Udder, Claw, and Reproductive Health in Genomic Selection of the Czech Holstein.

The aim of this study was to construct an enhanced selection index using the genomic and economic parameters of new health disorders and current production and functional traits. Genomic evaluation for the incidence of clinical mastitis (CM), three claw disease traits, retained placenta (RET), metritis (MET), and cystic ovaries (CYS) was performed using linear animal models based on producer-recorded data. Good correlations among the health disorders were found, and their heritability estimates did not exceed 7%. Economic weights (EWs) for the health disorders were EUR -132.10 for CM, EUR -128.87 for overall claw diseases, EUR -52.10 for RET, EUR -80.48 for MET, and EUR -16.16 for CYS. These EWs indicate changes in the present value of the annual profit per cow when increasing the incidence of the traits by one case per cow year. Selection using the enhanced index resulted in favourable responses for most of the new health disorders (e.g., -0.001 and -0.006 cases of RET and MET per cow year, respectively), and also in the current breeding objective traits (+49 kg of milk, -0.02% of calf losses). An index contribution of 7% for the new health disorders was assessed as acceptable for the breeders.

Evaluating the effect of the COVID-19 pandemic on medical waste disposal using preference selection index with CRADIS in a fuzzy environment.

The COVID-19 pandemic has caused a surge in essential medical supplies usage, leading to a notable increase in medical waste generation. Consequently, extensive research has focused on sustainable disposal methods to handle used medical equipment safely. Given the necessity to evaluate these methods considering qualitative and quantitative criteria, this falls within the realm of multi-criteria decision-making (MCDM). This study introduces a framework for selecting the most suitable medical waste treatment methods, taking into account economic, technological, environmental, and social aspects. Sixteen criteria were assessed using the Fuzzy Preference Selection Index (F-PSI) to determine the optimal waste disposal approach. Additionally, the Fuzzy Compromise Ranking of Alternatives from Distance to Ideal Solution (F-CRADIS) method was employed to evaluate nine technologies for medical waste disposal. Notably, disinfection efficiency emerged as the most crucial criterion, with autoclaving identified as the preferred method for medical waste treatment. A practical case study conducted in Sivas, Turkey, validates the feasibility of these strategies. Multiple sensitivity analyses were performed to ensure the stability and reliability of the proposed approach.

Enhancing grapevine breeding efficiency through genomic prediction and selection index.

Grapevine (Vitis vinifera) breeding reaches a critical point. New cultivars are released every year with resistance to powdery and downy mildews. However, the traditional process remains time-consuming, taking 20-25 years, and demands the evaluation of new traits to enhance grapevine adaptation to climate change. Until now, the selection process has relied on phenotypic data and a limited number of molecular markers for simple genetic traits such as resistance to pathogens, without a clearly defined ideotype, and was carried out on a large scale. To accelerate the breeding process and address these challenges, we investigated the use of genomic prediction, a methodology using molecular markers to predict genotypic values. In our study, we focused on 2 existing grapevine breeding programs: Rosé wine and Cognac production. In these programs, several families were created through crosses of emblematic and interspecific resistant varieties to powdery and downy mildews. Thirty traits were evaluated for each program, using 2 genomic prediction methods: Genomic Best Linear Unbiased Predictor and Least Absolute Shrinkage Selection Operator. The results revealed substantial variability in predictive abilities across traits, ranging from 0 to 0.9. These discrepancies could be attributed to factors such as trait heritability and trait characteristics. Moreover, we explored the potential of across-population genomic prediction by leveraging other grapevine populations as training sets. Integrating genomic prediction allowed us to identify superior individuals for each program, using multivariate selection index method. The ideotype for each breeding program was defined collaboratively with representatives from the wine-growing sector.

Characteristics of restricted selection indices and geometrical interpretation of restricted breeding values.

Restricted selection is used to control genetic changes in one or more characters. Three main selection indices are adopted for this purpose. First, Kempthorne's index is used to maximize aggregate breeding value (BV) with changes in some traits restricted to zero; second, Harville's index is used to maximize aggregate BV with proportional changes for some traits; and third, Yamada's index is mathematically used to achieve the relative desired changes for all traits. Kempthorne's index is equivalent to Harville's index. However, the relationship between Kempthorne's and Yamada's indices has not been clarified. In addition, the characteristics of restricted selection indices and the relationship between BV and restricted BV (RBV) are also unknown. The aim of this study was to clarify the characteristics of restricted selection indices and describe the relationship between BV and RBV by using linear algebra and geometric techniques, respectively. First, I proved that Yamada's index is part of Kempthorne's index. Second, I investigated the relationship between BVs that were estimated using an ordinary selection index (EBVs) and RBVs estimated using a restricted selection index (ERBVs) and proved that the ERBVs of the restricted traits are proportional to the relative desired changes. Third, I proved that RBV is represented by a linear function of BV and geometrically represented the relationship between BV and RBV. In this study, new findings on restricted selection indices and RBV were obtained. This useful clarification of the relationship between BV and RBV will make it possible to evaluate the response to selection using not only a restricted selection index, but also a restricted BLUP in computer simulation studies.

Designing an early selection morphological traits index for reproductive efficiency in Pura Raza Española mares.

The low rate of reproductive efficiency in horses may be linked to the equine industry's practice of maintaining breeding stock that stands out for its athletic or morphological performance but exhibits poor reproductive efficiency. In this study, the age at first foaling, age at last foaling, interval between first and second foaling, average interval between foaling, foaling number and reproductive efficiency, and their relationship with the morphological records in 19,758 Pura Raza Española (PRE) mares were analyzed. After a partial least squares analysis height at withers, lateral hock angle, dorsal-sternal diameter, perimeter of anterior cannon bone, angle of shoulder, thoracic perimeter, hip-stifle distance, and angle of croup were the most important traits related with reproductive traits in PRE mares. A multivariate animal model with both morphological and reproductive traits was applied, including age, geographical area, coat color, and average stud size in the decade of the mare's first foaling. The results indicate that reproductive selection is feasible, and is enhanced by the use of morphological traits, given the moderate to high magnitudes of heritability values in both types of traits, which oscillated between 0.1 (interval between first and second foaling) and 0.95 (height at withers). The resulting genetic parameters were used to develop a series of selection indexes based on morphological or morphological and reproductive combination traits to improve reproductive efficiency traits in PRE mares and thus compute the expected genetic response (EGR) for the different strategies. The increase in EGR, when comparing EGR using only reproductive traits as selection criteria vs. using a combined index of both morphological and reproductive traits, oscillated between 4.0% for the age at first foaling to 46.8% for the interval between first and second foaling. In addition, two precocity indexes showed positive EGR when the age at last foaling and the interval between first and second foaling, both with and without morphological traits, were used as selection criteria. Therefore, this analysis reveals that the preselection of reproductive traits based on morphological traits is possible in PRE mares. Ultimately, this knowledge will help breeders achieve genetic progress in reproductive traits, leading to healthier and more successful breeding outcomes in horses.

Historically in livestock production, employing combinations of traits as selection criteria for indirect selection of related traits has been a challenging task, particularly when this implies selection for reproductive traits based on the animal morphology. However, if the decision about animal selection is based on morphological traits that are quick and easy to obtain, in addition to early reproductive traits, selection responses can be improved and made earlier. This is particularly significant in sport horse breeds like the Pura Raza Española horse, which is primarily used for dressage competitions. Mares belonging to this breed commonly engage in several years of competition before transitioning to breeding, without the breeders having prior knowledge of their reproductive efficiency. Nonetheless, the availability of existing morphological information enables us to make informed decisions in this regard. While a selection index using morphology alone would not yield as good a response as direct selection for reproductive traits, there are cases, such as age at last foaling, where the correlated response can be very high. Our study further illustrates a substantial increase in selection response when morphological and reproductive traits are jointly included as selection criteria, with the aim of enhancing reproductive efficiency.

Identification of High-Yielding Genotypes of Barley in the Warm Regions of Iran.

One of the most important effects of climatic changes is increasing temperatures and expanding water deficit stress in tropical and subtropical regions. As the fourth most important cereal crop, barley (Hordeum vulgare L.) is crucial for food and feed security, as well as for a sustainable agricultural system. The present study investigates 56 promising barley genotypes, along with four local varieties (Norooz, Oxin, Golchin, and Negin) in four locations to identify high-yielding and adapted genotypes in the warm climate of Iran. Genotypes were tested in an alpha lattice design with six blocks, which were repeated three times. Traits measured were the number of days to heading and maturity, plant height, thousand kernels weight, and grain yield. A combined analysis of variance showed the significant effects of genotypes (G), environments (E), and their interaction (GEI) on all measured traits. Application of the additive main-effect and multiplicative interaction (AMMI) model to the grain yield data showed that GEI was divided into three significant components (IPCAs), and each accounted for 50.93%, 30.60%, and 18.47%, respectively. Two selection indices [Smith-Hazel (SH) and multiple trait selection index (MTSI)] identified G18, G24, G29, and G57 as desirable genotypes at the four test locations. Using several BLUP-based indices, such as the harmonic mean of genotypic values (HMGV), the relative performance of genotypic values (RPGV), and the harmonic mean of the relative performance of genotypic values (HMRPGV), genotypes G6, G11, G22, G24, G29, G38, G52, and G57 were identified as superior genotypes. The application of GGE analysis identified G6, G24, G29, G52, and G57 as the high-yielding and most stable genotypes. Considering all statistical models, genotypes G24, G29, and G57 can be used, as they are well-adapted to the test locations in warm regions of Iran.

Muscle growth affects the metabolome of the pectoralis major muscle in red-winged tinamou (Rhynchotus rufescens).

The aim of the present study was to identify and quantify the metabolites (metabolome analysis) of the pectoralis major muscle in male red-winged tinamou (Rhynchotus rufescens) selected for growth traits. A selection index was developed for females [body weight (BW), chest circumference (CC), and thigh circumference (TC)] and males [BW, CC, TC, semen volume, and sperm concentration] in order to divide the animals into 2 experimental groups: selection group with a higher index (TinamouS) and commercial group with a lower index (TinamouC). Twenty male offspring of the 2 groups (TinamouS, n = 10; TinamouC, n = 10) were confined for 350 d. The birds were slaughtered and pectoralis major muscle samples were collected, subjected to polar and apolar metabolites extractions and analyzed by proton nuclear magnetic resonance (1H NMR) spectroscopy. Analysis of the polar metabolomic profile identified 65 metabolites; 29 of them were differentially expressed between the experimental groups (P < 0.05). The TinamouS groups exhibited significantly higher concentrations (P < 0.05) of 25 metabolites, including anserine, aspartate, betaine, carnosine, creatine, glutamate, threonine, 3-methylhistidine, NAD+, pyruvate, and taurine. Significantly higher concentrations of cysteine, beta-alanine, lactose, and choline were observed in the TinamouC group (P < 0.05). The metabolites identified in the muscle provided information about the main metabolic pathways (higher impact value and P < 0.05), for example, phenylalanine, tyrosine and tryptophan biosynthesis; alanine, aspartate and glutamate metabolism; D-glutamine and D-glutamate metabolism; ß-alanine metabolism; glycine, serine and threonine metabolism; taurine and hypotaurine metabolism; histidine metabolism; phenylalanine metabolism. The NMR spectra of apolar fraction showed 8 classes of chemical compounds. The metabolome analysis shows that the selection index resulted in the upregulation of polyunsaturated fatty acids, unsaturated fatty acids, phosphocholines, phosphoethanolamines, triacylglycerols, and glycerophospholipids. The present study suggests that, despite few generations, the selection based on muscle growth traits promoted changes in metabolite concentrations in red-winged tinamou.

Association of Phenotypic Markers of Heat Tolerance with Australian Genomic Estimated Breeding Values and Dairy Cattle Selection Indices.

Dairy cattle predicted by genomic breeding values to be heat tolerant are known to have less milk production decline and lower core body temperature increases in response to elevated temperatures. In a study conducted at the University of Melbourne's Dookie Robotic Dairy Farm during summer, we identified the 20 most heat-susceptible and heat-tolerant cows in a herd of 150 Holstein Friesian lactating cows based on their phenotypic responses (changes in respiration rate, surface body temperature, panting score, and milk production). Hair samples were collected from the tip of the cows' tails following standard genotyping protocols. The results indicated variation in feed saved and HT genomic estimated breeding values (GEBVs) (p ≤ 0.05) across age, indicating a potential for their selection. As expected, the thermotolerant group had higher GEBVs for HT and feed saved but lower values for milk production. In general, younger cows had superior GEBVs for the Balanced Performance Index (BPI) and Australian Selection Index (ASI), whilst older cows were superior in fertility, feed saved (FS), and HT. This study demonstrated highly significant (p ≤ 0.001) negative correlations (-0.28 to -0.74) between HT and GEBVs for current Australian dairy cattle selection indices (BPI, ASI, HWI) and significant (p ≤ 0.05) positive correlations between HT and GEBVs for traits like FS (0.45) and fertility (0.25). Genomic selection for HT will help improve cow efficiency and sustainability of dairy production under hot summer conditions. However, a more extensive study involving more lactating cows across multiple farms is recommended to confirm the associations between the phenotypic predictors of HT and GEBVs.

Selection of Short-Day Strawberry Genotypes through Multivariate Analysis.

Strawberries are produced in tropical regions using imported cultivars adapted to temperate and subtropical climates. These cultivars, under tropical conditions, produce below their genetic potential. Through multivariate analyses, the objective was to evaluate and select short-day strawberry genotypes based on intraspecific crosses, product characteristics, and fruit quality. The genotypes were obtained from the cross between 'Camino Real' (female parent) and the first-generation genotypes RVCA16, RVCS44, RVFS06, RVFS07, and RVDA11 (male parent), obtained in previous selections. The experimental design consisted of augmented blocks with standard controls, consisting of first-generation genotypes and commercial cultivars. The fruits were harvested and evaluated for productivity and post-harvest characteristics: total fruit mass (MTF), total number of fruits (TFN), average fruit mass (AFM), commercial fruit mass (CFM), fruit commercial number (CFN), average commercial mass of fruits (ACFM), total soluble solids (TSS), firmness (F), brightness (L), hue angle (°Hue), and chroma (C). The selection index of Mulamba and Mock (1978) was used with an intensity of 3% to obtain superior genotypes and submitted to multivariate analysis for comparative purposes. Of the 1500 genotypes evaluated, it was possible to select 44 genotypes with characteristics superior to the 13 controls. The RVDA11CR59 genotype showed better values for the attributes of interest, but the RVCS44CR population, from the cross between 'Camino Real' × RVCS44 ('Camarosa' × 'Sweet Charlie'), obtained the highest number (16) of individuals among those selected. Significant traits had high heritability but were not necessarily reflected in high selection gain. Coefficients of genetic variation were high, indicating sufficient genetic variability to select genotypes for these traits. When multivariate analyses were used, it was possible to group the selected genotypes into the same cluster according to the similarity and balance in the responses to the evaluated variables, demonstrating that these analyses help other parameters choose superior genotypes. The multivariate analysis allowed the selection of more balanced genotypes for production and post-harvest traits for tropical climates.

Genetic (co)variance components for slaughter traits in a multi-breed sheep population.

Carcass value is one of the main contributors to revenue in meat sheep enterprises, while age at slaughter is also a major component to the cost of production. Despite the contribution of such traits to overall profit, little is actually known on the extent of exploitable genetic variability in the traits that govern carcass value (i.e. carcass weight, carcass conformation, carcass fat) and age at slaughter, especially independent of each other. The objective of the present study was to estimate genetic (co)variances for and among carcass weight, carcass conformation, carcass fat, kill-out percentage and age at slaughter as well as their genetic (co)variances with traits measured earlier in life. Data consisted of slaughter records from 15 714 lambs, with 12 630 of these lambs having at least one live weight measure. The heritability (SE) of carcass weight, carcass conformation, carcass fat, kill-out percentage, and age at slaughter was 0.14 (0.02), 0.19 (0.02), 0.08 (0.01), 0.22 (0.03), and 0.16 (0.02), respectively. The maternal heritability for age at slaughter was 0.07 (0.02); no maternal genetic influence was found on any of the other slaughter traits. The coefficient of genetic variation for carcass weight and age at slaughter was 3 and 8%, respectively. The correlations between the direct genetic effects for live weight throughout life, and carcass weight were weak up to weaning but were strong (0.83) thereafter. The correlation between the direct genetic effects of birth weight and age at slaughter was zero, but varied from -0.91 to -0.56 between live weight measured later in life and age at slaughter. Results demonstrate significant exploitable genetic variability in a range of slaughter traits with the prediction of genetic merit for carcass traits and age at slaughter being possible using live weight measures taken on live animals. For example, the accuracy of selection for slaughter traits (comprising of age at slaughter, carcass conformation and carcass fat) from weaning weight records available on 100 progeny was 0.37; when slaughter data were also available for 10 progeny, the accuracy of selection increased to 0.56.

Decision tree scoring system to guide selection for consumer preference in sweetpotato breeding trials.

BACKGROUND: Previously, a lexicon and protocol for quantitative descriptive analysis (QDA) was established for the Uganda sweetpotato breeding program. The implication of QDA scores for priority sensory attributes on consumer preference should be determined to interpret results efficiently and make decisions effectively. The present study aimed to develop a gender-responsive decision tree to obtain an overall sweetpotato eating quality score to facilitate demand-led targeted breeding selection. It focused on Kamuli and Hoima districts (Uganda) and uses pre-lease advanced clones ('NKB3', 'NKB105', 'NKB135', 'D11' and 'D20'), released varieties ('NASPOT 8' and 'NAROSPOT 1') and landraces ('Muwulu-Aduduma', 'Umbrella'). RESULTS: Including boiled sweetpotato sensory characteristics, namely mealy, sweet taste, sweetpotato smell, firm and not fibrous, in breeding design would benefit end-users, especially women given their role in varietal selection, food preparation and marketing. 'D20', 'NASPOT 8' and 'NAROSPOT 1' were most liked in both districts. 'NKB3' and 'D11' were the least liked in Hoima, whereas 'Muwulu-Aduduma' was the least liked in Kamuli. There was a positive correlation between color and overall liking (r2 = 0.8) and consumers liked the color (average rating ≥ 6 on a nine-point hedonic scale) of all genotypes. Threshold values (average rating on 11-point scales) for consumer acceptability were identified (sweet taste = 6, sweetpotato aroma and flavor = 6, firmness = 3, and mealiness = 4). A regression decision tree tool was created to calculate an eating quality selection index when screening lines in breeding programs using the values. CONCLUSION: Decision trees that include consumer needs and gender considerations would facilitate demand-led breeding and make varietal selection in sweetpotato breeding programs more effective. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Stability analysis for seed yield of chickpea (Cicer arietinum L.) genotypes by experimental and biological approaches.

A range of environmental factors restricts the production of chickpea; therefore, introducing compatible cultivars to a range of environments is an important goal in breeding programs. This research aims to find high-yielding and stable chickpea genotypes to rainfed condition. Fourteen advanced chickpea genotypes with two control cultivars were cultivated in a randomized complete block design in four regions of Iran during 2017-2020 growing seasons. The first two principal components of AMMI explained 84.6 and 10.0 % of genotype by environment interactions, respectively. Superior genotypes based on simultaneous selection index of ASV (ssiASV), ssiZA, ssiDi and ssiWAAS were G14, G5, G9 and G10; those based on ssiEV and ssiSIPC were G14, G5, G10 and G15 and those based on ssiMASD were G14, G5, G10 and G15. The AMMI1 biplot identified G5, G12, G10 and G9 as stable and high-yielding genotypes. Genotypes G6, G5, G10, G15, G14, G9 and G3 were the most stable genotypes in the AMMI2 biplot. Based on the harmonic mean and relative performance of genotypic values, G11, G14, G9 and G13 were the top four superior genotypes. Factorial regression indicated that rainfall is very important at the beginning and end of the growing seasons. Genotype G14, in many environments and all analytical and experimental approaches, has good performance and stability. Partial least squares regression identified genotype G5 as a suitable genotype for moisture and temperature stresses conditions. Therefore, G14 and G5 could be candidates for introduction of new cultivars.

Effect of Genetic and Environmental Factors on Twin Pregnancy in Primiparous Dairy Cows.

Twin pregnancies are highly undesirable in dairy cattle; they compromise the health and wellbeing of a cow and dramatically impair the farm economy. Recently, a genomic prediction for twin pregnancies has been developed. The objective of this study was to assess environmental and management risk factors affecting the incidence of twin pregnancies in high-producing dairy cows in their first lactation, with a special emphasis placed on the genomic prediction values of twin pregnancy. Our study population of primiparous cows proved valuable in identifying factors other than genomic predictive values that influence twin pregnancy rates. The odds ratio for twin pregnancies was 0.85 (p < 0.0001) for each unit of a prediction value increase, 3.5 (p = 0.023) for cows becoming pregnant during the negative photoperiod, and 0.33 (p = 0.016) for cows producing ≥42 kg of milk at AI, compared with the remaining cows who produced <42 kg of milk. As a general conclusion, the practical implication of our findings is that genomic prediction values can identify the risk of twin pregnancy at a herd level. Given the cumulative effect of genomic selection, selecting animals with a reduced genetic risk of twin pregnancies can contribute to reducing the incidence of twin pregnancies in dairy herds.

Identification of Superior Barley Genotypes Using Selection Index of Ideal Genotype (SIIG).

The main objective of the study was to evaluate and select the superior barley genotypes based on grain yield and some pheno-morphological traits using a new proposed selection index (SIIG). For this purpose, one-hundred-eight pure and four local cultivars (Norouz, Auxin, Nobahar, and WB-97-11) were evaluated as reference genotypes in four warm regions of Iran, including Ahvaz, Darab, Zabol, and Gonbad, during the 2020-2021 cropping seasons. The results of REML analysis showed that the heritability of all traits (except plant height) was higher in Gonbad than in other environments, while the lowest values were estimated in Ahvaz and Zabol environments. In addition, among the measured traits, the thousand kernel weight and grain filling period showed the highest and lowest values of heritability (0.83 and 0.01, respectively). The results showed that the seed yield of genotypes 1, 108, 3, 86, 5, 87, 19, 16, 15, 56, and 18 was higher than the four reference genotypes, and, on the other hand, the SIIG index of these genotypes was greater than or equal to 0.60. Based on the SIIG discriminator index, 4, 8, 31, and 28 genotypes with values greater than or equal to 0.60 were identified as superior for Darab, Ahvaz, Zabol, and Gonbad environments, respectively. As a conclusion, our results revealed that the SIIG index has ideal potential to identify genotypes with high yield and desirable traits. Therefore, the use of this index can be beneficial in screening better genotypes in the early stages of any breeding program for any crop.

Incorporation of feeding behaviour traits to increase the genetic gain of feed efficiency in Pietrain pigs.

Improved feed efficiency is an essential goal for the sustainability of pig production in economic and environmental terms. Traits such as feed conversion rate (FCR), residual feed intake (RFI), residual body weight gain (RG) and feeding behaviour, such as duration (TPV) and feeding rate per visit (FR) can now be measured by automatic feeding systems. The aim of this study was to evaluate the benefits of incorporating feeding behaviour traits into a selection index to improve feed efficiency in a nucleus of purebred Pietrain pigs. Data on body weight, feed intake and duration were recorded at each visit in 1608 animals. The information contained in 843,605 visits was grouped by animal ID to obtain a set of feed efficiency and feeding behaviour traits. These traits were obtained in three periods (first, second and total period). Bayesian models were built to estimate the posterior marginal distribution of the variance components. The heritabilities were between 0.44 and 0.59 for feeding behaviour traits and between 0.31 and 0.49 for feed efficiency traits. The FCR and RFI showed a considerable genetic correlation with daily feed intake (~0.65). FCR showed a genetic correlation with feeding behaviour traits, such as feed intake per visit (FPV) (0.44) and FR (0.33). Furthermore, the fast-eating pigs were less efficient. This was due to the positive genetic correlation found between the FR and the FCR (0.33) and the RFI (0.23), and the negative correlation found with the RG (-0.28). On the other hand, the inclusion of the feeding behaviour traits into a selection index slightly increased the selection response for FCR (4%) and RFI (1.8%). However, there was an increase of up to 19% in the selection response for RG and an improvement in accuracy from 0.59 to 0.70. Therefore, we concluded that it would be interesting to include feeding behaviour traits in a selection index to improve the selection response and accuracy of feed efficiency traits.

Implementation of Feed Efficiency in Iranian Holstein Breeding Program.

This study aimed to evaluate the economic impact of improving feed efficiency on breeding objectives for Iranian Holsteins. Production and economic data from seven dairy herds were used to estimate the economic values of different traits, and a meta-analysis was conducted to analyze the genetic relationships between feed efficiency and other traits. Economic weights were calculated for various traits, with mean values per cow and per year across herds estimated at USD 0.34/kg for milk yield, USD 6.93/kg for fat yield, USD 5.53/kg for protein yield, USD -1.68/kg for dry matter intake, USD -1.70/kg for residual feed intake, USD 0.47/month for productive life, and USD -2.71/day for days open. The Iranian selection index was revised to improve feed efficiency, and the feed efficiency sub-index (FE$) introduced by the Holstein Association of the United States of America was adopted to reflect Iran's economic and production systems. However, there were discrepancies between Iranian and US genetic coefficients in the sub-index, which could be attributed to differences in genetic and phenotypic parameters, as well as the economic value of each trait. More accurate estimates of economic values for each trait in FE$ could be obtained by collecting dry matter intake from Iranian herds and conducting genetic evaluations for residual feed intake.

Characterizing quality traits of boiled yam: texture and taste for enhanced breeding efficiency and impact.

BACKGROUND: Boiled yam key quality attributes typical for West African consumers are that it is crumbly, easy to break and has a sweet taste. New yam varieties are being developed but high- or medium-throughput tools to assess the required quality traits and their range of acceptance are limited. This study assessed the acceptance thresholds of these quality attributes and established predictive models for screening yam varieties that meet the required consumer preferences. RESULTS: Overall liking was associated with sweet taste, crumbliness and easiness to break (r-values 0.502, 0.291 and -0.087, respectively). These parameters and selected biophysical parameters highly discriminated the boiled yam varieties. Crumbly texture and easiness to break were well predicted by penetration force and dry matter, whereas sweet taste were well predicted by dry matter and sugar intensity. A high crumbliness and sweet taste are preferred (sensory scores above 6.19 and 6.22 for crumbly and sweet taste, respectively, on a 10 cm unstructured line scale), while a too high easiness to break is disliked (sensory scores ranging from 4.72 to 7.62). Desirable biophysical targets were between 5.1 and 7.1 N for penetration force, dry matter around 39% and sugar intensity below 3.62 g 100 g-1 . Some improved varieties fulfilled the acceptable thresholds, and screening was improved through deviation from the optimum. CONCLUSION: Acceptance thresholds and deviation from optimum for boiled yam assessed through the instrumental measurements are promising tools for yam breeders. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Carcass and meat quality of red-winged tinamou (Rhynchotus rufescens) selected for muscle growth.

The aim of the present study was to evaluate the efficiency of selection for body growth and its association with carcass and meat quality traits in the red-winged tinamou. Two experimental groups were selected based on the selection index: selection group with a higher index (TinamouS) and commercial group with a lower index (TinamouC). Weight at 180 days and slaughter weight were significantly higher (p < 0.05) in the TinamouS group, as were hot carcass weight, skinless breast weight, wing weight, and thigh and drumstick weight. The meat quality traits or sensory attributes did not differ significantly (p > 0.05) between groups. A significant positive correlation (0.59; p < 0.05) was found between shear force and chewability and a significant negative correlation (- 0.59; p < 0.05) between aroma intensity and strange aroma. The present study suggests that the selection index promotes greater body growth and preserves meat quality and sensory traits in red-winged tinamou.

Identification of Disease Resistance Parents and Genome-Wide Association Mapping of Resistance in Spring Wheat.

The likelihood of success in developing modern cultivars depend on multiple factors, including the identification of suitable parents to initiate new crosses, and characterizations of genomic regions associated with target traits. The objectives of the present study were to (a) determine the best economic weights of four major wheat diseases (leaf spot, common bunt, leaf rust, and stripe rust) and grain yield for multi-trait restrictive linear phenotypic selection index (RLPSI), (b) select the top 10% cultivars and lines (hereafter referred as genotypes) with better resistance to combinations of the four diseases and acceptable grain yield as potential parents, and (c) map genomic regions associated with resistance to each disease using genome-wide association study (GWAS). A diversity panel of 196 spring wheat genotypes was evaluated for their reaction to stripe rust at eight environments, leaf rust at four environments, leaf spot at three environments, common bunt at two environments, and grain yield at five environments. The panel was genotyped with the Wheat 90K SNP array and a few KASP SNPs of which we used 23,342 markers for statistical analyses. The RLPSI analysis performed by restricting the expected genetic gain for yield displayed significant (p < 0.05) differences among the 3125 economic weights. Using the best four economic weights, a subset of 22 of the 196 genotypes were selected as potential parents with resistance to the four diseases and acceptable grain yield. GWAS identified 37 genomic regions, which included 12 for common bunt, 13 for leaf rust, 5 for stripe rust, and 7 for leaf spot. Each genomic region explained from 6.6 to 16.9% and together accounted for 39.4% of the stripe rust, 49.1% of the leaf spot, 94.0% of the leaf rust, and 97.9% of the common bunt phenotypic variance combined across all environments. Results from this study provide valuable information for wheat breeders selecting parental combinations for new crosses to develop improved germplasm with enhanced resistance to the four diseases as well as the physical positions of genomic regions that confer resistance, which facilitates direct comparisons for independent mapping studies in the future.

Drug Combinations to Prevent Antimicrobial Resistance: Various Correlations and Laws, and Their Verifications, Thus Proposing Some Principles and a Preliminary Scheme.

Antimicrobial resistance (AMR) has been a serious threat to human health, and combination therapy is proved to be an economic and effective strategy for fighting the resistance. However, the abuse of drug combinations conversely accelerates the spread of AMR. In our previous work, we concluded that the mutant selection indexes (SIs) of one agent against a specific bacterial strain are closely related to the proportions of two agents in a drug combination. To discover probable correlations, predictors and laws for further proposing feasible principles and schemes guiding the AMR-preventing practice, here, three aspects were further explored. First, the power function (y = axb, a > 0) correlation between the SI (y) of one agent and the ratio (x) of two agents in a drug combination was further established based on the mathematical and statistical analyses for those experimental data, and two rules a1 × MIC1 = a2 × MIC2 and b1 + b2 = −1 were discovered from both equations of y = a1xb1 and y = a2xb2 respectively for two agents in drug combinations. Simultaneously, it was found that one agent with larger MPC alone for drug combinations showed greater potency for narrowing itself MSW and preventing the resistance. Second, a new concept, mutation-preventing selection index (MPSI) was proposed and used for evaluating the mutation-preventing potency difference of two agents in drug combination; a positive correlation between the MPSI and the mutant prevention concentration (MPC) or minimal inhibitory concentration (MIC) was subsequently established. Inspired by this, the significantly positive correlation, contrary to previous reports, between the MIC and the corresponding MPC of antimicrobial agents against pathogenic bacteria was established using 181 data pairs reported. These results together for the above three aspects indicate that the MPCs in alone and combination are very important indexes for drug combinations to predict the mutation-preventing effects and the trajectories of collateral sensitivity, and while the MPC of an agent can be roughly calculated from its corresponding MIC. Subsequently, the former conclusion was further verified and improved via antibiotic exposure to 43 groups designed as different drug concentrations and various proportions. The results further proposed that the C/MPC for the agent with larger proportion in drug combinations can be considered as a predictor and is the key to judge whether the resistance and the collateral sensitivity occur to two agents. Based on these above correlations, laws, and their verification experiments, some principles were proposed, and a diagram of the mutation-preventing effects and the resistant trajectories for drug combinations with different concentrations and ratios of two agents was presented. Simultaneously, the reciprocal of MPC alone (1/MPC), proposed as the stress factors of two agents in drug combinations, together with their SI in combination, is the key to predict the mutation-preventing potency and control the trajectories of collateral sensitivity. Finally, a preliminary scheme for antimicrobial combinations preventing AMR was further proposed for subsequent improvement research and clinic popularization, based on the above analyses and discussion. Moreover, some similar conclusions were speculated for triple or multiple drug combinations.