Non-destructive prediction of sweetness of intact mango using near infrared spectroscopy
- 作者：Shyam Narayan Jha ; snjha_ciphet@yahoo.co.in ; Pranita Jaiswal ; K. Narsaiah ; Mansha Gupta ; Rishi Bhardwaj ; Ashish Kumar Singh
- 关键词：Mango ; Total soluble solids (TSS) ; pH ; Near infrared spectroscopy (NIRS) ; Multi-linear regression (MLR) ; Partial least square (PLS) ; Multiplicative scatter correction (MSC)
- 刊名：Scientia Horticulturae
- 出版年：2012
- 期刊代码：93_03044238
- 类别：abs
- 出版时间：1 May, 2012
- 卷：138
- 期：Complete
- 页码：171-175
- 文件大小：256 K
摘要
Agriculture industries are continuously in search of new user friendly technologies to evaluate the intrinsic properties of fruits before it is put in the market for the consumer. In the current study the potential of near-infrared (NIR) spectroscopy in the wavelength range of 1200-2200 nm was evaluated to determine total soluble solids and pH for seven major cultivars of mangoes from seven states of India. NIR models were developed based on multiple-linear regression (MLR) and partial least square (PLS) regression employing preprocessing technologies (baseline correction, smoothening, multiplicative scatter correction (MSC) and second order derivatisation). The multiple correlation coefficients for calibration and validation were found to be 0.782 and 0.762 for total soluble solids and 0.715 and 0.703 for pH respectively. The standard errors of calibration, prediction, biases and differences in them were low which indicated the NIRS potential to predict internal quality parameters (TSS and pH) of mango non-destructively for both models.