Total nitrogen in rice paddy field independently predicted from soil carbon using Near Infrared Reflectance Spectroscopy (NIRS)

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 tim...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 1402; no. 2; pp. 22096 - 22101
Main Authors Kusumo, B H, Sukartono, S, Bustan, B, Purwanto, Y A
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.12.2019
Subjects
Carbon
Data collection
Infrared reflection
Infrared spectroscopy
Laboratories
Near infrared radiation
Nitrogen
Physics
Regression models
Soil analysis
Spectrum analysis
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Summary: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.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1402/2/022096