Performance of mid infrared spectroscopy to predict nutrients for agricultural soils in selected areas of Ethiopia

Knowledge of soil nutrient status is a basic requirement in sustainable agriculture. However, assessment of soil properties has long been done through conventional laboratory analysis, which is costly and time-consuming. Therefore, developing alternative, cheaper and faster techniques for soil analysis is highly required. Mid-infrared spectroscopy (MIRS) techniques are rapid, convenient, environmentally friendly, and nondestructive techniques for quantifying several soil properties. This study aimed to evaluate the prediction performance of MIR for pH, organic carbon (O.C.), available phosphorus and sulfur, total nitrogen, exchangeable cations, and micronutrient. Soil samples were collected from southern Ethiopia. In this study, properties of 3882 soil samples were used as references from different parts of Ethiopia. Partial least squares regression (PLSR) was used for calibration. The correlation of measured and predicted properties of soil samples collected was analyzed using the Pearson correlation coefficient. Better prediction was obtained for Ca (R(2) = 0.95 and RPD = 3.9), CEC (R(2) = 0.92 and RPD = 3.5), TN (R(2) = 0.92 and RPD = 3.4), OC (R(2) = 0.91 and RPD = 3.4), Mg (R(2) = 0.84 and RPD = 2.6), pH (R(2) = 0.85 and RPD = 2.4) and Fe (R(2) = 0.65 and RPD = 1.7). In general, soil properties could be predicted using MIRS methods. On the other hand, soil nutrients that showed poor prediction require further studies.