Abstract Soybean and its derivatives are one of the most valuable and traded agricultural commodities worldwide. The major problem faced by the producers is the reduction of soybean yield due to diseases. In Brazil, the green stem and foliar retention (GSFR) was recently described as affecting soybean plants and causing concerns. Unfortunately, no effective methods of early diagnosis and treatments are known. In an attempt to better investigate the plant changes caused by GSFR infection, soybean leaves collected from healthy and sick plants of two varieties from two different places of Brazil were evaluated comparatively for their content of the three macronutrients Ca, K and Mg by laser-induced breakdown spectroscopy (LIBS). Atomic absorption spectrometry (AAS) was used as the reference technique. In general, the relative simplicity of LIBS instrumentation and the minimal sample preparation required makes it a valuable tool for agriculture application, including nutritional investigation and disease diagnosis of plant samples. The Pearson coefficients obtained for the correlation between LIBS and AAS data were close to 0.80 for the three nutrients analyzed. The results obtained by applying the Student t-test and Principal Component Analysis (PCA) to experimental data allowed to discern between healthy and sick plant leaves. LIBS data analyzed by the classification via regression (CVR) method associated with Partial Least Square Regression (PLSR) yielded success rates higher than 80% in class differentiation. This study demonstrates the possibility of using LIBS as a convenient analytical tool to discern between healthy and GSFR infected plants by analyzing the three macronutrient Ca, K and Mg, thus providing an early GSFR diagnostic tool.

中文翻译：

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通过激光诱导击穿光谱 (LIBS) 对健康和 Aphelenchoides besseyi 感染的大豆叶片进行营养表征

摘要 大豆及其衍生物是全球最有价值和交易量最大的农产品之一。生产者面临的主要问题是病害导致大豆减产。在巴西，绿色茎叶滞留 (GSFR) 最近被描述为影响大豆植物并引起关注。不幸的是，尚无有效的早期诊断和治疗方法。为了更好地研究 GSFR 感染引起的植物变化，从巴西两个不同地方的两个品种的健康和患病植物中采集的大豆叶片，通过激光诱导比较评估其三种常量营养素 Ca、K 和 Mg 的含量。击穿光谱（LIBS）。原子吸收光谱法 (AAS) 用作参考技术。一般来说，LIBS 仪器的相对简单性和所需的最少样品制备使其成为农业应用的宝贵工具，包括植物样品的营养调查和疾病诊断。对于分析的三种营养素，LIBS 和 AAS 数据之间的相关性获得的 Pearson 系数接近 0.80。通过将学生 t 检验和主成分分析 (PCA) 应用于实验数据获得的结果允许区分健康和生病的植物叶子。通过与偏最小二乘回归 (PLSR) 相关的回归分类 (CVR) 方法分析的 LIBS 数据在类别区分方面的成功率高于 80%。