Short communication: Long term performance of near infrared spectroscopy to predict intramuscular fat content in New Zealand lamb

Hitchman, Sam; Johnson, Peggy A.; Bain, W. E.; Craigie, C.R.; Reis, Marlon M.

doi:10.1016/j.meatsci.2020.108376

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…Finally, the optimal feature band is filtered by forward and backward partial least squares (FBiPLS) filtering [11]. According to the joint xy distance, the sample set was divided into 100 segments, and PLS fitting is performed to obtain 100 local regression models.…”

Section: Resultsmentioning

confidence: 99%

Rapid Diagnosis of HIV-1 virus by Near Infrared Spectroscopy: based on Partial least squares regression

Song

Shang

et al. 2021

E3S Web Conf.

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Currently, the laboratory diagnostic tests available for HIV-1 viral infection are mainly based on serological testing which relies on enzyme-linked immunosorbent assay (ELISA) for blood HIV antigen detection and reverse transcription polymerase chain reaction (RT-PCR) for HIV specific RNA sequence identification. However, these methods are expensive and time-consuming, and suffer from false positive and/or false negative results. Thus, there is an urgent need for developing a cost effective, rapid and accurate diagnostic method for HIV-1 infection. In order to reduce the barriers for effective diagnosis, a near-infrared spectroscopy (NIR) method was used to detect the HIV-1 virus in human serum, specifically, three absorption peaks with dose-dependent at 1582nm, 1810nm and 2363nm were found by multiple FBiPLSR test analysis for HIV-nano and HIV-EGFP, but not for MLV. Therefore, we recommend the use of 1582nm, 1810nm and 2363nm as the characteristic spectrum peak, for early screening and rapid diagnosis of serum HIV.

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Section: Resultsmentioning

confidence: 99%

Rapid Diagnosis of HIV-1 virus by Near Infrared Spectroscopy: based on Partial least squares regression

Song

Shang

et al. 2021

E3S Web Conf.

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“…In pork, Wang et al (2018a) and Wang et al (2020b) found high correlations between NIR spectra and IMF, protein, and moisture content (r p ≥ 0.86) using portable dual-band Vis-NIR spectrometers in research labs and PLSR. In contrast, several studies reported low or unreliable NIRS predictability for IMF content in lambs at 24 to 28 h postmortem (R 2 cv = 0.52 to 0.55 or R 2 p = 0.29 to 0.54; Knight et al, 2019;Fowler et al, 2021b;Hitchman et al, 2021a;Lambe et al, 2021) and beef longissimus thoracis aged for 2 and 7 d (R 2 cv = 0.08 and 0.12, respectively; de Nadai Bonin et al, 2020), using portable Vis-NIR spectrometers (350 to 2,500 or 400 to 1,395 nm) and PLSR at commercial abattoirs. The lower NIRS predictability in these studies could be partly due to the narrower range of wavelengths and/or IMF content compared with those used in Dixit et al (2020b).…”

Section: Near Infrared Spectroscopymentioning

confidence: 98%

Prediction of Carcass Composition and Meat and Fat Quality Using Sensing Technologies: A Review

Leighton

Marcoux

Wei

et al. 2022

Meat and Muscle Biology

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Consumer demand for high-quality healthy food is increasing,  thus meat processors require the means toassess these rapidly, accurately, and inexpensively. Traditional methods forquality assessments are time-consuming, expensive, invasive, and have potentialto negatively impact the environment. Consequently, emphasis has been put onfinding non-destructive, fast, and accurate technologies for productcomposition and quality evaluation. Research in this area is advancing rapidlythrough recent developments in the areas of portability, accuracy, and machinelearning. The present review, therefore, critically evaluates and summarizes developmentsof popular non-invasive technologies (i.e., from imaging to spectroscopicsensing technologies) for estimating beef, pork, and lamb composition andquality, which will hopefully assist in the implementation of thesetechnologies for rapid evaluation/real-timegrading of livestock products in the nearfuture.

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“…(2008), Hitchman et al . (2021a, 2021b) and Lambe et al . (2021) have all highlighted the ability of the NIRS system to quickly and accurately predict the IMF content of fresh beef and sheep meat samples; however, few studies have reported on the development of prediction models for protein using freeze‐dried ground samples from either species (Perry et al ., 2001; Dixit et al ., 2020; Coombs et al ., 2021), and fewer still that have examined combined species models, using both freeze‐dried ground beef and sheep meat (Coombs et al ., 2021).…”

Section: Introductionmentioning

confidence: 95%

“…Near-infrared spectroscopy has undergone many changes and advancements since its development in the 1960s (Davies, 1998), becoming an increasingly important tool in the food processing sector. Studies by Cozzolino et al (2002), Prevolnik et al (2005), Prieto et al (2006), Ripoll et al (2008), Hitchman et al (2021aHitchman et al ( , 2021b and Lambe et al (2021) have all highlighted the ability of the NIRS system to quickly and accurately predict the IMF content of fresh beef and sheep meat samples; however, few studies have reported on the development of prediction models for protein using freeze-dried ground samples from either species (Perry et al, 2001;Dixit et al, 2020;Coombs et al, 2021), and fewer still that have examined combined species models, using both freeze-dried ground beef and sheep meat (Coombs et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Prediction of the intramuscular fat and protein content of freeze‐dried ground meat from cattle and sheep using near‐infrared spectroscopy (NIRS)

Bailes¹,

Meyer²,

Piltz³

2022

Int J of Food Sci Tech

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Summary This study assessed the ability of near‐infrared spectroscopy to predict intramuscular fat (IMF) and protein content of freeze‐dried ground beef and sheep meat determined using the modified Soxhlet extraction and Dumas combustion, and ascertain if robust calibration models could be developed for both assays using the combined spectral data from both species. Samples were sourced from sheep and cattle slaughtered for a variety of experiments, which covered a range in age, diet fed and carcase cut. All samples were scanned using a benchtop NIRS instrument to develop calibration models, a subset of which was used for later validation. Intramuscular fat and protein content of samples ranged from 5.1 to 32.8 and 63.4 to 89.8, respectively, with combined species of the R2 values of 98.4 and 96.5 (RMSE 0.74 and 0.76) for IMF and protein respectively. Additionally, animal age and carcase cut were found to have no significant impact on the precision of prediction models. Results from our study showed that individual species as well as combined calibration models can be successfully developed for predicting IMF and protein content of freeze‐dried ground beef and sheep meat.

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Short communication: Long term performance of near infrared spectroscopy to predict intramuscular fat content in New Zealand lamb

Cited by 9 publications

References 15 publications

Rapid Diagnosis of HIV-1 virus by Near Infrared Spectroscopy: based on Partial least squares regression

Rapid Diagnosis of HIV-1 virus by Near Infrared Spectroscopy: based on Partial least squares regression

Prediction of Carcass Composition and Meat and Fat Quality Using Sensing Technologies: A Review

Prediction of the intramuscular fat and protein content of freeze‐dried ground meat from cattle and sheep using near‐infrared spectroscopy (NIRS)

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