Now showing items 21-40 of 2275

    • Bioprocessing of brewers’ spent grain for production of Xylanopectinolytic enzymes by Mucor sp.

      Hassan, Shady S.; Tiwari, Brijesh K; Adams, Gwylim A.; Jaiswal, Amit K.; TU Dublin; Science Foundation Ireland; 16/RC/3889 (Elsevier, 2019-12-26)
      The potential of microwave and ultrasound was evaluated for the pretreatment of brewer's spent grain (BSG). Under optimal conditions of microwave and ultrasound pretreatments, reducing sugar yields per 1 g of pretreated BSG were 64.4 ± 7 mg and 39.9 ± 6 mg, respectively. Subsequently, the pretreated BSG was evaluated as a substrate for production of Xylanopectinolytic enzymes using fungi isolated from spoiled fruits. Out of twenty-nine (29) isolates recovered, Mucor sp. (AB1) isolated from Bramley apple (Malus domestica) produced xylanopectinolytic enzymes with higher specific activity, and was selected for further studies. The highest enzyme activity (137 U/g, and 67 U/g BSG, for pectinase and xylanase, respectively) was achieved in a medium that contained 15 g of BSG, at pH 6, temperature of 30 °C, supplemented with 1% xylan or pectin for inducing the production of xylanase or pectinase, respectively. The partially purified xylanopectinolytic enzymes were optimally active at 60 °C and pH 5.
    • Evolution of the bovine milk fatty acid profile – From colostrum to milk five days post parturition

      O'Callaghan, Tom; O'Donovan, Michael; Murphy, John; Sugrue, Katie; Mannion, David; McCarthy, William P.; Timlin, Mark; Kilcawley, Kieran; Hickey, Rita M.; Tobin, John T. (Elsevier BV, 2020-05)
      Milk was collected from each of 18 cows (presenting an even spread of 1st, 2nd and 3rd lactation): colostrum on the day of calving and subsequent morning milk 1–5 days post parturition. Days post parturition significantly affected the fatty acid profile of colostrum and transition milk samples. The colostrum fatty acid profile was distinctly different from that of mature milk, with significantly higher levels of polyunsaturated and saturated fatty acids. Parity of the cow had a significant effect on the fatty acid profile of colostrum and transition milk samples; conjugated linoleic acid was significantly higher in cows entering their 1st lactation than in those in their 3rd lactation, while multiparous cows produced significantly higher concentrations of C16:0. The changing composition of the fatty acid profile can be classed into three distinct phases: colostrum (D0), transition milk (D1 and D2 post parturition) and mature milk (D3–D5).
    • The effects of sequential heat treatment on microbial reduction and spore inactivation during milk processing

      Li, Fang; Hunt, Karen; Buggy, Aoife K.; Murphy, Kevin; Ho, Quang Tri; O'Callaghan, Tom; Butler, Francis; Jordan, Kieran; Tobin, John; Department of Agriculture, Food and the Marine; et al. (Elsevier BV, 2020-05)
      Sequential heating processes are commonly applied to milk by the dairy industry as part of their microbiological control strategy. Often pasteurisation at 72 °C is followed by a sequential high heat treatment step of up to 125 °C; however, such severe heat treatment can lead to reduced protein quality. Nine temperature combinations (80–90 °C) were evaluated to assess microbial reduction and whey protein nitrogen index values during pilot scale milk processing. A total of 110 bacterial isolates were identified to species level by 16S rDNA sequencing, with Bacillus licheniformis identified as the dominant species. While the experimental treatments did not achieve microbial reductions comparable with the control heating process, the results of this study provide a benchmark for milk processors relative to the effects of sequential heat treatments on milk and their impact on the survival of both thermally resistant microbial populations and thermally labile milk components during processing.
    • Mid-infrared spectroscopy as an alternative to laboratory extraction for the determination of lime requirement in tillage soils

      Metzger, Konrad; Zhang, Chaosheng; Ward, Mark; Daly, Karen; Teagasc Walsh Fellowship Programme; Department for Agriculture Food and the Marine; RMIS 6837; 15/ICTAGRI 2 (Elsevier BV, 2020-04)
      Lime is a crucial soil conditioner to bring agricultural soils to optimum pH values for nutrient availability. Lime recommendations are typically determined in laboratory extractions, the most common being the “Shoemaker- McLean and Pratt” (SMP) buffer method, that requires carcinogenic reagents soon to be abolished under the EU legislation. As an alternative to wet chemistry, mid-infrared (MIR) spectroscopy has shown to be a cost-and time effective method at predicting soil properties. The capability and feasibility of diffuse reflectance infrared spectroscopy (DRIFTS) to predict lime requirement (LR) in tillage fields is examined. Samples from 41 cereal tillage fields (n = 655) are used to build a calibration for DRIFTS using partial least squares regression (PLSR). The samples were split into calibration set (31 fields, n=495) and validation set (10 fields, n= 160). After preprocessing with trim, smoothing and standard normal variate, a calibration model using 6 latent variables, provided R2 of 0.89 and root mean square error of cross-validation (RMSECV) of 1.56 t/ha. Prediction of all fields from the validation set resulted in R2 of 0.76 and root mean square error of prediction (RMSEP) of 1.68 t/ ha. The predictions of the single fields ranged from R2 values of 0.41 to 0.72, RMSEP of 0.48 to 4.2 t/ha and ratios of performance to inter-quartile distance (RPIQ) of 0.45 to 3.56. It was shown that the signals of soil constituents having an influence on the LR were picked up in the spectra and were identified in the loading weights of the PLSR. While the error is too high to predict the variability of LR within the field, MIR prediction using field averages provided a viable alternative to current laboratory methods for blanket spreading of lime on tillage fields.
    • Can technology help achieve sustainable intensification? Evidence from milk recording on Irish dairy farms

      Balaine, Lorraine; Dillon, Emma J.; Läpple, Doris; Lynch, John; Teagasc Walsh Fellowship Programme; Department of Agriculture, Food and the Marine; University of Oxford; 14/ 889; 205212/Z/16/Z (Elsevier BV, 2020-03)
      This article explores the potential of a farm technology to simultaneously improve farm efficiency and provide wider environmental and social benefits. Identifying these ‘win-win-win’ strategies and encouraging their widespread adoption is critical to achieve sustainable intensification. Using a nationally representative sample of 296 Irish dairy farms from 2015, propensity score matching is applied to measure the impact of milk recording on a broad set of farm sustainability indicators. The findings reveal that the technology enhances economic sustainability by increasing dairy gross margin and milk yield per cow. Furthermore, social sustainability is improved through a reduction in milk bulk tank somatic cell count (an indicator of animal health and welfare status). Conversely, milk recording (as it is currently implemented) does not impact farm environmental sustainability, represented by greenhouse gas emission efficiency. While the study shows that milk recording is a ‘win-win’ strategy, ways of improving current levels of utilisation are discussed so that milk recording achieves its ‘win-win-win’ potential in the future.
    • Evaluation of Phage Therapy in the Context of Enterococcus faecalis and Its Associated Diseases

      Bolocan, Andrei S.; Upadrasta, Aditya; de Almeida Bettio, Pedro H.; Clooney, Adam G.; Draper, Lorraine A.; Ross, R. Paul; Hill, Colin; Science Foundation Ireland; European Union; Janssen Biotech, Inc.; et al. (MDPI, 2019-04-20)
      Bacteriophages (phages) or bacterial viruses have been proposed as natural antimicrobial agents to fight against antibiotic-resistant bacteria associated with human infections. Enterococcus faecalis is a gut commensal, which is occasionally found in the mouth and vaginal tract, and does not usually cause clinical problems. However, it can spread to other areas of the body and cause life-threatening infections, such as septicemia, endocarditis, or meningitis, in immunocompromised hosts. Although E. faecalis phage cocktails are not commercially available within the EU or USA, there is an accumulated evidence from in vitro and in vivo studies that have shown phage efficacy, which supports the idea of applying phage therapy to overcome infections associated with E. faecalis. In this review, we discuss the potency of bacteriophages in controlling E. faecalis, in both in vitro and in vivo scenarios. E. faecalis associated bacteriophages were compared at the genome level and an attempt was made to categorize phages with respect to their suitability for therapeutic application, using orthocluster analysis. In addition, E. faecalis phages have been examined for the presence of antibiotic-resistant genes, to ensure their safe use in clinical conditions. Finally, the domain architecture of E. faecalis phage-encoded endolysins are discussed.
    • Urease and Nitrification Inhibitors—As Mitigation Tools for Greenhouse Gas Emissions in Sustainable Dairy Systems: A Review

      Byrne, Maria P.; Tobin, John T.; Forrestal, Patrick J.; Danaher, Martin; Nkwonta, Chikere; Richards, Karl; Cummins, Enda; Hogan, Sean A.; O'Callaghan, Tom; Department of Agriculture Food and the Marine; et al. (MDPI AG, 2020-07-27)
      Currently, nitrogen fertilizers are utilized to meet 48% of the total global food demand. The demand for nitrogen fertilizers is expected to grow as global populations continue to rise. The use of nitrogen fertilizers is associated with many negative environmental impacts and is a key source of greenhouse and harmful gas emissions. In recent years, urease and nitrification inhibitors have emerged as mitigation tools that are presently utilized in agriculture to prevent nitrogen losses and reduce greenhouse and harmful gas emissions that are associated with the use of nitrogen-based fertilizers. Both classes of inhibitor work by different mechanisms and have different physiochemical properties. Consequently, each class must be evaluated on its own merits. Although there are many benefits associated with the use of these inhibitors, little is known about their potential to enter the food chain, an event that may pose challenges to food safety. This phenomenon was highlighted when the nitrification inhibitor dicyandiamide was found as a residual contaminant in milk products in 2013. This comprehensive review aims to discuss the uses of inhibitor technologies in agriculture and their possible impacts on dairy product safety and quality, highlighting areas of concern with regards to the introduction of these inhibitor technologies into the dairy supply chain. Furthermore, this review discusses the benefits and challenges of inhibitor usage with a focus on EU regulations, as well as associated health concerns, chemical behavior, and analytical detection methods for these compounds within milk and environmental matrices.
    • Grazing of Dairy Cows in Europe—An In-Depth Analysis Based on the Perception of Grassland Experts

      van den Pol-van Dasselaar, Agnes; Hennessy, Deirdre; Isselstein, Johannes (MDPI AG, 2020-02-04)
      Grazing is inherently close to the nature of herbivores, but no longer applied everywhere in Europe. Therefore, the perception of grassland experts on the occurrence, importance, constraints, solutions and future of grazing of dairy cows was studied. The study builds on results from the European Grassland Federation Working Group Grazing in the period 2010–2019. Both surveys and focus group meetings were used. There is a clear trend of reduced grazing in Europe. Since grazing is valued by different stakeholders and provides many ecosystem services, solutions to the constraints to grazing must be found. Constraints can be divided into region specific constraints, farm specific constraints and farmer specific constraints. The solutions include developing new knowledge, bringing the knowledge already available to practice and rewarding farmers for grazing as a service to society. If grazing is not supported, it will further decline. However, a joined endeavour has the potential to make a significant difference in transforming grass-based production systems and stimulating grazing.
    • Assessing the Carbon Emission Driven by the Consumption of Carbohydrate-Rich Foods: The Case of China

      Yang, Xiaoke; Zhang, Zhihang; Chen, Huangyixin; Zhao, Rongrong; Xu, Zhongyue; Xie, Anguo; Chen, Qiuhua; Fujian Provincial Social Science Research Base for Ecological Civilization; Guangdong Planning Projects of Philosophy and Social Science; Natural Science Foundation of Guangdong Province; et al. (MDPI AG, 2019-03-28)
      Background: Carbohydrate-rich (CR) foods are essential parts of the Chinese diet. However, CR foods are often given less attention than animal-based foods. The objectives of this study were to analyze the carbon emissions caused by CR foods and to generate sustainable diets with low climate impact and adequate nutrients. Methods: Twelve common CR food consumption records from 4857 individuals were analyzed using K-means clustering algorithms. Furthermore, linear programming was used to generate optimized diets. Results: Total carbon emissions by CR foods was 683.38g CO2eq per day per capita, accounting for an annual total of 341.9Mt CO2eq. All individuals were ultimately divided into eight clusters, and none of the popular clusters were low carbon or nutrient sufficient. Optimized diets could reduce about 40% of carbon emissions compared to the average current diet. However, significant structural differences exist between the current diet and optimized diets. Conclusions: To reduce carbon emissions from the food chain, CR foods should be a research focus. Current Chinese diets need a big change to achieve positive environmental and health goals. The reduction of rice and wheat-based foods and an increase of bean foods were the focus of structural dietary change in CR food consumption.
    • The Use of High Performance Liquid Chromatography for the Characterization of the Unfolding and Aggregation of Dairy Proteins

      Gaspard, Sophie; Brodkorb, Andre; Dairy Levy Research Trust; Food Institutional Research Measure; Enterprise Ireland; Teagasc Walsh Fellowship Programme; MDDT6261; 08RDTMFRC650; CC20080001; 2012211 (Springer New York, 2019-07-25)
      High-performance liquid chromatography (HPLC) is routinely used to identify and characterize proteins. HPLC can help to understand protein aggregation processes in dairy products, which are induced by common industrial processing steps such as heat treatment. In this chapter, three complementary chromatographic methods are described, which are based on the principles of size exclusion and reversed-phase chromatography. These methods are used to determine the degree of denaturation and aggregation of proteins, and estimate the molecular weight of these aggregates.
    • Reproductive efficiency and survival of Holstein-Friesian cows of divergent Economic Breeding Index, evaluated under seasonal calving pasture-based management

      O'Sullivan, Morgan; Butler, Stephen; Pierce, K. M.; Crowe, M; O'Sullivan, K; Fitzgerald, R; Buckley, F (Elsevier for American Dairy Science Association, 2020-02)
      The objective of the current study was to examine phenotypic fertility performance and survival, and to gain insight into underlying factors that may contribute to greater fertility performance in 2 divergent genetic groups (GG) of Holstein-Friesian, selected using the Irish Economic Breeding Index (EBI). The GG were evaluated across 3 spring calving pasture-based feeding treatments (FT) over 4 yr. The 2 divergent GG were (1) high EBI; representative of the top 5% nationally (elite), and (2) EBI representative of the national average (NA). In each year, 90 elite and 45 NA cows were randomly allocated to 1 of 3 FT: control, lower grass allowance, and high concentrate. No interaction between GG and FT was observed for any of the measures of fertility investigated. The elite cows achieved significantly greater pregnancy rate to first service (+14.9 percentage points), and significantly greater pregnancy rates after 21, 42, and 84 d of breeding (+17.3, +15.2, and +9.6 percentage points, respectively) compared with NA. The number of services per cow was fewer for elite (1.57) compared with NA (1.80). The interval from mating start date to pregnancy was significantly shorter for elite cows compared with NA. The elite cows maintained greater mean body condition score than NA throughout the study (2.91 vs. 2.72), and had greater body condition score at calving, artificial insemination, and drying off compared with NA. The elite cows had greater mean circulating concentrations of insulin-like growth factor-1 compared with NA. No significant effect was observed of GG on commencement of luteal activity, or progesterone profile variables. Greater survival to the start of fifth lactation was observed for elite cows. The elite cows were 43% less likely to be culled than NA by the beginning of the fifth lactation. The results highlight the success of the Economic Breeding Index to deliver reproductive performance and longevity consistent with industry targets across a range of seasonal pasture-based FT. The results also clearly demonstrate the potential of appropriate genetic selection to reverse negative fertility trends incurred during previous decades of selection for milk production alone.
    • Influence of high-pressure processing on quality attributes of haddock and mackerel minces during frozen storage, and fishcakes prepared thereof

      Cropotova, Janna; Mozuraityte, Revilija; Standal, Inger Beate; Ojha, Shikha; Rustad, Turid; Tiwari, Brijesh K; JPI; RCN 259582/E50 (Elsevier BV, 2020-01)
    • Teagasc-EPA Soils and Subsoils Mapping Project Final Report Vol. II Maps & Statistics

      green, stuart; Fealy, Reamonn; Department of Agriculture, Food and the Marine; Department of Environment, Heritage and Local Government (2021-02-01)
      This report contains the maps and statistics for this project.
    • Leveraging Social Network Analysis for Characterizing Cohesion of Human-Managed Animals

      Vimalajeewa, Dixon; Balasubramaniam, Sasitharan; O'Brien, Bernadette; Kulatunga, Chamil; Berry, Donagh P.; Science Foundation Ireland; Department of Agriculture, Food and the Marine; European Union; 13/1A/1977; 16/RC/3835; et al. (Institute of Electrical and Electronics Engineers (IEEE), 2019-04)
      Social network analysis (SNA) is a technique to study behavioral dynamics within a social group. In SNA, it is an open question whether it is possible to characterize animal-level behaviors by using group-level information. Also, it was believed that the combined use of SNA would provide a more comprehensive understanding of social dynamics. In light of these two factors, here we explain an approach to evaluate animal importance to a group by considering the variability in group-level structural information, which is computed by joining the animal- and group-level SNA measures node centrality and network entropy, respectively. Moreover, two other metrics, animal social interaction range and nearest-neighbor frequency matrix, which represent a social affiliation of each animal within the group, are computed to help address the general challenges in graph-based SNA and, thereby, improve the precision of animal importance measures. Finally, we derive the joint distribution of animal importance of the group in detecting atypical social behaviors. The approach is tested using tracking data of dairy cows. The reliability of the derived animal importance was superior to the already existing animal importance measures. To illustrate the usability of the animal importance metric, a simulation study was conducted to identify sick and estrus animals in a group. The social affiliation of sick cows was less when compared to healthy cows. Also, their individual distributions of animal importance were shifted toward the left of the mean of the animal importance distributions of healthy cows. Consequently, the joint distribution of animal importance of the group exhibited a bimodal distribution with a left tailored shape. The behavior of cows in estrus was opposite to that of sick cows. Moreover, with the increasing number of sick and estrus cows in the group, respectively, the group entropy decreased with larger variance and slightly increased with less variance. Therefore, the entropy-based animal importance metric has superior performances when evaluating animal importance to the group compared to the existing metrics. It can be used for generating alerts for the early detection of atypical social behaviors associated with, for instance, animal health, veterinary, and welfare.
    • Why Dairy Farming And Silvopastoral Agroforestry Could Be The Perfect Match

      Irish Agroforestry Forum; Short, Ian; Department of Agriculture, Food and the Marine (Irish Farm Business, 2020)
      Could we be missing a trick here? Could silvopasture be a design solution to the environmental challenges facing farming? Can it be the ideal mechanism to combine agriculture, forestry and ecology with very positive outcomes for farmers? Well -designed silvopasture can help increase profits and productivity, animal, and soil health, diversify the farm business, buffer against increasingly variable weather, drought and flood risks while benefiting the environment, the water cycle and the carbon cycle.
    • Breed- and trait-specific associations define the genetic architecture of calving performance traits in cattle

      Purfield, Deirdre C; Evans, Ross D; Berry, Donagh; European Union; Science Foundation Ireland; 727213; 14/IA/2576); 16/RC/3835 (Oxford University Press (OUP), 2020-05-04)
      Reducing the incidence of both the degree of assistance required at calving, as well as the extent of perinatal mortality (PM) has both economic and societal benefits. The existence of heritable genetic variability in both traits signifies the presence of underlying genomic variability. The objective of the present study was to locate regions of the genome, and by extension putative genes and mutations, that are likely to be underpinning the genetic variability in direct calving difficulty (DCD), maternal calving difficulty (MCD), and PM. Imputed whole-genome single-nucleotide polymorphism (SNP) data on up to 8,304 Angus (AA), 17,175 Charolais (CH), 16,794 Limousin (LM), and 18,474 Holstein-Friesian (HF) sires representing 5,866,712 calving events from descendants were used. Several putative quantitative trait loci (QTL) regions associated with calving performance both within and across dairy and beef breeds were identified, although the majority were both breed- and trait-specific. QTL surrounding and encompassing the myostatin (MSTN) gene were associated (P < 5 × 10−8) with DCD and PM in both the CH and LM populations. The well-known Q204X mutation was the fifth strongest association with DCD in the CH population and accounted for 5.09% of the genetic variance in DCD. In contrast, none of the 259 segregating variants in MSTN were associated (P > × 10−6) with DCD in the LM population but a genomic region 617 kb downstream of MSTN was associated (P < 5 × 10−8). The genetic architecture for DCD differed in the HF population relative to the CH and LM, where two QTL encompassing ZNF613 on Bos taurus autosome (BTA)18 and PLAG1 on BTA14 were identified in the former. Pleiotropic SNP associated with all three calving performance traits were also identified in the three beef breeds; 5 SNP were pleiotropic in AA, 116 in LM, and 882 in CH but no SNP was associated with more than one trait within the HF population. The majority of these pleiotropic SNP were on BTA2 surrounding MSTN and were associated with both DCD and PM. Multiple previously reported, but also novel QTL, associated with calving performance were detected in this large study. These also included QTL regions harboring SNP with the same direction of allele substitution effect for both DCD and MCD thus contributing to a more effective simultaneous selection for both traits.
    • On-farm net benefit of genotyping candidate female replacement cattle and sheep

      Newton, J.E.; Berry, Donagh; Science Foundation Ireland; Department of Agriculture, Food and the Marine; European Union; 16/RC/3835; 727213 (Elsevier BV, 2020-12-07)
      The net benefit from investing in any technology is a function of the cost of implementation and the expected return in revenue. The objective of the present study was to quantify, using deterministic equations, the net monetary benefit from investing in genotyping of commercial females. Three case studies were presented reflecting dairy cows, beef cows and ewes based on Irish population parameters; sensitivity analyses were also performed. Parameters considered in the sensitivity analyses included the accuracy of genomic evaluations, replacement rate, proportion of female selection candidates retained as replacements, the cost of genotyping, the sire parentage error rate and the age of the female when it first gave birth. Results were presented as an annualised monetary net benefit over the lifetime of an individual, after discounting for the timing of expressions. In the base scenarios, the net benefit was greatest for dairy, followed by beef and then sheep. The net benefit improved as the reliability of the genomic evaluations improved and, in fact, a negative net benefit of genotyping was less frequent when the reliability of the genomic evaluations was high. The impact of a 10% point increase in genomic reliability was, however, greatest in sheep, followed by beef and then dairy. The net benefit of genotyping female selection candidates reduced as replacement rate increased. As genotyping costs increased, the net benefit reduced irrespective of the percentage of selection candidates kept, the replacement rate or even the population considered. Nonetheless, the association between the genotyping cost and the net benefit of genotyping differed by the percentage of selection candidates kept. Across all replacement rates evaluated, retaining 25% of the selection candidates resulted in the greatest net benefit when genotyping cost was low but the lowest net benefit when genotyping cost was high. Genotyping breakeven cost was non-linearly associated with the percentage of selection candidates retained, reaching a maximum when 50% of selection candidates were retained, irrespective of replacement rate, genomic reliability or the population. The genotyping breakeven cost was also non-linearly associated with replacement rate. The approaches outlined within provide the back-end framework for a decision support tool to quantify the net benefit of genotyping, once parameterised by the relevant population metrics.
    • Improving robustness and accuracy of predicted daily methane emissions of dairy cows using milk mid‐infrared spectra

      Vanlierde, Amélie; Dehareng, Frédéric; Gengler, Nicolas; Froidmont, Eric; McParland, Sinead; Kreuzer, Michael; Bell, Matthew; Lund, Peter; Martin, Cécile; Kuhla, Björn; et al. (Wiley, 2020-11-22)
      BACKGROUND A robust proxy for estimating methane (CH4) emissions of individual dairy cows would be valuable especially for selective breeding. This study aimed to improve the robustness and accuracy of prediction models that estimate daily CH4 emissions from milk Fourier transform mid‐infrared (FT‐MIR) spectra by (i) increasing the reference dataset and (ii) adjusting for routinely recorded phenotypic information. Prediction equations for CH4 were developed using a combined dataset including daily CH4 measurements (n = 1089; g d−1) collected using the SF6 tracer technique (n = 513) and measurements using respiration chambers (RC, n = 576). Furthermore, in addition to the milk FT‐MIR spectra, the variables of milk yield (MY) on the test day, parity (P) and breed (B) of cows were included in the regression analysis as explanatory variables. RESULTS Models developed based on a combined RC and SF6 dataset predicted the expected pattern in CH4 values (in g d−1) during a lactation cycle, namely an increase during the first weeks after calving followed by a gradual decrease until the end of lactation. The model including MY, P and B information provided the best prediction results (cross‐validation statistics: R2 = 0.68 and standard error = 57 g CH4 d−1). CONCLUSIONS The models developed accounted for more of the observed variability in CH4 emissions than previously developed models and thus were considered more robust. This approach is suitable for large‐scale studies (e.g. animal genetic evaluation) where robustness is paramount for accurate predictions across a range of animal conditions. © 2020 Society of Chemical Industry
    • A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra

      Soyeurt, H.; Grelet, C.; McParland, Sinead; Calmels, M.; Coffey, M.; Tedde, A.; Delhez, P.; Dehareng, F.; Gengler, N.; European Union; et al. (American Dairy Science Association, 2020-10-22)
      Lactoferrin (LF) is a glycoprotein naturally present in milk. Its content varies throughout lactation, but also with mastitis; therefore it is a potential additional indicator of udder health beyond somatic cell count. Condequently, there is an interest in quantifying this biomolecule routinely. First prediction equations proposed in the literature to predict the content in milk using milk mid-infrared spectrometry were built using partial least square regression (PLSR) due to the limited size of the data set. Thanks to a large data set, the current study aimed to test 4 different machine learning algorithms using a large data set comprising 6,619 records collected across different herds, breeds, and countries. The first algorithm was a PLSR, as used in past investigations. The second and third algorithms used partial least square (PLS) factors combined with a linear and polynomial support vector regression (PLS + SVR). The fourth algorithm also used PLS factors, but included in an artificial neural network with 1 hidden layer (PLS + ANN). The training and validation sets comprised 5,541 and 836 records, respectively. Even if the calibration prediction performances were the best for PLS + polynomial SVR, their validation prediction performances were the worst. The 3 other algorithms had similar validation performances. Indeed, the validation root mean squared error (RMSE) ranged between 162.17 and 166.75 mg/L of milk. However, the lower standard deviation of cross-validation RMSE and the better normality of the residual distribution observed for PLS + ANN suggest that this modeling was more suitable to predict the LF content in milk from milk mid-infrared spectra (R2v = 0.60 and validation RMSE = 162.17 mg/L of milk). This PLS +ANN model was then applied to almost 6 million spectral records. The predicted LF showed the expected relationships with milk yield, somatic cell score, somatic cell count, and stage of lactation. The model tended to underestimate high LF values (higher than 600 mg/L of milk). However, if the prediction threshold was set to 500 mg/L, 82% of samples from the validation having a content of LF higher than 600 mg/L were detected. Future research should aim to increase the number of those extremely high LF records in the calibration set.
    • Comparative Genomics Analysis of Lactobacillus ruminis from Different Niches

      Wang, Shuo; Yang, Bo; Ross, R. Paul; STANTON, CATHERINE; Zhao, Jianxin; Zhang, Hao; Chen, Wei; National Natural Science Foundation of China; Jiangsu Province; 31771953; et al. (MDPI AG, 2020-01-08)
      Lactobacillus ruminis is a commensal motile lactic acid bacterium living in the intestinal tract of humans and animals. Although a few genomes of L. ruminis were published, most of them were animal derived. To explore the genetic diversity and potential niche-specific adaptation changes of L. ruminis, in the current work, draft genomes of 81 L. ruminis strains isolated from human, bovine, piglet, and other animals were sequenced, and comparative genomic analysis was performed. The genome size and GC content of L. ruminis on average were 2.16 Mb and 43.65%, respectively. Both the origin and the sampling distance of these strains had a great influence on the phylogenetic relationship. For carbohydrate utilization, the human-derived L. ruminis strains had a higher consistency in the utilization of carbon source compared to the animal-derived strains. L. ruminis mainly increased the competitiveness of niches by producing class II bacteriocins. The type of clustered regularly interspaced short palindromic repeats /CRISPR-associated (CRISPR/Cas) system presented in L. ruminis was mainly subtype IIA. The diversity of CRISPR/Cas locus depended on the high denaturation of spacer number and sequence, although cas1 protein was relatively conservative. The genetic differences in those newly sequenced L. ruminis strains highlighted the gene gains and losses attributed to niche adaptations.