All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Prediction of Moisture, Ash, Fat and PH in Both Intact Goat Cuts and Individual Muscles Using a Portable Near-Infrared Spectrometer

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027014%3A_____%2F25%3A10006293" target="_blank" >RIV/00027014:_____/25:10006293 - isvavai.cz</a>

  • Alternative codes found

    RIV/60460709:41210/25:103062

  • Result on the web

    <a href="https://doi.org/10.1007/s11947-025-03976-6" target="_blank" >https://doi.org/10.1007/s11947-025-03976-6</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11947-025-03976-6" target="_blank" >10.1007/s11947-025-03976-6</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Prediction of Moisture, Ash, Fat and PH in Both Intact Goat Cuts and Individual Muscles Using a Portable Near-Infrared Spectrometer

  • Original language description

    The objective evaluation of goat meat (e.g. quality and composition of different cuts and muscles) is important in developing and developed economies. These methods are essential to monitor meat composition from different production systems and aid in enterprise profitability. This study aimed to evaluate the ability of a portable near infrared (NIR) instrument to predict the proximate composition [moisture (M), ash, fat] and pH in intact goat cuts and individual muscle samples collected from a commercial abattoir. Intact cut and individual muscle samples were analysed using proximate analysis and scanned using a portable NIR instrument (900 - 1650 nm). The cross-validation statistics including the coefficient of determination (R2 CV) and the standard error in cross validation (SECV) were 0.76 (SECV: 0.62%), 0.73 (SECV: 0.47%), 0.72 (SECV: 0.24%) and 0.80 (SECV: 0.20) for the prediction of M (%), fat (%), ash (%) and pH in the combined goat cuts and individual muscle sample set, respectively. Separate calibrations were also developed for each of the individual muscles analysed where the R2 CV and SECV ranged between 0.75 to 0.80 (SECV: 0.79 to 1.26%) and between 0.69 to 0.73 (SECV: 0.14 to 024%) for moisture (%) and pH, respectively. It was concluded that NIR spectroscopy could determine the proximate composition (%M, % fat and % ash) and pH of intact goat cuts and individual muscle samples.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    21101 - Food and beverages

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Food and Bioprocess Technology

  • ISSN

    1935-5130

  • e-ISSN

  • Volume of the periodical

    18

  • Issue of the periodical within the volume

    10

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    9

  • Pages from-to

    8902-8910

  • UT code for WoS article

    001537767000001

  • EID of the result in the Scopus database

    2-s2.0-105011725753