Non-Destructive Quality Characterization of Peach Fruit Using Vis / NIR Spectroscopy and Multivariate Analyzing

Alizadeh Langebiz, Fatemeh (2019) Non-Destructive Quality Characterization of Peach Fruit Using Vis / NIR Spectroscopy and Multivariate Analyzing. Masters thesis, University of Mohaghegh Ardabili.

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Abstract

Research Aim:In this study, the capability of the Vis / NIR method for non-destructive evaluation of quality and detection of some peach varieties including Zaferani, Makhmali and Javadi was investigated. Research method:In this regard, a capacitive array (CCD) spectroradiometer witharange of 350 to 1150 nm was used to predict pH, titrable acid (TA), soluble solid-state (SSC), total phenol (TP), extract anthocyanin (Prance and Nesbitt) nondestructively.Multivariate partial least squares (PLS) regression models were used based on reference and degradation measurements. Spectral data processed with Savitsky-Goley smoothing (SG), first derivative (D1), incremental diffusivity correction (MSC), standard normal distribution (SNV) and Baseline correction was performed individually and in combination (SG + MSC + D1) and (SG + Baseline) to predict peach quality characteristics. The models were evaluated by the root mean square error of prediction (RMSEP), correlation coefficient (rp) and standard deviation ratio (SDR). Findings: The results showed that the Vis / NIR spectroscopy method had different capabilities in predicting some qualitative parameters of the peach cultivars. The best prediction accuracy was related to pH parameter, which could make saffron cultivar with moderate accuracy (SDR >1/5), velvet cultivar with acceptable accuracy (SDR >2) and velvet cultivar with high accuracy (SDR >2.5). The velvet peach's TA was not predictable using spectroscopy, but in the rest of cultivars, this parameter was predicted in the range of 1/5<SDR<2/5. The SSC predicted two velvet and Javadi cultivars with moderate accuracy (rp >0/8 and SDR >1/5) and saffron cultivar with high accuracy (rp>0/90 and SDR>2/5). The amount of total phenol and anthocyanin in Javadi cultivar was not predictable for any pretreatments and these parameters were predicted in two cultivars of Saffron and Velvet with moderate accuracy (rp >0/75 and SDR >1/5).

Item Type: Thesis (Masters)
Persian Title: تشخیص غیرمخربپارامترهای کیفی میوه هلو با استفاده از اسپکتروسکوپی Vis/NIR و تحلیل رگرسیون چندگانه
Persian Abstract: -
Supervisor:
SupervisorE-mail
Rasooli Sharabiani, ValiUNSPECIFIED
Advisor:
AdvisorE-mail
Azad SKahraki, FarzadUNSPECIFIED
Soltani Nazarlo, ArazUNSPECIFIED
Subjects: Faculty of Agricultural Sciences & Natural Resources > Department of Biosystem
Divisions > Faculty of Agricultural Sciences & Natural Resources > Department of Biosystem
Divisions: Subjects > Faculty of Agricultural Sciences & Natural Resources > Department of Biosystem
Faculty of Agricultural Sciences & Natural Resources > Department of Biosystem
Date Deposited: 07 Jun 2020 04:35
Last Modified: 07 Jun 2020 04:35
URI: http://repository.uma.ac.ir/id/eprint/11555

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