Utilizing VSWIR spectroscopy for macronutrient and micronutrient profiling in winter wheat.

Area of Science:

• Agricultural Science
• Plant Physiology
• Remote Sensing

Background:

• Accurate quantification of foliar nutrients is crucial for optimizing crop health and yield in winter wheat.
• Traditional methods for nutrient analysis are often destructive, time-consuming, and not suitable for large-scale field assessments.
• Visible-to-shortwave infrared (VSWIR) spectroscopy offers a potential non-destructive approach for assessing plant physiological status.

Purpose of the Study:

• To evaluate the efficacy of leaf-level VSWIR reflectance in predicting macronutrient, micronutrient, and moisture concentrations in winter wheat.
• To develop and validate predictive models using partial least squares regression (PLSR) and explore different component selection methods.
• To assess the potential of VSWIR spectroscopy for high-throughput, non-destructive nutrient analysis in wheat breeding and precision agriculture.

Main Methods:

• Collected 360 winter wheat leaf samples over two growing seasons for VSWIR reflectance measurements (350–2,500 nm) and chemical analysis.
• Developed predictive models using partial least squares regression (PLSR) with three component selection methods: absolute minimum PRESS, backward iteration over PRESS, and Van der Voet's randomized t-test.
• Evaluated model performance using cross-validation and examined spectral region importance via variable importance in projection (VIP) scores.

Main Results:

• The backward iteration method generally provided a good balance between model performance and complexity.
• High predictive accuracies (R² values) were achieved for several nutrients and moisture content, including nitrogen (0.84), calcium (0.75), magnesium (0.78), and moisture (0.84).
• Variable importance analysis identified key spectral regions contributing to the predictive power of the models.

Conclusions:

• Leaf-level VSWIR reflectance combined with PLSR is a powerful, high-throughput method for quantifying diverse foliar nutrients and moisture in winter wheat.
• This non-destructive approach facilitates rapid and precise field assessments, supporting precision agriculture and enhancing wheat breeding program efficiency.
• The study demonstrates the potential of VSWIR spectroscopy to address nutrient deficiencies and optimize crop management strategies.