Impact of computers on sensory evaluation: past, present and future

Developments in hardware and software in the last decade have dramatically changed the role of computers in sensory analysis. Besides data-entry and data-analysis, personal computers are used more and more for data-collection, experimental design and panel-management. Tests are prepared on the personal computer, the questions are displayed on screens in the tasting booths, the subjects can enter their responses directly and the results can be available instantaneously. In the last five years, several systems for automated sensory analysis have been developed. In the coming years, computers will become more powerful, cheaper, faster, and will have more memory. Although it is not clear at this moment which operating system will become the standard for the next decade, the software will certainly be more user-friendly. Graphical-user-interfaces will change the way we interact with the computer. New approaches to software development, like object-oriented programming, artifical intelligence and relational database management systems will make it possible to use the computer for more aspects of sensory evaluation. It is important to identify the different tasks in the laboratory that can be automated and to look for the right tools to use. In view of the developments in the last decade, it is not advisable to wait for the ultimate solution.     

Multibreed genomic evaluation for production traits of dairy cattle in the United States using single-step genomic best linear unbiased predictor

Official multibreed genomic evaluations for dairy cattle in the United States are based on multibreed BLUP evaluation followed by single-breed estimation of SNP effects. Single-step genomic BLUP (ssGBLUP) allows the straight computation of genomic (G)EBV in a multibreed context. This work aimed to develop ssGBLUP multibreed genomic predictions for US dairy cattle using the algorithm for proven and young (APY) to compute the inverse of the genomic relationship matrix. Only purebred Ayrshire (AY), Brown Swiss (BS), Guernsey (GU), Holstein (HO), and Jersey (JE) animals were considered. A 3-trait model with milk (MY), fat (FY), and protein (PY) yields was applied using about 45 million phenotypes recorded from January 2000 to June 2020. The whole data set included about 29.5 million animals, of which almost 4 million were genotyped. All the effects in the model were breed specific, and breed was also considered as fixed unknown parent groups. Evaluations were done for (1) each single breed separately (single); (2) HO and JE together (HO_JE); (3) AY, BS, and GU together (AY_BS_GU); (4) all the 5 breeds together (5_BREEDS). Initially, 15k core animals were used in APY for AY_BS_GU and 5_BREEDS, but larger core sets with more animals from the least represented breeds were also tested. The HO_JE evaluation had a fixed set of 30k core animals, with an equal representation of the 2 breeds, whereas HO and JE single-breed analysis involved 15k core animals. Validation for cows was based on correlations between adjusted phenotypes and (G)EBV, whereas for bulls on the regression of daughter yield deviations on (G)EBV. Because breed was correctly considered in the model, BLUP results for single and multibreed analyses were the same. Under ssGBLUP, predictability and reliability for AY, BS, and GU were on average 7% and 2% lower in 5_BREEDS compared with single-breed evaluations, respectively. However, validation parameters for these 3 breeds became better than in the single-breed evaluations when 45k animals were included in the core set for 5_BREEDS. Evaluations for Holsteins were more stable across scenarios because of the greatest number of genotyped animals and amount of data. Combining AY, BS, and GU into one evaluation resulted in predictions similar to the ones from single breed, especially when using about 30k core animals in APY. The results showed that single-step large-scale multibreed evaluations are computationally feasible, but fine tuning is needed to avoid a reduction in reliability when numerically dominant breeds are combined. Having evaluations for AY, BS, and GU separated from HO and JE may reduce inflation of GEBV for the first 3 breeds.     

Invited Review: Reliability of genomic predictions for North American Holstein bulls

Genetic progress will increase when breeders examine genotypes in addition to pedigrees and phenotypes. Genotypes for 38,416 markers and August 2003 genetic evaluations for 3,576 Holstein bulls born before 1999 were used to predict January 2008 daughter deviations for 1,759 bulls born from 1999 through 2002. Genotypes were generated using the Illumina BovineSNP50 BeadChip and DNA from semen contributed by US and Canadian artificial-insemination organizations to the Cooperative Dairy DNA Repository. Genomic predictions for 5 yield traits, 5 fitness traits, 16 conformation traits, and net merit were computed using a linear model with an assumed normal distribution for marker effects and also using a nonlinear model with a heavier tailed prior distribution to account for major genes. The official parent average from 2003 and a 2003 parent average computed from only the subset of genotyped ancestors were combined with genomic predictions using a selection index. Combined predictions were more accurate than official parent averages for all 27 traits. The coefficients of determination (R²) were 0.05 to 0.38 greater with nonlinear genomic predictions included compared with those from parent average alone. Linear genomic predictions had R² values similar to those from nonlinear predictions but averaged just 0.01 lower. The greatest benefits of genomic prediction were for fat percentage because of a known gene with a large effect. The R² values were converted to realized reliabilities by dividing by mean reliability of 2008 daughter deviations and then adding the difference between published and observed reliabilities of 2003 parent averages. When averaged across all traits, combined genomic predictions had realized reliabilities that were 23% greater than reliabilities of parent averages (50 vs. 27%), and gains in information were equivalent to 11 additional daughter records. Reliability increased more by doubling the number of bulls genotyped than the number of markers genotyped. Genomic prediction improves reliability by tracing the inheritance of genes even with small effects.     

Invited review: A perspective on the future of genomic selection in dairy cattle

Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of “single-step” methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.     

Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada

Nearly 57,000 single-nucleotide polymorphisms (SNP) genotyped with the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) were investigated to determine usefulness of the associated SNP for genomic prediction. Genotypes were obtained for 12,591 bulls and cows, and SNP were selected based on 5,503 bulls with genotypes from a larger set of SNP. The following SNP were deleted: 6,572 that were monomorphic, 3,213 with scoring problems (primarily because of poor definition of clusters and excess number of clusters), and 3,649 with a minor allele frequency of <2%. Number of SNP for each minor allele frequency class (≥2%) was fairly uniform (777 to 1,004). For 5 contiguous SNP assigned to chromosome 7, no bulls were heterozygous, which indicated that those SNP are actually on the nonpseudoautosomal portion of the X chromosome. Another 178 SNP that were not assigned to a chromosome but that had many fewer heterozygotes than expected were also assigned to the X chromosome. Existence of Hardy-Weinberg equilibrium was investigated by comparing observed with expected heterozygosity. For 11 SNP, the observed percentage of heterozygous individuals differed from the expected by >15%; therefore, those SNP were deleted. For 2,628 SNP, the genotype at another SNP was highly correlated (i.e., genotypes were identical for >99.5% of bulls), and those were deleted. After edits, 40,874 SNP remained. A parent-progeny conflict was declared when the genotypes were alternate homozygotes. Mean number of conflicts was 2.3 when pedigree was correct and 2,411 when it was incorrect. The sire was genotyped for >93% of animals. Maternal grandsire genotype was similarly checked; however, because alternate homozygotes could be valid, a conflict threshold of 16% was used to indicate a need for further investigation. Genotyping consistency was investigated for 21 bulls genotyped twice with differences primarily from SNP that were not scored in one of the genotypes. Concordance for readable SNP was extremely high (99.96-100%). Thousands of SNP that were polymorphic in Holsteins were monomorphic in Jerseys or Brown Swiss, which indicated that breed-specific SNP sets are required or that all breeds need to be considered in the SNP selection process. Genotypes from the Illumina BovineSNP50 BeadChip are of high accuracy and provide the basis for genomic evaluations in the United States and Canada.     

Multiple-trait genomic evaluation of linear type traits using genomic and phenotypic data in US Holsteins

Currently, the USDA uses a single-trait (ST) model with several intermediate steps to obtain genomic evaluations for US Holsteins. In this study, genomic evaluations for 18 linear type traits were obtained with a multiple-trait (MT) model using a unified single-step procedure. The phenotypic type data on up to 18 traits were available for 4,813,726 Holsteins, and single nucleotide polymorphism markers from the Illumina BovineSNP50 genotyping Beadchip (Illumina Inc., San Diego, CA) were available on 17,293 bulls. Genomic predictions were computed with several genomic relationship matrices (G) that assumed different allele frequencies: equal, base, current, and current scaled. Computations were carried out with ST and MT models. Procedures were compared by coefficients of determination (R²) and regression of 2004 prediction of bulls with no daughters in 2004 on daughter deviations of those bulls in 2009. Predictions for 2004 also included parent averages without the use of genomic information. The R² for parent averages ranged from 10 to 34% for ST models and from 12 to 35% for MT models. The average R² for all G were 34 and 37% for ST and MT models, respectively. All of the regression coefficients were <1.0, indicating that estimated breeding values in 2009 of 1,307 genotyped young bulls’ parents tended to be biased. The average regression coefficients ranged from 0.74 to 0.79 and from 0.75 to 0.80 for ST and MT models, respectively. When the weight for the inverse of the numerator relationship matrix (A⁻¹) for genotyped animals was reduced from 1 to 0.7, R² remained almost identical while the regression coefficients increased by 0.11-0.26 and 0.12-0.23 for ST and MT models, respectively. The ST models required about 5 s per iteration, whereas MT models required 3 (6) min per iteration for the regular (genomic) model. The MT single-step approach is feasible for 18 linear type traits in US Holstein cattle. Accuracy for genomic evaluation increases when switching ST models to MT models. Inflation of genomic evaluations for young bulls could be reduced by choosing a small weight for the A⁻¹ for genotyped bulls.     

Use of a single-step approach for integrating foreign information into national genomic evaluation in Holstein cattle

The use of multi-trait across-country evaluation (MACE) and the exchange of genomic information among countries allows national breeding programs to combine foreign and national data to increase the size of the training populations and potentially increase accuracy of genomic prediction of breeding values. By including genotyped and nongenotyped animals simultaneously in the evaluation, the single-step genomic BLUP (GBLUP) approach has the potential to deliver more accurate and less biased genomic evaluations. A single-step genomic BLUP approach, which enables integration of data from MACE evaluations, can be used to obtain genomic predictions while avoiding double-counting of information. The objectives of this study were to apply a single-step approach that simultaneously includes domestic and MACE information for genomic evaluation of workability traits in Canadian Holstein cattle, and compare the results obtained with this methodology with those obtained using a multi-step approach (msGBLUP). By including MACE bulls in the training population, msGBLUP led to an increase in reliability of genomic predictions of 4.8 and 15.4% for milking temperament and milking speed, respectively, compared with a traditional evaluation using only pedigree and phenotypic information. Integration of MACE data through a single-step approach (ssGBLUP_IM) yielded the highest reliabilities compared with other considered methods. Integration of MACE data also helped reduce bias of genomic predictions. When using ssGBLUP_IM, the bias of genomic predictions decreased by half compared with msGBLUP using domestic and MACE information. Therefore, the reliability and bias of genomic predictions for both traits improved substantially when a single-step approach was used for evaluation compared with a multi-step approach. The use of a single-step approach with integration of MACE information provides an alternative to the current method used in Canadian genomic evaluations.     

Science of nutrition: past, present, future

The article describes the history of development of science of nutrition in Russia, the history of creating and development of Institute of Nutrition RAMS.     

Lysine fortification: past, present, and future

Fortification with lysine to improve the protein value of human diets that are heavily based on cereals has received support from the results of these recent studies [1,2]. Support also comes from examination of average food and nutrient availability data derived from food balance sheets. Whereas nutritional status is influenced by the nutrient content of foods consumed in relation to need, the requirements for protein and amino acids are influenced by many additional factors [10, 12, 14, 28, 29]. These include age, sex, body size, physical activity, growth, pregnancy and lactation, infection, and the efficiency of nutrient utilization. Even if the immune response was influenced by the added lysine, adequate water and basic sanitation would remain essential. Acute and chronic undernutrition and most micronutrient deficiencies primarily affect poor and deprived people who do not have access to food of adequate nutritional value, live in unsanitary environments without access to clean water and basic services, and lack access to appropriate education and information [30]. A further variable is the possible interaction between protein and food energy availability [31]. This could affect the protein value of diets when food energy is limiting to a significant degree. Thus, the additional effects of food energy deficiency on protein utilization could well be superimposed on the very poorest. The improvement of dietary diversity must be the long-term aim, with dietary fortification considered only a short-term solution. The former should take place as wealth improves and the gaps between rich and poor diminish. Although such changes are taking place, they are highly uneven. Over the last several decades, increases have occurred in the availability of food energy, total protein, and animal protein for both developed and developing countries. However, for the very poorest developing countries over the same period, changes have been almost nonexistent, and the values for some nutritional indicators have even declined. For estimated lysine value, the developed countries showed increases in per capita availability from 5,400 to 6,167 mg per day and the developing countries from 2,400 to 3,454 mg per day, while in contrast, the very poorest countries remained static at about 2,400 to 2,500 mg per day. Thus, although lysine fortification may be theoretically only a short-term solution, in the very poorest countries changes in wealth such that dietary diversity and lysine availability may increase by natural progression remain remote. If we can justify using lysine to fortify animal feed in the rich regions of the world for economic gain, perhaps we should now consider adding lysine to the flour consumed by the deprived people in the poorest regions of the world to improve both their nutrition and their resistance to disease.     

Polyfluorinated compounds: past, present, and future

Interest and concern about polyfluorinated compounds (PFCs), such as perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), and an increasing number of other related compounds is growing as more is learned about these ubiquitous anthropogenic substances. Many of these compounds can be toxic, and they are regularly found in the blood of animals and humans worldwide. A great deal of research has been conducted in this area, but a surprising amount remains unknown about their distribution in the environment and how people ultimately become exposed. The utility of these compounds seems to ensure their continued use in one form or another for the foreseeable future, presenting a long-term challenge to scientists, industry leaders, and public health officials worldwide.     

Multiple trait genomic evaluation of conception rate in Holsteins

A national data set of artificial inseminations in US Holsteins was used to obtain genetic evaluations for conception rate (CR). The objective of this study was to investigate the feasibility and resulting accuracy from using all available phenotypic, pedigree, and genomic information. Evaluations were performed by regular BLUP or by BLUP with the traditional pedigree and genomic relationships combined in a unified single-step procedure (SSP). Genetic parameters of CR in the first 3 parities were estimated with data from New York State only. Heritability estimates were around 2% and genetic correlations between CR in different parities were >0.73. The R² obtained with the SSP were almost twice as large as those achieved with regular BLUP. Computing the SSP took 2 h, and it was 33% slower than a regular BLUP. A multiple-trait evaluation of CR using the SSP is both possible and advantageous.     

Short communication: The role of genotypes from animals without phenotypes in single-step genomic evaluations

In a 2-step genomic system, genotypes of animals without phenotypes do not influence genomic prediction of other animals, but that might not be the case in single-step systems. We investigated the effects of including genotypes from culled bulls on the reliability of genomic predictions from single-step evaluations. Four scenarios with a constant amount of phenotypic information and increasing numbers of genotypes from culled bulls were simulated and compared with respect to prediction reliability. With increasing numbers of genotyped culled bulls, there was a corresponding increase in prediction reliability. For instance, in our simulation scenario the reliability for selection candidates was twice as large when all culled bulls from the last 4 generations were included in the analysis. Single-step evaluations imply the imputation of all nongenotyped animals in the pedigree. We showed that this imputation was increasingly more accurate as increasingly more genotypic information from the culled bulls was taken into account. This resulted in higher prediction reliabilities. The extent of the benefit from including genotypes from culled bulls might be more relevant for small populations with low levels of reliabilities.     

Selection and management of DNA markers for use in genomic evaluation

To facilitate routine genomic evaluation, a database was constructed to store genotypes for 50,972 single nucleotide polymorphisms (SNP) from the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Multiple samples per animal are allowed. All SNP genotypes for a sample are stored in a single row. An indicator specifies whether the genotype for a sample was selected for use in genomic evaluation. Samples with low call rates or pedigree conflicts are designated as unusable. Among multiple samples that qualify for use in genomic evaluation, the one with the highest call rate is designated as usable. When multiple samples are stored for an animal, a composite is formed during extraction by using SNP genotypes from other samples to replace missing genotypes. To increase the number of SNP available, scanner output for approximately 19,000 samples was reprocessed. Any SNP with a minor allele frequency of ≥1% for Holsteins, Jerseys, or Brown Swiss was selected, which was the primary reason that the number of SNP used for USDA genomic evaluations increased. Few parent-progeny conflicts (≤1%) and a high call rate (≥90%) were additional requirements that eliminated 2,378 SNP. Because monomorphic SNP did not degrade convergence during estimation of SNP effects, a single set of 43,385 SNP was adopted for all breeds. The use of a database for genotypes, detection of conflicts as genotypes are stored, online access for problem resolution, and use of a single set of SNP for genomic evaluations have simplified tracking of genotypes and genomic evaluation as a routine and official process.     

Wavefront technology: past, present and future.

After outlining what is meant by wavefront aberration, the history of the field of wavefront technology is sketched and methods for measuring ocular wavefront aberration are briefly described. The variations in aberration of the normal eye with the individual and their pupil size, accommodation and age are summarised. Potential contact lens applications are outlined, including the design and on-eye performance of single-vision lenses, lenses for presbyopes and keratoconics, orthokeratology, tear film studies, and the design and performance of customised contact lenses intended to minimise residual lens-eye wavefront error.     

Smoke-free air policies: past, present and future

Smoke-free policies have been an important tobacco control intervention. As recently as 20 years ago, few communities required workplaces and hospitality venues to be smoke-free, but today approximately 11% of the world's population live in countries with laws that require these places to be smoke-free. This paper briefly summarises important milestones in the history of indoor smoke-free policies, the role of scientific research in facilitating their adoption, a framework for smoke-free policy evaluation and industry efforts to undermine regulations. At present, smoke-free policies centre on workplaces, restaurants and pubs. In addition, many jurisdictions are now beginning to implement policies in outdoor areas and in shared multiunit housing settings. The future of smoke-free policy development depends on credible scientific data that documents the health risks of secondhand smoke exposure. Over the next 20 years smoke-free policies will very likely extend to outdoor and private areas, and changes in the types of tobacco products that are consumed may also have implications for the nature and scope of the smoke-free policies of the future.     

Preservation and fermentation: past,present and future

Preservation of food and beverages resulting from fermentation has been an effective form of extending the shelf-life of foods for millennia. Traditionally, foods were preserved through naturally occurring fermentations, however, modern large scale production generally now exploits the use of defined strain starter systems to ensure consistency and quality in the final product. This review will mainly focus on the use of lactic acid bacteria (LAB) for food improvement, given their extensive application in a wide range of fermented foods. These microorganisms can produce a wide variety of antagonistic primary and secondary metabolites including organic acids, diacetyl, CO2 and even antibiotics such as reuterocyclin produced by Lactobacillus reuteri. In addition, members of the group can also produce a wide range of bacteriocins, some of which have activity against food pathogens such as Listeria monocytogenes and Clostridium botulinum. Indeed, the bacteriocin nisin has been used as an effective biopreservative in some dairy products for decades, while a number of more recently discovered bacteriocins, such as lacticin 3147, demonstrate increasing potential in a number of food applications. Both of these lactococcal bacteriocins belong to the lantibiotic family of posttranslationally modified bacteriocins that contain lanthionine, beta-methyllanthionine and dehydrated amino acids. The exploitation of such naturally produced antagonists holds tremendous potential for extension of shelf-life and improvement of safety of a variety of foods.     

Protein deposition on contact lenses: The past, the present, and the future

Proteins are a key component in body fluids and adhere to most biomaterials within seconds of their exposure. The tear film consists of more than 400 different proteins, ranging in size from 10 to 2360 kDa, with a net charge of pH 1-11. Protein deposition rates on poly-2-hydroxyethyl methacrylate (pHEMA) and silicone hydrogel soft contact lenses have been determined using a number of ex vivo and in vitro experiments. Ionic, high water pHEMA-based lenses attract the highest amount of tear film protein (1300 μg/lens), due to an electrostatic attraction between the material and positively charged lysozyme. All other types of pHEMA-based lenses deposit typically less than 100 μg/lens. Silicone hydrogel lenses attract less protein than pHEMA-based materials, with <10 μg/lens for non-ionic and up to 34 μg/lens for ionic materials. Despite the low protein rates on silicone hydrogel lenses, the percentage of denatured protein is typically higher than that seen on pHEMA-based lenses. Newer approaches incorporating phosphorylcholine, polyethers or hyaluronic acid into potential contact lens materials result in reduced protein deposition rates compared to current lens materials.