The success of precision agriculture (PA) depends strongly upon an efficient and accurate method for in-field soil property determination. This information is critical for farmers to calculate the proper amount of inputs for best crop performance and least environmental effect. Grid sampling, as a traditional way to explore in-field soil variation, is no longer considered appropriate since it is labor intensive, time consuming and lacks spatial exhaustiveness. Remote sensing (RS) provides a new tool for PA information gathering and has advantages of low cost, rapidity, and relatively high spatial resolution. Great progress has been made in utilizing RS for in-field soil property determination. In this article, recent publications on the subject of RS of soil properties in PA are reviewed. It was found that a large array of agriculturally-important soil properties (including textures, organic and inorganic carbon content, macro-and micro-nutrients, moisture content, cation exchange capacity, electrical conductivity, pH, and iron) were quantified with RS successfully to the various extents. The applications varied from laboratoryanalysis of soil samples with a bench-top spectrometer to field-scale soil mapping with satellite hyper-spectral imagery. The visible and near-infrared regions are most commonly used to infer soil properties, with the ultraviolet, mid-infrared, and thermal-infrared regions have been used occasionally. In terms of data analysis, MLR, PCR, and PLSR are three techniques most widely used. Limitations and possibilities of using RS for agricultural soil property characterization were also identified in this article.

Even though annual rainfall is high in the Delta region of Mississippi, only 30% occurs during the months in which the major crops are produced, making irrigation often necessary to meet crop water needs and to avoid risk of yield and profitability loss. Approximately, 65% of the farmland in this region is irrigated. The shallow Mississippi River Valley Alluvial Aquifer is the major source of water for irrigation and for aquaculture in the predominant catfish industry. This groundwater is being heavily used as row-crop irrigation has increased tremendously. Water level in this aquifer has declined significantly over the past twenty five years, with overdraft of approximately 370 million cubic meters of water per year. Moreover, the common irrigation practices in the Delta region of Mississippi do not use water efficiently, further depleting the ground water and making irrigation more expensive to producers due to increasing energy prices. Irrigation experts in the region have tested and verified various methods and tools that increase irrigation efficiency. This article presents a review of the current status of the irrigation practices in the Delta region of Mississippi, and the improved methods and tools that are available to increase irrigation efficiency and to reduce energy costs for producers in the region as well as to stop the overdraft of the declining aquifer, ensuring its sustainable use.

Soil samples were collected on a 0.4-ha (1.0-ac) grid from two agricultural fields in northeastern Mississippi. The samples were measured for soil nutrient composition, soil texture, and diffuse reflectance between 250 and 2500 nm. The data were examined for two purposes: (1) to understand the relationships between soil properties and reflectance spectra, and (2) to understand the sources of variability in the reflectance spectra. From the raw reflectance spectra, 50-nm-band averages were calculated. There were significant correlations between groups of the averaged spectra and soil properties, but no single 50-nm band was highly correlated to any soil property. Soil nutrients were better correlated with spectra in one field, but texture was better correlated with spectra in the other. Only Ca and Mg in one field and clay and pH in the other had multiple-regressor model correlations with R 2 values greater than 0.50. The relationships between soil properties and reflectance spectra were not consistent between fields. Based on the study of variability in reflectance spectra, the results of which were significantly dependent on the instrument used in this study, it was found that certain sections of the spectrum are more useful for discriminating among soil samples with differing characteristics. Spectral regions of high discriminatory power were 400 to 800 nm and 950 to 1500 nm.

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