Open AccessTotal nitrogen in rice paddy field independently predicted from soil carbon using Near Infrared Reflectance Spectroscopy (NIRS)
Author(s) -
Bambang Hari Kusumo,
S. Sukartono,
B Bustan,
Y. Aris Purwanto
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1402/2/022096
Subject(s) - soil carbon , soil test , paddy field , nitrogen , environmental science , soil science , agronomy , near infrared reflectance spectroscopy , soil fertility , near infrared spectroscopy , soil water , chemistry , physics , organic chemistry , quantum mechanics , biology
As nitrogen (N) is needed at the greatest amount for the plant growth, the addition of adequate amount of this nutrient in rice paddy field is one of the key factors for maximizing the rice production. Knowing the spatial soil N status in the rice field measured using conventional analysis takes time and expensive. Many previous researchers reported that near infrared spectroscopy (NIRS) was able to successfully predict soil N due to its high correlation to the soil carbon (C). The aim of this research is to test whether NIRS able to predict soil N content, independently predicted from soil C. Soil samples in 147 locations, including the coordinates, were collected in rice paddy field of Lombok Island, Indonesia. Parts of the samples were analysed in a laboratory using conventional analysis for total N and total organic C, and the other parts were scanned using near infrared spectroscopy (NIRS) for spectral data collection. A Partial Least Square Regression (PLSR) calibration model was developed using laboratory-analysed soil N (and C) data and soil spectral data. Although soil N and soil C have a poor correlation, but both can be predicted well using NIR technology, indicating the soil N was independently predicted from soil C. This finding shows that soil N content in rice paddy field of Lombok Island can be predicted and monitored by NIRS without depending on its high autocorrelation with soil C.