Chemometric strategies for non-destructive and rapid assessment of nitrate content in harvested spinach using vis- NIR spectroscopy
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Title |
Chemometric strategies for non-destructive and rapid assessment of nitrate content in harvested spinach using vis- NIR spectroscopy
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Creator |
Naveen Kumar Mahanti, Subir Kumar Chakraborty, Nachiket Kotwaliwale, Anand Kumar Vishwakarma
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Subject |
Vis-NIR spectroscopy
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Description |
Not Available
The overuse of nitrogenous fertilizers leads to an increase in the nitrate content of green leafy vegetables. Consumption of food with excess nitrate is not advisable because it results in human ailment. In this study, spinach leaves were harvested from plants grown under nine varying (0 to 400 kg/ha) nitrogenous fertilizer doses. A total of 261 samples were used to predict the nitrate content in spinach leaves using Vis-NIR (350 to 2,500 nm). The nitrate content was measured destructively using the ion-selective conductive method. Partial least square (PLS) regression models were developed using whole spectra and featured wavelengths. Spectral data were pre-processed using different spectral pre-processing techniques such as Savitzky–Golay (SG) derivative, standard normal variate (SNV), multiplicative scatter correction (MSC), baseline correction, and detrending. The predictive accuracy of the PLS model had improved after pre-processing of spectral data with MSC (RPDCV = 1.767; SECV = 545.745; biasCV = −3.107; slopeCV = 0.698) and SNV (RPDCV = 1.768; SECV = 545.337; biasCV = −3.201; slopeCV = 0.698) technique, but this was not significant (P < 0.05) as compared with raw spectral data (RPDCV = 1.679; SECV = 572.669; biasCV = −7.046; slopeCV = 0.687). The effective wavelengths for measurement nitrate content in spinach leaves were identified as 558, 706, 780, 1,000, and 1,420 nm. The performance of PLS model developed with effective wavelengths also had good prediction accuracy (RPDCV = 1.482; SECV = 648.672; biasCV = −3.805; slopeCV = 0.565) but significantly lower than the performance of model developed with full spectral data. The overall results of this study suggest that Vis-NIR spectroscopy can be an important tool and has great potential for the rapid and nondestructive assessment of nitrate content in harvested spinach, with a view to ascertain the suitability of the harvest for food uses. Not Available |
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Date |
2021-09-03T09:57:47Z
2021-09-03T09:57:47Z 2020-09-05 |
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Type |
Research Paper
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Identifier |
Mahanti, N. K., Chakraborty, S. K., Kotwaliwale, N., & Vishwakarma, A. K. (2020). Chemometric strategies for nondestructive and rapid assessment of nitrate content in harvested spinach using Vis‐NIR spectroscopy. Journal of Food Science, 85(10), 3653-3662.
Not Available http://krishi.icar.gov.in/jspui/handle/123456789/61271 |
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Language |
English
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Relation |
Not Available;
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Publisher |
Wiley Online Library
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