The efficacy of a vitamin D3 metabolite for improving the myofibrillar tenderness of meat from Bos indicus cattle

The influence of a once only administration of a metabolite of vitamin D3 (HY [middle dot] D(R)-25-hydroxy vitamin D3) on myofibrillar meat tenderness in Australian Brahman cattle was studied. Ninety-six Brahman steers of three phenotypes (Indo-Brazil, US and US/European) and with two previous hormonal growth promotant (HGP) histories (implanted or not implanted with Compudose(R)) were fed a standard feedlot ration for 70 d. Treatment groups of 24 steers were offered daily 10 g/head HY [middle dot] D(R) (125 mg 25-hydroxyvitamin D3) for 6, 4, or 2 d before slaughter. One other group of 24 steers was given the basal diet without HY [middle dot] D(R). Feed lot performance, blood and muscle samples and carcass quality data were collected at slaughter. Calcium, magnesium, potassium, sodium, iron and Vitamin D3 metabolites were measured in plasma and longissimus dorsi muscle. Warner-Bratzler (WB) shear force (peak force, initial yield) and other objective meat quality measurements were made on the longissimus dorsi muscle of each steer after ageing for 1, 7 and 14 d post-mortem at 0-2 [deg]C.There were no significant effects of HY [middle dot] D(R) supplements on average daily gain (ADG, 1.28-1.45 kg/d) over the experimental period. HY [middle dot] D(R) supplements given 6 d prior to slaughter resulted in significantly higher (P (R)) by phenotype/HGP interaction for peak force (P = 0.028), in which Indo-Brazil steers without previous HGP treatment responded positively (increased tenderness) to HY [middle dot] D(R) supplements at 2 d when compared with Indo-Brazil steers previously given HGP. There were no significant effects of treatment on other phenotypes. HY [middle dot] D(R) supplements did not affect muscle or plasma concentrations of calcium, potassium or sodium, but did significantly decrease plasma magnesium and iron concentrations when given 2 d before slaughter. There were no detectable amounts of 25-hydroxyvitamin D3 in the blood or muscle of any cattle at slaughter.

Detecting quantitative trait loci affecting beef tenderness on bovine chromosome 7 near calpastatin and lysyl oxidase

From a study of 3 large half-sib families of cattle, we describe linkage between DNA polymorphisms on bovine chromosome 7 and meat tenderness. Quantitative trait loci (QTL) for Longissimus lumborum peak force (LLPF) and Semitendonosis adhesion (STADH) were located to this map of DNA markers, which includes the calpastatin ( CAST) and lysyl oxidase (LOX) genes. The LLPF QTL has a maximum lodscore of 4.9 and allele substitution of approximately 0.80 of a phenotypic standard deviation, and the peak is located over the CAST gene. The STADH QTL has a maximum lodscore of 3.5 and an allele substitution of approximately 0.37 of a phenotypic standard deviation, and the peak is located over the LOX gene. This suggests 2 separate likelihood peaks on the chromosome. Further analyses of meat tenderness measures in the Longissimus lumborum, LLPF and LL compression (LLC), in which outlier individuals or kill groups are removed, demonstrate large shifts in the location of LLPF QTL, as well as confirming that there are indeed 2 QTL on bovine chromosome 7. We found that both QTL are reflected in both LLPF and LLC measurements, suggesting that both these components of tenderness, myofibrillar and connective tissue, are detected by both measurements in this muscle.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Determining and quantifying components of an aquaculture soundscape.

Recirculating aquaculture systems have a unique anthropogenic-based soundscape which is characterized by the type of equipment utilized, the structural configuration of walls, tanks, equipment, the substrate the tanks are situated on and even the activities of the personnel operating the facility. The soundscape of recirculation facilities is inadequately understood and remains poorly characterized, although it is generally accepted that the dominant sounds found in such facilities are within the hearing range of fish. The objective of this study was to evaluate the soundscape in a recirculating aquaculture facility from an intra-tank perspective and determine how the soundscape is shaped by a range of characteristics within the facility. Sounds were recorded across an operating aquaculture facility including different tank designs. The sounds recorded fell within previously measured pressure level ranges for recirculating systems, with the highest maximum sound pressure level (SPL) recorded at 124 dB re 1 mu Pa-2/Hz (with an FFT bin width of 46.9 Hz, centered at 187.5 Hz). The soundscape within the tanks was stratified and positively correlated with depth, the highest sound pressure occurring at the base of the tanks. Each recording of the soundscape was dominated by a frequency component of 187.5 Hz (corresponding centre of the 4th 46.9 Hz FFT analysis bin) that produced the highest observed SPL Analysis of sound recordings revealed that this peak SPL was associated with the acoustic signature of the pump. The soundscape was also evaluated for impacts of tank hood position, time of day, transient sounds and airstone particle size types, all of which were found to appreciably influence sound levels and structure within the tank environment. This study further discusses the distinctiveness of the soundscape, how it is shaped by the various operating components and considers the aquaculture soundscape in relation to natural soundscapes found within aquatic tropical environments.

Improved estimation of size-transition matrices using tag-recapture data

We derive a new method for determining size-transition matrices (STMs) that eliminates probabilities of negative growth and accounts for individual variability. STMs are an important part of size-structured models, which are used in the stock assessment of aquatic species. The elements of STMs represent the probability of growth from one size class to another, given a time step. The growth increment over this time step can be modelled with a variety of methods, but when a population construct is assumed for the underlying growth model, the resulting STM may contain entries that predict negative growth. To solve this problem, we use a maximum likelihood method that incorporates individual variability in the asymptotic length, relative age at tagging, and measurement error to obtain von Bertalanffy growth model parameter estimates. The statistical moments for the future length given an individual’s previous length measurement and time at liberty are then derived. We moment match the true conditional distributions with skewed-normal distributions and use these to accurately estimate the elements of the STMs. The method is investigated with simulated tag–recapture data and tag–recapture data gathered from the Australian eastern king prawn (Melicertus plebejus).

Fungal community structure in disease suppressive soils assessed by 28S LSU gene sequencing

Natural biological suppression of soil-borne diseases is a function of the activity and composition of soil microbial communities. Soil microbe and phytopathogen interactions can occur prior to crop sowing and/or in the rhizosphere, subsequently influencing both plant growth and productivity. Research on suppressive microbial communities has concentrated on bacteria although fungi can also influence soil-borne disease. Fungi were analyzed in co-located soils 'suppressive' or 'non-suppressive' for disease caused by Rhizoctonia solani AG 8 at two sites in South Australia using 454 pyrosequencing targeting the fungal 28S LSU rRNA gene. DNA was extracted from a minimum of 125 g of soil per replicate to reduce the micro-scale community variability, and from soil samples taken at sowing and from the rhizosphere at 7 weeks to cover the peak Rhizoctonia infection period. A total of ∼994,000 reads were classified into 917 genera covering 54% of the RDP Fungal Classifier database, a high diversity for an alkaline, low organic matter soil. Statistical analyses and community ordinations revealed significant differences in fungal community composition between suppressive and non-suppressive soil and between soil type/location. The majority of differences associated with suppressive soils were attributed to less than 40 genera including a number of endophytic species with plant pathogen suppression potentials and mycoparasites such as Xylaria spp. Non-suppressive soils were dominated by Alternaria , Gibberella and Penicillum. Pyrosequencing generated a detailed description of fungal community structure and identified candidate taxa that may influence pathogen-plant interactions in stable disease suppression. © 2014 Penton et al.

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.