2]
From the daily results of analyses performed by conventional methods at the mill, it was possible to characterize the variation of the main parameters determined analytically (Brix, Pol, and Fibre), as well as for total recoverable sugars (TRS), throughout the months in which the experiment was performed (Figure 2)
In the months corresponding to autumn (June) and winter (June to September), water stress and cooler temperatures contribute to the reduction of vegetative crop growth and favor sucrose storage [37]
Summary
Near-Infrared (NIR) spectroscopy is a well-established technique to monitor the quality of raw sugarcane received by sugar mills [1], and for pricing and trading with producers and growers [2]. All other parameters (purity, Pol of cane, reducing sugars, and total recoverable sugars) are calculated based on the former parameters [3], from which total recoverable sugars (TRS) are used for the pricing and trading of the raw material. Sugarcane quality parameters are determined by analytical methods and empirical equations described by the National Council of Sugarcane Producers (CONSECANA), which are based on the International Commission for Uniform Methods of Sugar Analysis (ICUMSA). It is possible to obtain some crop quality parameters by NIR spectroscopy [4]
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