Visible and near-infrared spectroscopy is an effective measurement method for estimating many soil ingredients at once. In precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for soil management, crop quality control using fertilizer, manure and compost, and variable-rate input for soil variability in a field.
We obtained Twenty-five calibration models based on Vis-NIR (305 - 1700 nm) underground soil reflectance spectra collected using a Real-time soil sensor with a differential global positioning system, in order to create each ingredient soil maps. The investigated soil ingredients were moisture content, soil organic matter, pH, electrical conductivity, cation exchange capacity, total carbon, ammonium nitrogen, hot water exchangeable nitrogen, nitrate nitrogen, total nitrogen, exchangeable potassium, exchangeable calcium, exchangeable magnesium, hot water soluble soil boron, soluble copper, exchangeable manganese, soluble zinc, available phosphate, C/N ratio, MgO/K2O ratio, CaO/MgO ratio, lime saturation degree, base saturation degree, bulk density and phosphate absorption coefficient.
The experimental site is a commercial upland field with alluvial soil located in Hokkaido, Japan. The experiment was conducted on 2 fields (Field A: 303×146 m, Field B: 303×148.8 m) after crop harvesting for development of Twenty-five calibration models. To develop these calibration models, soil samples were collected from the corresponding scanning positions of Vis-NIR data using a Real-time soil sensor.
A Real-time soil sensor was designed to collect underground soil reflectance spectra at depths of 0.05 to 0.35 m at 0.05 m spacing. The penetrator tip with flat plane edge ensures uniform soil cuts, and the soil flattener behind finishes to produce a uniform surface. The sensor unit’s housing included core devices of the system, such as a personal computer, a halogen lamp, two spectrophotometers, differential global positioning system receiver, CCD camera and etc. The spectrophotometer for Vis had a 256-pixel linear photodiode array to quantify the reflected energy in the spectral range of 310 to 1,100 nm. A 128-pixel linear diode array (Multiplexed InGaAs) for NIR was used to quantify the reflected energy in the spectral range of 950 to 1,700 nm.
In order to analyze Twenty-five calibration models, a total of 334 soil samples were collected from field A and B. Partial least-squares regression coupled with leave-one-out cross-validation method were used to establish the relationship between Vis-NIR underground soil reflectance spectra captured by a Real-time soil sensor and Twenty-five calibration models were obtained through soil chemical analysis. To develop these calibration models, the Unscrambler V9.8 software was used. We show the coefficient of correlation, coefficient of determination, root mean square error and residual prediction deviation. Accuracy of the calibration models in terms of each value of results was compared with that of previous studies, which includes field-based and lab-based results on almost the same wavelengths. The accuracy of Twenty-five calibration models were obtained for coefficient of determination (R2: from 0.64 to 0.84, leave-one-out cross-validation).
