Objective grading of rib eye traits using the Q-FOM™ camera in Australian beef carcasses.

The objective of this study was to develop calibration models against rib eye traits and independently validate the precision, accuracy, and repeatability of the Frontmatec Q-FOM™ Beef grading camera in Australian carcasses. This study compiled 12 different research datasets acquired from commercial processing facilities and were comprised of a diverse range of carcass phenotypes, graded by industry identified expert Meat Standards Australia (MSA) graders and sampled for chemical intramuscular fat (IMF%). Calibration performance was maintained when the device was independently validated. For continuous traits, the Q-FOM™ demonstrated precise (root mean squared error of prediction, RMSEP) and accurate (coefficient of determination, R2) prediction of eye muscle area (EMA) (R2 = 0.89, RMSEP = 4.3 cm2, slope = 0.96, bias = 0.7), MSA marbling (R2 = 0.95, RMSEP = 47.2, slope = 0.98, bias = -12.8) and chemical IMF% (R2 = 0.94, RMSEP = 1.56%, slope = 0.96, bias = 0.64). For categorical traits, the Q-FOM™ predicted 61%, 64.3% and 60.8% of AUS-MEAT marbling, meat colour and fat colour scores equivalent, and 95% within ±1 classes of expert grader scores. The Q-FOM™ also demonstrated very high repeatability and reproducibility across all traits.

Feedlot Factors Influencing the Incidence of Dark Cutting in Australian Grain-Fed Beef.

It has been well-established that dark cutting (DC) is a multifactorial issue that is associated with numerous animal and management factors. However, there is limited understanding of the feedlot-based factors that contribute to the influence of DC. The aim of this study was to evaluate the effect of climate, animal, and feedlot factors on the incidence of pH non-compliance in Australian grain-fed cattle. For this study, feedlot and abattoir records from 142,228 individual cattle over a 1-year period were investigated. These data incorporated records from seven feedlots that consigned cattle to three abattoirs. The average incidence of DC in these carcasses was 2.8%. The production factors that were associated with increased risk of DC included feedlot, sex, hormone growth promotants (HGP), cattle health, and days on feed (DOF). Additionally, DC also increased by reduced solar radiation (SR, W/m2), lower wind speeds (WS, m/s), increased ambient temperature (TA, °C), higher rainfall, a higher average temperature-humidity index (THI), and increased duration of time above heat-load-index threshold of 86 (HLI ≥ 86) during the 7 days prior to feedlot departure. This study identified the feedlot factors that increase the risk of DC from a feedlot-management perspective.

Cross-Platform Omics Prediction procedure: a statistical machine learning framework for wider implementation of precision medicine.

In this modern era of precision medicine, molecular signatures identified from advanced omics technologies hold great promise to better guide clinical decisions. However, current approaches are often location-specific due to the inherent differences between platforms and across multiple centres, thus limiting the transferability of molecular signatures. We present Cross-Platform Omics Prediction (CPOP), a penalised regression model that can use omics data to predict patient outcomes in a platform-independent manner and across time and experiments. CPOP improves on the traditional prediction framework of using gene-based features by selecting ratio-based features with similar estimated effect sizes. These components gave CPOP the ability to have a stable performance across datasets of similar biology, minimising the effect of technical noise often generated by omics platforms. We present a comprehensive evaluation using melanoma transcriptomics data to demonstrate its potential to be used as a critical part of a clinical screening framework for precision medicine. Additional assessment of generalisation was demonstrated with ovarian cancer and inflammatory bowel disease studies.

Differentiation of Livestock Internal Organs Using Visible and Short-Wave Infrared Hyperspectral Imaging Sensors.

Automatic identification and sorting of livestock organs in the meat processing industry could reduce costs and improve efficiency. Two hyperspectral sensors encompassing the visible (400-900 nm) and short-wave infrared (900-1700 nm) spectra were used to identify the organs by type. A total of 104 parenchymatous organs of cattle and sheep (heart, kidney, liver, and lung) were scanned in a multi-sensory system that encompassed both sensors along a conveyor belt. Spectral data were obtained and averaged following manual markup of three to eight regions of interest of each organ. Two methods were evaluated to classify organs: partial least squares discriminant analysis (PLS-DA) and random forest (RF). In addition, classification models were obtained with the smoothed reflectance and absorbance and the first and second derivatives of the spectra to assess if one was superior to the rest. The in-sample accuracy for the visible, short-wave infrared, and combination of both sensors was higher for PLS-DA compared to RF. The accuracy of the classification models was not significantly different between data pre-processing methods or between visible and short-wave infrared sensors. Hyperspectral sensors, particularly those in the visible spectrum, seem promising to identify organs from slaughtered animals which could be useful for the automation of quality and process control in the food supply chain, such as in abattoirs.

Using infrared thermography on farm of origin to predict meat quality and physiological response in cattle (Bos Taurus) exposed to transport and marketing.

Temperature is used as an indicator of animals' response to external stimuli and thus it could potentially be used as an indicator or poor animal welfare and meat quality. Remote monitoring of temperature can be achieved using infrared thermography (IRT) at the farm of origin before animals are sent to slaughter. Relationships between temperatures of cattle measured using IRT on-farm and potential indicators of stress and meat quality were investigated in 481 cattle in 2 experiments, one with sea transport and another with land transport. On-farm measurements included IRT and behavioural assessment of temperament along with measurement of physiological indicators of stress and carcass traits post-mortem. Significant correlations were found between IRT and meat pH, meat colour, creatine kinase, glucose, non-esterified fatty acids, magnesium, and temperament (P < .05). That said, these correlations did not persist across both experiments. Current findings suggest that on-farm IRT could have the potential to assist with the detection of compromised animal welfare and predict meat quality.

The Impact of Pre-Slaughter Stress on Beef Eating Quality.

The study evaluated the relationship between pre-slaughter stress, plasma biomarkers and consumer-evaluated eating quality of pasture raised beef cattle (n = 488). The design tested steer only, heifer only and mixed sex cattle with a comparison of direct kill versus a 14 day rest period in abattoir holding paddocks prior to slaughter. Experiment One sourced cattle from four farms and tested shipping and road transport. Experiment Two sourced cattle from four farms and tested a commercial saleyard pathway. The impact on treatment on untrained consumer eating quality scores were tested on five muscle groups, m. psoas major, m. longissimus dorsi lumborum, m. biceps femoris, m. semitendinosis, and m. infraspinatus. Across all muscles, a two-week rest period had the biggest improvement in sensory score. Mixed groups scored lower in the outside muscle than non-mixed groups. However, the mixing response was inconsistent in the eye round muscle and not significant in the other muscles. Plasma glucose and L-lactate indicated a marked acute stress response at slaughter with a small detrimental impact on consumer score. The muscle damage enzyme markers creatine kinase (CK) and aspartate aminotransferase (AST) were strongly associated with a lower meat quality score (MQ4). Neither ß-hydroxybutyrate (ßHB) nor non-esterified fatty acids (NEFA) were associated with MQ4, suggesting that fat mobilisation does not impact consumer sensory score.

Influence of Kiwifruit Extract Infusion on Consumer Sensory Outcomes of Striploin (M. longissimus lumborum) and Outside Flat (M. biceps femoris) from Beef Carcasses.

Actinidin is a cysteine protease enzyme which occurs in kiwifruit and has been associated with improved tenderness in red meat. This study evaluated the impact of actinidin, derived from kiwifruit, on consumer sensory outcomes for striploin (M. longissimus lumborum) and outside flat (M. biceps femoris). Striploins and outside flats were collected from 87 grass-fed steers. Carcasses were graded to the Meat Standards Australia (MSA) protocols. Striploins and outside flats were then dissected in half and allocated to one of the following two treatments: (1) not infused (control) and (2) infused with a kiwifruit extract (enhanced), and then prepared as grill and roast samples. Grill and roast samples were then aged for 10 or 28 days. Consumer evaluations for tenderness, juiciness, flavor, and overall liking were conducted using untrained consumer sensory panels consisting of 2080 individual consumers, in accordance with the MSA protocols. These scores were then used to calculate an overall eating quality (MQ4) score. Consumer sensory scores for tenderness, juiciness, flavor, overall liking, and MQ4 score were analyzed using a linear mixed-effects model. Kiwifruit extract improved consumer scores for tenderness, juiciness, flavor, overall liking, and MQ4 scores for striploins and outside flat (p < 0.05). These results suggest that kiwifruit extract provides an opportunity to improve eating experiences for consumers.

The Use of Biochemical Measurements to Identify Pre-Slaughter Stress in Pasture Finished Beef Cattle.

This study considered the relationship between pre-slaughter stressors and plasma biomarkers in 488 pasture-raised cattle across two experiments. The design aimed to test groups consisting of steer only, heifer only, and mixed sex cattle under direct kill versus rested (14 days in abattoir holding paddocks) protocols. In Experiment One, cattle were sourced from four farms, and transported by trucks and ships on the same day. In Experiment Two, cattle were sourced from four farms where a comparison was made between marketing via two commercial saleyards or direct farm gate consignment to abattoir. Blood samples were collected at exsanguination for subsequent analyses and relation to meat quality attributes. Muscle damage, as indicated by creatine kinase, is the biomarker most correlated to ultimate pH and muscle glycogen concentrations. A two-week rest period is effective for lowering this enzyme and improving muscle glycogen concentration. Although the cattle was subjected to a range of stress inducing treatments, we found that plasma biomarkers alone appeared insufficient for use as diagnostic stress indicators.

bcGST-an interactive bias-correction method to identify over-represented gene-sets in boutique arrays.

MOTIVATION: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes are important tools in Gene-Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene-set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene-set selection bias induced during the construction of these platforms. RESULTS: We propose bcGST, a bias-corrected GST by introducing bias-correction terms in the contingency table needed for calculating the Fisher's Exact Test. The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and the Cancer Genome Atlas cancer studies. AVAILABILITY AND IMPLEMENTATION: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Relationships between marbling measures across principal muscles.

As marbling is a principal input into many grading systems it is important to have an accurate and reliable measurement procedure. This paper compares three approaches to measuring marbling: trained personnel, near infrared spectroscopy (NIR) and image analysis. One 25mm slice of meat was utilised from up to 12 cuts from 48 carcasses processed in Poland and France. Each slice was frozen to enable a consistent post-slaughter period then thawed for image analysis. The images were appraised by experienced beef graders and the sample used to determine fat content by NIR. We find that image analysis based marbling measures are capturing something different to trained personnel and that there is a strong relationship between near infrared spectroscopy and trained personnel. Finally, we demonstrate that marbling measures taken on one muscle can be predictive of marbling in other muscles in the same carcase. This is particularly important for cut based models such as the Meat Standards Australia system.