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This chapter provides a review on the state of art of the use of the visible near-infrared (vis-NIR) spectroscopy technique to determine mineral nutrients, organic compounds, and other physical and chemical characteristics in samples from agricultural systemssuch as plant tissues, soils, fruits, cocomposted sewage sludge and wastes, cereals, and forage and silage. Currently, all this information is needed to be able to carry out the appropriate fertilization of crops, to handle agricultural soils, determine the organoleptic characteristics of fruit and vegetable products, discover the characteristics of the various substrates obtained in composting processes, and characterize byproducts from the industrial sector. All this needs a large number of samples that must be analyzed; this is a time-consuming work, leading to high economic costs and, obviously, having a negative environmental impact owing to the production of noxious chemicals during the analyses. Therefore, the development of a fast, environmentally friendly, and cheaper method of analysis like vis-NIR is highly desirable. Our intention here is to introduce the main fundamentals of infrared reflectance spectroscopy, and to show that procedures like calibration and validation of data from vis-NIR spectra must be performed, and describe the parameters most commonly measured in the agricultural sector.

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The preferred olive tree cultivation strategy has evolved towards high-density cultivations to increase profitability and satisfy the global demand for olive oil. However, there is a lack of specific norms for the nutritional diagnosis of new growing systems and the varieties adapted to these systems. The objective of this study is to determine the sufficiency range and the diagnosis and recommendation integrated system and compositional nutritional diagnosis norms for Arbequina, Arbosana and Picual cultivars under superhigh-density olive tree cultivation. Leaves were sampled every fifteen days, from July to December, from high-productivity trees with production densities exceeding 8000 kg ha-1. The results show two periods of stability for the three varieties of olives: July-first two weeks of August and October-November. The three varieties showed substantial variability in their macronutrient concentrations, i.e., N, P, K, Ca and Mg, during both periods. The three aforementioned methods have improved the reliability of such diagnosis and provided concurrent diagnoses. Nevertheless, all the resulting norms need to be validated through an analysis of the results obtained in practice after their application.