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T-Stór is Teagasc’s Open Access Repository, maintained by the Teagasc Library Service. Stór is the Gaelic word for Repository or Store or Warehouse, and T-Stór is an online “store” of Teagasc Research outputs and related documents. T-Stór collects preserves and makes freely available scholarly communication, including peer-reviewed articles, working papers and conference papers created by Teagasc researchers. Where material has already been published it is made available subject to the open-access policies of the original publishers. About Teagasc
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Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysisThe objective of this study was to compare mid-infrared reflectance spectroscopy (MIRS) analysis of milk and near-infrared reflectance spectroscopy (NIRS) analysis of feces with regard to their ability to predict the dry matter intake (DMI) of lactating grazing dairy cows. A data set comprising 1,074 records of DMI from 457 cows was available for analysis. Linear regression and partial least squares regression were used to develop the equations using the following variables: (1) milk yield (MY), fat percentage, protein percentage, body weight (BW), stage of lactation (SOL), and parity (benchmark equation); (2) MIRS wavelengths; (3) MIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (4) NIRS wavelengths; (5) NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (6) MIRS and NIRS wavelengths; and (7) MIRS wavelengths, NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity. The equations were validated both within herd using animals from similar experiments and across herds using animals from independent experiments. The accuracy of equations was greater for within-herd validation compared with across-herds validation. Across-herds validation was deemed the more suitable method to assess equations for robustness and real-world application. The benchmark equation was more accurate [coefficient of determination (R2) = 0.60; root mean squared error (RMSE) = 1.68 kg] than MIRS alone (R2 = 0.30; RMSE = 2.23 kg) or NIRS alone (R2 = 0.16; RMSE = 2.43 kg). The combination of the benchmark equation with MIRS (R2 = 0.64; RMSE = 1.59 kg) resulted in slightly superior fitting statistics compared with the benchmark equation alone. The combination of the benchmark equation with NIRS (R2 = 0.58; RMSE = 1.71 kg) did not result in a more accurate prediction equation than the benchmark equation. The combination of MIRS and NIRS wavelengths resulted in superior fitting statistics compared with either method alone (R2 = 0.36; RMSE = 2.15 kg). The combination of the benchmark equation and MIRS and NIRS wavelengths resulted in the most accurate equation (R2 = 0.68; RMSE = 1.52 kg). A further analysis demonstrated that Holstein-Friesian cows could predict the DMI of Jersey × Holstein-Friesian crossbred cows using both MIRS and NIRS. Similarly, the Jersey × Holstein-Friesian animals could predict the DMI of Holstein-Friesian cows using both MIRS and NIRS. The equations developed in this study have the capacity to predict DMI of grazing dairy cows. From a practicality perspective, MIRS in combination with variables in the benchmark equation is the most suitable equation because MIRS is currently used on all milk-recorded milk samples from dairy cows.
Meta-proteomics for the discovery of protein biomarkers of beef tenderness: An overview of integrated studiesThis meta-proteomics review focused on proteins identified as candidate biomarkers of beef tenderness by comparing extreme groups of tenderness using two-dimensional electrophoresis (2-DE) associated with mass spectrometry (MS). We reviewed in this integromics study the results of 12 experiments that identified protein biomarkers from two muscles, Longissimus thoracis (LT) and Semitendinosus (ST), of different types of cattle: young bulls, steers or cows from beef breeds (Charolais, Limousin, Blond d’Aquitaine), hardy breed (Salers) or mixed breed (PDO Maine-Anjou). Comparative proteomics of groups differing in their tenderness evaluated by instrumental Warner-Bratzler shear force (WBSF) or by sensory analysis using trained panelists, revealed 61 proteins differentially abundant (P < 0.05) between tender and tough groups. A higher number of discriminative proteins was observed for LT (50 proteins) compared to ST muscle (28 proteins). The Gene Ontology annotations showed that the proteins of structure and contraction, protection against oxidative stress and apoptosis, energy metabolism, 70 family HSPs and proteasome subunits are more involved in LT tenderness than in ST. Amongst the list of candidate biomarkers of tenderness some proteins such as HSPB1 are common between the 2 muscles whatever the evaluation method of tenderness, but some relationships with tenderness for others (MYH1, TNNT3, HSPB6) are inversed. Muscle specificities were revealed in this meta-proteomic study. For example, Parvalbumin (PVALB) appeared as a robust biomarker in ST muscle whatever the evaluation method of tenderness. HSPA1B seems to be a robust candidate for LT tenderness (with WBSF) regardless the animal type. Some gender specificities were further identified including similarities between cows and steers (MSRA and HSPA9) in contrast to bulls. The comparison of the 12 proteomic studies revealed strong dissimilarities to identify generic biomarkers of beef tenderness. This integrative analysis allowed better understanding of the biological processes involved in tenderness in two muscles and their variations according to the main factors underlying this quality. It allowed also proposing for the first time a comprehensive list of candidate biomarkers to be evaluated deeply to validate their relationships with tenderness on a large number of cattle and breeds.
Transcriptomic response of maize primary roots to low temperatures at seedling emergenceBackground. Maize (Zea mays) is a C4 tropical cereal and its adaptation to temperate climates can be problematic due to low soil temperatures at early stages of establishment. Methods. In the current study we have firstly investigated the physiological response of twelve maize varieties, from a chilling condition adapted gene pool, to sub-optimal growth temperature during seedling emergence. To identify transcriptomic markers of cold tolerance in already adapted maize genotypes, temperature conditions were set below the optimal growth range in both control and low temperature groups. The conditions were as follows; control (18 ◦C for 16 h and 12 ◦C for 8 h) and low temperature (12 ◦C for 16 h and 6 ◦C for 8 h). Four genotypes were identified from the condition adapted gene pool with significant contrasting chilling tolerance. Results. Picker and PR39B29 were the more cold-tolerant lines and Fergus and Codisco were the less cold-tolerant lines. These four varieties were subjected to microarray analysis to identify differentially expressed genes under chilling conditions. Exposure to low temperature during establishment in the maize varieties Picker, PR39B29, Fergus and Codisco, was reflected at the transcriptomic level in the varieties Picker and PR39B29. No significant changes in expression were observed in Fergus and Codisco following chilling stress. A total number of 64 genes were differentially expressed in the two chilling tolerant varieties. These two varieties exhibited contrasting transcriptomic profiles, in which only four genes overlapped. Discussion. We observed that maize varieties possessing an enhanced root growth ratio under low temperature were more tolerant, which could be an early and inexpensive measure for germplasm screening under controlled conditions. We have identified novel cold inducible genes in an already adapted maize breeding gene pool. This illustrates that further varietal selection for enhanced chilling tolerance is possible in an already preselected gene pool.
Advances of plant-based structured food delivery systems on the in vitro digestibility of bioactive compoundsFood researchers are currently showing a growing interest in in vitro digestibility studies due to their importance for obtaining food products with health benefits and ensuring a balanced nutrient intake. Various bioactive food compounds are sensitive to the digestion process, which results in a lower bioavailability in the gut. The main objective of structured food delivery systems is to promote the controlled release of these compounds at the desired time/place, in addition to protecting them during digestion processes. This review provides an overview of the influence of structured delivery systems on the in vitro digestive behavior. The main delivery systems are summarized, the pros and cons of different structures are outlined, and examples of several studies that optimized the use of these structured systems are provided. In addition, we have reviewed the use of plant-based systems, which have been of interest to food researchers and the food industry because of their health benefits, improved sustainability as well as being an alternative for vegetarian, vegan and consumers suffering from food allergies. In this context, the review provides new insights and comprehensive knowledge regarding the influence of plant-based structured systems on the digestibility of encapsulated compounds and proteins/polysaccharides used in the encapsulation process.
Mid infrared spectroscopy and milk quality traits: a data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2021”chemometric data analysis challenge has been arranged during the first edition of the “International Workshop on Spectroscopy and Chemometrics”, organized by the Vistamilk SFI Research Centre and held online in April 2021. The aim of the competition was to build a calibration model in order to predict milk quality traits exploiting the information contained in mid-infrared spectra only. Three different traits have been provided, presenting heterogeneous degrees of prediction complexity thus possibly requiring trait-specific modelling choices. In this paper the different approaches adopted by the participants are outlined and the insights obtained from the analyses are critically discussed.