Abstract. Our work aimed to evaluate the use of visible–near-infrared (Vis–NIR) spectroscopy for predicting the production of leaf dry mass (LDM), as well as macro- and micronutrients contents of soybean leaves grown after application of limestone-mining coproducts. The treatments were arranged within a triple factorial scheme (6 × 2 × 2 + 2) and placed into pots in a greenhouse. We evaluated the following factors: type of input (limestone-mining coproducts), input particle size (filler and powder), and soil class (Arenosol and Ferralsol). After inputs incubation, the soybean was sown. Then, 42 days after sowing, we collected the foliar spectra, as well as leaves, for further analysis of the contents of macro- and micronutrients in leaves and production of LDM. We managed to adjust models at the stage of prediction with R2p > 0.50 and RPDp > 1.50 for the variables LDM, P, K, Mg, S, and Zn, with emphasis on the first four, which presented R2p above 0.65. Therefore, we conclude that Vis–NIR spectroscopy has a potential for predicting LDM and the nutrients contents of soybean subjected to the application of limestone-mining coproducts, with advantages such as speed, low cost, and no use of reagents that are toxic to the environment.

中文翻译：

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Vis-NIR 光谱：从叶片干产量估计到预测大豆作物中的宏量和微量营养素

摘要。我们的工作旨在评估使用可见-近红外 (Vis-NIR) 光谱预测叶片干重 (LDM) 的产生，以及施用石灰石开采副产品后生长的大豆叶片的宏量和微量营养素含量. 处理按三重因子方案（6 × 2 × 2 + 2）排列，并置于温室中的盆中。我们评估了以下因素：输入类型（石灰石开采副产品）、输入粒度（填料和粉末）和土壤类别（Arenosol 和 Ferralsol）。投入孵化后，播种大豆。然后，在播种后 42 天，我们收集了叶面光谱以及叶片，以进一步分析叶片中宏量和微量营养素的含量以及 LDM 的产生。我们设法在预测阶段调整模型，R2p > 0.50 和 RPDp > 变量 LDM、P、K、Mg、S 和 Zn 为 1.50，重点是前四个，它们的 R2p 高于 0.65。因此，我们得出结论，Vis-NIR 光谱具有预测 LDM 和应用石灰石开采副产品的大豆的营养成分的潜力，具有速度快、成本低、不使用对大豆有毒的试剂等优点。环境。