Literature DB >> 22063261

Prediction of pork quality attributes from near infrared reflectance spectra.

G H Geesink1, F H Schreutelkamp, R Frankhuizen, H W Vedder, N M Faber, R W Kranen, M A Gerritzen.   

Abstract

Near infrared spectroscopy (NIRS) is one of the most promising techniques for large-scale meat quality evaluation. We investigated the potential of NIRS-based models to predict drip loss and shear force of pork samples. Near infrared reflectance spectra (1000-2500 nm), water-holding capacity, shear force, ultimate pH, and colour (L(∗), a(∗), b(∗)-value) of 96 pork longissimus muscles were recorded at 2 days post mortem. Stepwise multiple linear regression (SMLR) and partial least squares regression (PLSR) analyses were used to formulate models for drip loss and shear force. Prediction models for drip loss correlated moderately strong with measured drip loss (R=0.71-0.74), which is similar to the correlation obtained using a combination of ultimate pH, filter paper test, and L(∗)-value (R=0.74). The current results indicate that NIRS enables the classification of pork longissimus muscles with a superior or inferior water-holding capacity as having a drip loss lower than 5% or higher than 7%. No useful models could be constructed for shear force.

Entities:  

Year:  2003        PMID: 22063261     DOI: 10.1016/S0309-1740(02)00269-3

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  5 in total

1.  Relationship between water-holding capacity and intramuscular fat content in Japanese commercial pork loin.

Authors:  Genya Watanabe; Michiyo Motoyama; Ikuyo Nakajima; Keisuke Sasaki
Journal:  Asian-Australas J Anim Sci       Date:  2017-12-19       Impact factor: 2.509

2.  Application of MIR Spectroscopy to the Evaluation of Chemical Composition and Quality Parameters of Foal Meat: A Preliminary Study.

Authors:  Marta Ruiz; María José Beriain; Miguel Beruete; Kizkitza Insausti; José Manuel Lorenzo; María Victoria Sarriés
Journal:  Foods       Date:  2020-05-05

3.  Determination of Hemicellulose, Cellulose and Lignin in Moso Bamboo by Near Infrared Spectroscopy.

Authors:  Xiaoli Li; Chanjun Sun; Binxiong Zhou; Yong He
Journal:  Sci Rep       Date:  2015-11-25       Impact factor: 4.379

4.  Chocolate Quality Assessment Based on Chemical Fingerprinting Using Near Infra-red and Machine Learning Modeling.

Authors:  Thejani M Gunaratne; Claudia Gonzalez Viejo; Nadeesha M Gunaratne; Damir D Torrico; Frank R Dunshea; Sigfredo Fuentes
Journal:  Foods       Date:  2019-09-20

5.  Nondestructive measurement of kiwifruit firmness, soluble solid content (SSC), titratable acidity (TA), and sensory quality by vibration spectrum.

Authors:  Wen Zhang; Aichen Wang; Zhenzhen Lv; Zongmei Gao
Journal:  Food Sci Nutr       Date:  2020-01-20       Impact factor: 2.863

  5 in total

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