Survey of New Zealand consumer attitudes to consumption of meat and meat alternatives.

This study examined consumers' consumption, motivations, and concerns regarding meat and meat alternatives by means of an online survey of 1061 New Zealand consumers and review of literature. Outcomes of the survey indicate New Zealanders are overwhelmingly omnivorous (93%), regard taste as the most important factor in their meat purchasing decision followed by price and freshness and consider environmental impact and social responsibility of less importance. Those surveyed indicated willingness to pay 17-24% more for food safety and sustainability related meat attributes. About half of respondents lowered their meat consumption the previous year, mainly red and processed meats, due to lack of affordability and health concerns. Although those surveyed showed high awareness about meat alternatives, their consumption level of the products was very low and more prevalent for female, younger and more educated individuals. Overall, the outlook for meat consumption and meat industry in New Zealand is positive and is likely to remain so for the foreseeable future.

Potential of in-plant intramuscular fat predictions to enable sheep breeders to incorporate consumer preferences in breeding programmes.

The inclusion of eating quality traits in sheep genetic improvement programmes is desirable. Intramuscular fat (IMF) plays a key role in ensuring consumer satisfaction when eating lamb, but genetic progress for IMF is constrained by a lack of routine data collection. This study investigated the potential for IMF predictor traits to substitute for measured IMF in genetic improvement programmes. Carcass and predicted IMF (near-infrared estimated IMF and marbling score) data were available on 10,113 New Zealand lambs, 1678 of which also had measured chemical IMF on a slice of M. longissimus lumborum on which the predictions of IMF had been made. Genetic antagonisms were observed between carcass lean traits and IMF. The genetic correlation between the predictors and measured IMF approached one, indicating that predictors of IMF can be used in genetic improvement programmes. Through using selection indexes, simultaneous increases in IMF and the existing terminal selection index are possible, provided all traits are measured. This study highlights the importance and potential of predicted IMF to achieve genetic improvement in traits of importance to consumers.

Objective measurement technologies for transforming the Australian & New Zealand livestock industries.

This paper introduces the special edition of Meat Science focused upon the development, calibration and validation of technologies that measure traits influencing meat eating quality, or carcass fat and lean composition. These papers reflect the combined research efforts of groups in Australia, through the Advanced Livestock Measurement Technologies project, and New Zealand through AgResearch. We describe the various technologies being developed, how these devices are being trained upon common gold-standard measurements, and how their outputs are being simultaneously integrated into existing industry systems. We outline how this enhances the industry uptake and adoption of these technologies, and how this is further accelerated by education programs and strategic industry investment into their commercialisation.

Robustness of hyperspectral imaging and PLSR model predictions of intramuscular fat in lamb M. longissimus lumborum across several flocks and years.

The percentage of intramuscular fat content of lamb meat is a key index of consumer acceptability. Hyperspectral imaging is a potential technique for in-line measurements of intramuscular fat in fresh meat. However, little work has been conducted to investigate the robustness of hyperspectral imaging data and associated multivariate models over time. Fifteen trials consisting of eight independent flocks across five years were used to quantify robustness of partial least squares regression (PLSR) models developed using data collected with the same imaging system. Two models were developed; one using data from the first year of the trials, and a progressive model that cumulatively includes data in chronological order. The two models performed similarly, in terms of the coefficient of determination (R2), standard error of prediction (SEP) and bias, when experimental conditions were consistent. However, under varying imaging conditions, the progressive model was able to account for this variability resulting in higher R2 and lower SEP.

A global calibration model for prediction of intramuscular fat and pH in red meat using hyperspectral imaging.

This study demonstrates a novel approach to develop global calibration models for predicting intramuscular fat (IMF) and pH across various red meat species and muscle types. A total of 8 hyperspectral imaging (HSI) datasets were used from different experiments, comprising data from three species: beef, lamb and venison across various muscle type, slaughter season and measurement conditions. Prediction models were developed using Partial Least Squares Regression (PLSR) and Deep Convolutional Neural Networks (DCNN) using a total of 1080 and 1116 samples for IMF and pH, respectively. Models for pH and IMF via both techniques yielded high Rc2 (0.86-0.93) and low SEC values. Also, reasonably accurate prediction performance was observed with high Rp2 (0.86-0.89) and low SEP values. Overall results illustrated the comprehensiveness of these global calibration models with the ability to predict IMF and pH of red meat samples irrespective of species and muscle type.

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

This study investigates the performance of a partial least squares regression model to predict intramuscular fat (IMF) in lamb M. longissimus lumborum developed using near infrared (NIR) data collected under a range of different conditions. A total of 26 independent NIR datasets were collected across 7 years, including 14 flocks, four devices and several measurement conditions. A model is developed and its performance is tested using a total of n = 3201 NIR spectra and intramuscular fat percentage measurements by wet chemistry. The model had a coefficient of determination by cross-validation of 0.52, which agrees with previous results using smaller numbers of animals. Overall the results show that near infrared models can be robust across many varying conditions. These models could potentially be implemented in an automated meat quality monitoring system.

Non-invasive spectroscopic and imaging systems for prediction of beef quality in a meat processing pilot plant.

This study evaluated a range of diffuse reflectance spectroscopic (Vis-NIR spectrophotometers) and imaging (Hyperspectral imaging cameras) instruments for predicting pH, IMF and shear force values of beef in a meat processing pilot plant. A total of 364 beef striploin samples were evaluated and prediction models were developed using PLSR. Models for pH and IMF (except Vis snapshot camera) showed good fit with high Rcv2 (0.29-0.92) and low SECV values. Good prediction accuracy with high Rp2 (0.44-0.90), RPD and low SEP values was also observed. While low values of Rp2 for shear force was observed, the expected curvilinear relationship between predicted values of shear force and predicted values of pH was observed suggesting that spectroscopic measurements were able detect biophysical factors associated to these two attributes. Overall, it can be concluded that diffuse reflectance spectroscopy combined with chemometrics has a great potential to be used as an on/in-line quality monitoring system for the meat processing industry.

Consumer liking of M. longissimus lumborum from New Zealand pasture-finished lamb is influenced by intramuscular fat.

Palatability of meat is known to be affected by intramuscular fat (IMF), but the effect in relatively low-fat New Zealand lamb is unknown. This study evaluated the eating quality of 108 loins (M. longissimus lumborum) from a single flock of ewe-lambs. Loins ranged from 1.09-5.68% IMF and were stratified into 6 groups: 1.65, 2.12, 2.65, 3.20, 3.58 and 4.40%. Consumers' (n = 165) overall liking of lamb increased significantly at around 3% IMF, achieving maximum scores at 4% IMF. One consumer cluster (n = 111) showed a linear increase in overall liking with increasing IMF%, regarded as 'IMF lovers: the more the better', while a second cluster (n = 54) preferred 2.5-3.5% IMF, described as 'IMF optimizers: just the right amount'. IMF% was modestly correlated (~ + 0.25) with all sensory attributes except juiciness. Liking scores were modestly correlated with monounsaturated (~ + 0.25) and polyunsaturated (~ - 0.20) fatty acids. Results suggest aiming for IMF% levels in New Zealand lamb beyond 3% to maximize eating quality for premium markets in particular.

Evaluating the performance of a miniaturized NIR spectrophotometer for predicting intramuscular fat in lamb: A comparison with benchtop and hand-held Vis-NIR spectrophotometers.

This study compares a miniaturized spectrophotometer to benchtop and hand-held Vis-NIR instruments in the spectral range of 900-1700 nm for prediction of intramuscular fat (IMF) content of freeze-dried ground lamb meat; and their ability to differentiate fresh lamb meat based on animal age (4 vs 12 months). The performance of the miniaturized spectrophotometer was not affected by sample temperature equilibration time. Partial Least Square regression models for IMF showed Rcv2 = 0.86-0.89 and RMSECV = 0.36-0.40 values for all instruments. Day-to-day instrumental variation adversely affected performance of the miniaturized spectrophotometer (R2p = 0.27, RMSEP = 1.28). This negative effect was overcome by representing day-to-day variation in the model. The benchtop spectrophotometer and miniaturized spectrophotometer differentiated lamb meat by animal age. The miniaturized spectrophotometer has potential to be a fast, ultra-compact and cost-effective device for predicting IMF in freeze-dried ground lamb meat and for age classification of fresh lamb meat.

Application of Hyperspectral imaging to predict the pH, intramuscular fatty acid content and composition of lamb M. longissimus lumborum at 24h post mortem.

Cost-effective, rapid and objective measurement of lamb quality on a routine basis is an important step for lamb value chains wishing to manage lamb product quality. Hyperspectral imaging (HSI) technology has shown promise as a solution for objective non-invasive prediction of meat quality. The performance of HSI applied 24h post mortem to lamb M. longissimus lumborum (LL) within a processing plant environment was assessed over two sampling years to evaluate its suitability for an objective lamb meat quality assurance tool. Calibration and validation steps were undertaken to evaluate HSI prediction performance for predicting fatty acid content and composition (n=1020 lambs) and pH (n=2406 lambs). Practical considerations of reference meat quality data quality and validation strategies are discussed. HSI can be used to predict meat quality parameters of lamb LL with varying accuracy levels, but ongoing calibration and validation across seasons is required to improve robustness of HSI for objective non-invasive assessment of lamb meat quality.

A review of the development and use of video image analysis (VIA) for beef carcass evaluation as an alternative to the current EUROP system and other subjective systems.

The current EUROP beef carcass classification scheme is still largely dependent on visually assessed fatness and conformation and its purpose is to provide a common basis for the description of carcasses for use in trade, price reporting and intervention. The meat industry, however, aims for accurately predicted saleable meat yield (SMY%) to which the EUROP carcass classification shows highly variable correlations due in part to the variable distribution of fat throughout the carcass as affected by breed, sex, diet, and the level of fat trimming. Video image analysis (VIA) technology is capable of improving the precision and accuracy of SMY% prediction even for specific carcass joints and simultaneously mimics the visual assessment to comply with EU regulations on carcass classification. This review summarises the development and use of VIA for evaluation of beef carcasses and discusses the advantages and shortfalls of the technology and its application.