Rapid And Accurate Evaluation Of The Quality Of Soils And Commercial Organic Fertilizers Using Near Infrared Spectroscopy

Fertilization practices are very important for improving the soil fertiliy and increasing crop production. Meanwhile, rapid evaluation of the soil quality index under different fertilization practices are of great significance for optimizing fertilization practices. Since the traditional evaluation system of soil quality is time-consuming and laborious, seeking time-saving and economical analysis methods of soil quality has become a current research hot spot. The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance.In this study, a total of 136 paddy soil samples were collected from 17 different fertilization treatments of two short-term field experiments in Jintan and Zhangjiagang, the main grain production region in the middle and lower reaches of the Yangtze River for near infrared (350?2500 nm)-partial least squares (NIR-PLS) regression analysis. Based on the analysis coupled with the cross validation method, a model was established for quantitative analysis of the total carbon, total nitrogen, C/N ratio, available potassium, available phosphorus, electro-conductivity and soil pH obtained by near infrared diffuse reflectance spectroscopy and traditional chemical analysis. R2, determination coefficient value, and RSC, ratio of SD (standard deviation of chemical analysis)/RMSECV (root mean square error of cross validation) are two criteria for evaluation of the model. Results show that for the total carbon, total nitrogen, C/N ratio and pH, R2 was 0.94,0.95,0.97 and 0.92 and RSC was 4.31,4.35,5.60 and 3.37, respectively, suggesting that the model is good in prediction. For available potassium, R2 was 0.81 and RSC was 2.23, indicating that the model is good, however, for available phosphorus and electro-conductivity, R2 was 0.22 and 0.37 and RSC was 0.16 and 1.31, respectively, demonstrating that the model is not so ideal.A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China for near infrared (350?2500 nm) -partial least squares (NIR-PLS) regression analysis. Based on the analysis coupled with the cross validation method, a model was established for quantitative analysis of the moisture, total organic matter, total nitrogen, water soluble organic carbon, water soluble organic nitrogen, pH, electrical conductivity and germination index obtained by near infrared diffuse reflectance spectroscopy and traditional chemical analysis. Our results suggested the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon.In summary, relevant quality indices of paddy soil (total carbon, total nitrogen, C/N ratio, available potassium and soil pH) and commercial organic fertilizers (total organic matter, water soluble organic nitrogen, pH, germination index, moisture, total nitrogen, and electrical conductivity) can be rapidly predicted through the NIR-PLS regression analysis.