Total Variation Research Articles

The risk status, signatures of adaptation, and environmental suitability of village-based indigenous chickens from certain regions of Limpopo and KwaZulu-Natal provinces of South Africa

Indigenous chickens are an important Farm Animal Genetic Resource (FAnGR) in South Africa as they alleviate poverty and are a source of protein. Climate change and market demand for high-performing exotic breeds threaten and undermine locally adapted village chickens. The current study explored the risk status and signatures of adaptation of village-based indigenous chickens from two provinces and mapped their environmental suitability across the country. A total of 244 village chickens from rural areas of the Capricorn (n = 85) and Sekhukhune (n = 113) districts of Limpopo province; the Harry Gwala (n = 21) and uMzinyathi (n = 25) districts of KwaZulu-Natal province were genotyped using the Illumina 60K BeadChip. The conservation flock comprised Ovambo (OV; n = 10), Potchefstroom KoeKoek (PK; n = 20), and Venda (VD; n = 20). Naked Neck (NN; n = 20), New Hampshire (NH; n = 10), White Leghorn (WL; n = 10), and White Plymouth Rock (WR; n = 10) from the Agricultural Research Council Poultry Breeding Unit were used as reference populations and representative of flocks under conservation. The effective population size (Ne) in village chickens and conserved flocks ranged from 18 to 53 and 26 to 38 at 12 generations ago, respectively. PC1 and PC2 explained 5.64% of the total variation, which resulted in five clusters with the Venda, Naked Neck, and White Leghorn being separated from village chickens. The first three redundancy analysis (RDA) axes capture 46.8% of the total genetic variation used to detect significant outlier SNPs. A total of 386 outlier SNPs associated with all 10 environmental variables were detected. Using ecological niche modeling, chickens from Dipakakeng, Mgababa, and Podu villages, Limpopo, had a localized predicted suitability probability, while chickens originating from Nhlonga village, KwaZulu-Natal, had a broader distribution of predicted suitability habitats with elevation and BIO6 being important variables. The results of this study provide insight into the risk status, geographic suitability, and contributing environmental factors of indigenous chickens that can be used to influence conservation and improvement decisions.

Diet, physical activity, and sleep in relation to postprandial glucose responses under free-living conditions: an intensive longitudinal observational study

BackgroundIt remains unclear what lifestyle behaviors are optimal for controlling postprandial glucose responses under real-world circumstances in persons without diabetes. We aimed to assess associations of diet, physical activity, and sleep with postprandial glucose responses in Asian adults without diabetes under free-living conditions.MethodsWe conducted an observational study collecting intensive longitudinal data using smartphone-based ecological momentary assessments, accelerometers, and continuous glucose monitors over nine free-living days in Singaporean men and women aged 21–69 years without diabetes. The outcome was the 2-h postprandial glucose incremental area under the curve (mmol/l*min). Associations were estimated using linear mixed-effect models.ResultsThe analyses included 11,333 meals in 789 participants. Greater variations in glucose and lifestyle measures were observed within individuals than between individuals. Higher consumption of carbohydrate-rich and deep-fried foods and lower consumption of protein-rich foods were significantly associated with higher postprandial glucose levels (incremental area under the curve). The strongest association was observed for including refined grains (46.2 [95% CI: 40.3, 52.1]) in meals. Longer postprandial light-intensity physical activity (-24.7 [(-39.5, -9.9] per h) and moderate-to-vigorous-intensity physical activity (-58.0 [-73.8, -42.3]) were associated with substantially lower postprandial glucose levels. Longer daily light-intensity physical activity (-7.5 [-10.7, -4.2]) and sleep duration (-2.7 [-4.4, -1.0]) were also associated with lower postprandial glucose levels. Furthermore, postprandial glucose levels were the lowest in the morning and the highest in the afternoon. The results were largely consistent for males and females and for participants with and without prediabetes.ConclusionsConsuming less refined grains and more protein-rich foods, getting more physical activity (particularly during the postprandial period), and having a longer sleep duration were associated with lower postprandial glucose levels in Asian adults without diabetes. Our findings support multi-component lifestyle modifications for postprandial glucose control and highlight the importance of the timing of eating and physical activity.

An LC-MS/MS assay for simultaneous determination of 13 steroid hormones and two synthetic steroids in saliva: potential utility for paediatric population and beyond.

Saliva samples offer the possibility to obtain stress-free non-invasive samples, also for home-testing, especially useful when blood collection is either undesirable or difficult. The aim of this work was to develop an LC-MS/MS method to determine clinically relevant steroid hormones cortisol, cortisone, 11-deoxycortisol, 21-deoxycortisol, 17OH-progesterone, aldosterone, corticosterone, deoxycorticosterone, testosterone, androstenedione, DHEAS, DHEA, 17OH-pregnenolone, betamethasone and dexamethasone. A special effort was made to adapt the method to neonatal population with respect to choice of saliva as matrix, low sample volumes, selection of analytes and multiplexing. Validation included selectivity, interferences, matrix effects, lower and upper limit of quantification, linearity of calibration, dilution of samples, trueness, within-run and total analytical repeatability, robustness, carry-over, stability and recovery from sample collection swab. Ten microliters were acceptable but 50 µL preferable sample volume, except for 21-deoxycortisol. Cortisol, cortisone, aldosterone, 11-deoxycortisol, deoxycorticosterone, dexamethasone, betamethasone, 17OH-pregnenolone and DHEAS could be determined in as little as 2-5µL saliva. Total analytical variation was <15%, except for 17OH-progesterone, deoxycorticosterone, 17OH-pregnenolone, 21-deoxycortisol, androstenedione, DHEA and betamethasone, that could only be determined semi-quantitatively or qualitatively. The minimum turnaround time was 3-4 h. Recovery from the best performing sample collection swab SalivaBio ranged from 83 to 127%. Aldosterone, cortisone and DHEA were more stable in saliva compared to serum when stored at ambient temperature for one week. Corticosterone and 17OH-progesterone needed immediate freezing. The non-invasiveness, small saliva volume requirement, on-swab stability and analytical performance make the method relevant for both research and diagnostics, above all in the setting of neonatal intensive care unit.

A retinex inspired deep image prior model for despeckling and deblurring of aerial and satellite images using proximal gradient method

ABSTRACT Unsupervised learning models, particularly in the remote sensing domain, have gained significant attention in recent years. Various degradations in the satellite images, primarily occurring during acquisition, pose a substantial hurdle in obtaining reliable ground truth and extensive training data. The Deep Image Prior model (DIP) addresses these issues by performing restoration tasks using a single image, relying on the implicit regularization inherent in the network architecture. In this paper, we propose a novel approach, integrating the DIP model within the retinex framework to restore aerial and satellite images from the Gamma distributed speckles and linear shift-invariant Gaussian blur along with contrast enhancement using the alternating proximal gradient descent ascent (PGDA) method. Our proposed methodology combines implicit regularization with explicit total variational (TV) regularization, incorporating automated estimation of local regularization parameters. The data-fidelity component in the optimization function is formulated using the Bayesian Maximum A posteriori (MAP) estimate, assuming the speckles follow the Gamma distribution. Demonstration of despeckling and deblurring alone and in addition as a combined task is carried out on aerial and Synthetic Aperture Radar (SAR) images with different resolutions and polarization from various sources. Results obtained are compared with various state-of-the-art despeckling and deblurring models using distinct image quality metrics such as Equivalent Number of Looks (ENL), Contrast to Noise Ratio (CNR), Edge Preserving Index (EPI), Entropy, Global Contrast Factor (GCF), Natural Image Quality Evaluator (NIQE), Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) and Bradley-Terry (B-T) score based on the various factors. The quality of restored images depicted superior performance of the proposed method over the existing models under study.

Wavelet Total Variation Fusion and Fuzzy Logic Decision-Based Haze Density and Sky Region-Aware De-Hazing

In this study, we present a fuzzy logic-based classifier with a decision-based partial differential equation (PDE) for single image de-hazing. This enhanced partitioning is achieved via adaptive segmentation and morphological region-growing processes. Also, the first stage fusion of enhanced inverted log illumination and log reflectance components leads to minimization or elimination of edge artifacts. Additionally, improved scene discrimination between sky and non-sky regions due to the fuzzy logic decision-based approach is achieved. This results in effective de-hazing without sky region over-enhancement. Furthermore, a modified wavelet multi-level decomposition-based de-hazing algorithm is presented. It improves details and local contrast in de-hazed images, especially for images with thick haze. Ultimately, these algorithms are fused to obtain the best and most consistent results for all images. Experimental comparisons with the state-of-the-art algorithms show improved sky discrimination and improved clarity.

Sparse Geomagnetic Time-Series Sensing Data Completion Leveraging Improved Tensor Correlated Total Variation

Sparse Geomagnetic Time-Series Sensing Data Completion Leveraging Improved Tensor Correlated Total Variation

The Relationship Between Adolescent Orthodontic Treatment and Temporomandibular Disorders: A Systematic Review with Meta-Analysis

The relationship between fixed orthodontic treatment and the development of temporomandibular disorders (TMDs) in adolescents has been a topic of considerable debate. This systematic review and meta-analysis aimed to evaluate the impact of fixed orthodontic treatment on the prevalence of TMDs in adolescents. A comprehensive literature search was conducted using PubMed, Web of Science, EMBASE, Google Scholar, and the Cochrane Library, yielding 886 records. After duplicate removal, 665 records were screened, and 8 studies were assessed for eligibility. Following quality assessment using the Joanna Briggs Institute checklist, 4 studies were included in the final analysis. Data were analyzed using a random-effects model in RevMan software. The meta-analysis revealed an overall odds ratio of 0.75 (95% CI: 0.37–1.51, p = 0.42), indicating no statistically significant association between fixed orthodontic treatment and the risk of developing TMDs. Substantial heterogeneity was observed (I2 = 73%), attributed to variations in study designs, populations, and outcome measures. The risk of bias analysis highlighted concerns in several domains, particularly selection bias and measurement of outcomes. While confounding bias and missing data bias were generally well-controlled, deviations in intervention and inconsistent outcome measurements were noted across the studies. These findings suggest that fixed orthodontic treatment does not significantly alter the risk of developing TMDs in adolescents. However, the substantial heterogeneity and potential biases across the included studies emphasize the need for further high-quality, standardized research to confirm these results and provide clearer clinical guidance.

An optimisation method for coplanar array capacitor image reconstruction based on Chambolle-Pock framework with automatic parameter selection

ABSTRACT Coplanar array capacitance imaging is an attractive imaging technique in industrial and detection fields, but low-quality images reduce its practicality and reliability. The inverse problem is difficult to solve and the image reconstruction quality is low, in this paper, an auxiliary optimisation strategy is proposed to transform the inverse problem of image reconstruction into a general minimisation problem, combined with the threshold of automatic parameter selection for feature extraction of capacitive data. The Kullback-Leibler(KL) data error term is combined with the Total Variation (TV) semi-norm to form a new imaging model. Utilising the Chambolle-Pock framework, the image reconstruction problem is transformed into a general minimisation problem to obtain high-quality images. Capacitance data from a 3 × 4 coplanar array capacitance sensor is used for feature extraction, serving as the basis for automatic parameter selection in the auxiliary optimisation strategy. The proposed Chambolle-Pock framework with the support of the auxiliary optimisation strategy, validated through simulation and experiments, outperforms popular imaging algorithms in terms of performance. The novel automatic parameter selection optimization algorithm introduced in this paper enhances the accuracy of capacitor image reconstruction in coplanar arrays.

Antimicrobial effect of silver diamine fluoride (SDF) in arresting dentine caries of permanent teeth: A Systematic review

Background Silver diamine fluoride (SDF) is recognized for its potent antibacterial properties and is commonly used in dentistry to treat carious lesions. This review aims to evaluate the antimicrobial effect of SDF on dentine caries in permanent teeth. The objective is to provide a comprehensive analysis of the existing literature to assess the efficacy of SDF in combating cariogenic flora within dentin lesions. Materials and Methods A systematic electronic search was conducted using Google Scholar, Cochrane Library, and PubMed databases to identify relevant studies published between January 2010 and September 2022. The search strategy focused on retrieving in vitro and in vivo studies assessing the antimicrobial effect of SDF on dentinal caries. The inclusion criteria encompassed studies that compared SDF with other antimicrobial agents, such as sodium fluoride varnish, potassium iodide, silver nitrate, chlorhexidine, plasma jet, and deionized water. The Cochrane Collaboration assessment tool was employed to evaluate the risk of bias in the included studies. Results Nine studies met the inclusion criteria, consisting of seven in vitro and in situ studies investigating the antimicrobial effect of SDF on dentinal caries, and two in vitro and in vivo studies examining its antibacterial effect on root caries. These studies collectively demonstrated the promising antimicrobial potential of SDF against cariogenic flora present in dentin lesions. However, variations in study design, methodology, and outcome measures were observed across the included studies. Conclusion The review underscores the significant antimicrobial efficacy of SDF in combating cariogenic bacteria within dentin lesions of permanent teeth. Despite the promising findings, there remains a lack of comprehensive understanding regarding the precise characteristics and mechanisms underlying the antimicrobial action of SDF, particularly concerning nano-silver. Future research, including long-term clinical trials, is warranted to elucidate optimal dosage regimens and therapeutic approaches for the routine application of SDF in managing dental caries.

Assessment of the physiological effects and safety of transpulmonary chemoembolization with doxorubicin on pulmonary tissue using a human-isolated lung perfusion model

BackgroundWhole lung transpulmonary chemoembolization using a combination of doxorubicin (DXO) and degradable starch microspheres (DSM-TPCE) might be a promising treatment option in soft tissue sarcoma. To pave the way for clinical studies, this study aimed to evaluate the short-term effects of DSM-TPCE with DXO using an ex vivo isolated lung perfusion (ILP) model.MethodsNine lung specimens retrieved from patients undergoing lobectomy underwent ex vivo ILP. In groups of three, lung specimens were either treated with sole DXO, sole DSM, or combined substances (DSM + DXO). During ex vivo ILP, histological samples were obtained from each lung every 15 min. Quantitative DXO analysis and histopathological grading of possible tissue damage using a five-point Likert scale was performed. Two-way repeated measures ANOVA tested for differences between treatment groups and changes over time.ResultsWe created a preclinical ex vivo ILP model to simulate the effects of DSM-TPCE. In histopathological analysis, only two specimens, treated with only DXO, showed an increase in parenchymal damage over time. No significant effect of time (3.3%, p = 0.305) or group (23.3; p = 0.331) was identified. Within the lung tissue, the DXO concentration ranged from 205 to 1,244 ng/g. No significant effects could be detected regarding different treatment groups (4.9% of total variation, p = 0.103).ConclusionIn an ex vivo ILP model using human lung lobes, the physiological effects of DSM-TPCE with DXO could be tested. Neither increased DXO concentrations in lung tissue nor histopathological changes indicating early lung toxicity were observed.Relevance statementAn ex vivo ILP model using human lung specimens did not show any signs of early lung toxicity after transpulmonary chemoembolization with DXO. These results support further evaluation of DSM-TPCE in phase I/II trials.Key PointsTranspulmonary chemoembolization can be investigated in an ex vivo ILP model.DSM did not increase DXO in normal lung tissue.DSM did not increase parenchymal toxicity compared to the control groups.Graphical

Theory and fast learned solver for $\ell^1$-TV regularization

Abstract The $\ell^1$ and total variation (TV) penalties have been used successfully in many areas, and the combination of the $\ell^1$ and TV penalties can lead to further improved performance. In this work, we investigate the mathematical theory and numerical algorithms for the $\ell^1$-TV model in the context of signal recovery: we derive the sample complexity of the $\ell^1$-TV model for recovering signals with sparsity and gradient sparsity. Also we propose a novel algorithm (PGM-ISTA) for the regularized $\ell^1$-TV problem, and establish its global convergence and parameter selection criteria. Furthermore, we construct a fast learned solver (LPGM-ISTA) by unrolling PGM-ISTA. The results for the experiment on ECG signals show the superior performance of LPGM-ISTA in terms of recovery accuracy and computational efficiency.

On the existence of solutions to adversarial training in multiclass classification

Abstract Adversarial training is a min-max optimization problem that is designed to construct robust classifiers against adversarial perturbations of data. We study three models of adversarial training in the multiclass agnostic-classifier setting. We prove the existence of Borel measurable robust classifiers in each model and provide a unified perspective of the adversarial training problem, expanding the connections with optimal transport initiated by the authors in their previous work [21]. In addition, we develop new connections between adversarial training in the multiclass setting and total variation regularization. As a corollary of our results, we provide an alternative proof of the existence of Borel measurable solutions to the agnostic adversarial training problem in the binary classification setting.

A nonlocal weighted difference of anisotropic and isotropic total variation to regularize partition boundaries in an image

A nonlocal weighted difference of anisotropic and isotropic total variation to regularize partition boundaries in an image

Bayesian Frequency Estimation Under Local Differential Privacy With an Adaptive Randomized Response Mechanism

Frequency estimation plays a critical role in many applications involving personal and private categorical data. Such data are often collected sequentially over time, making it valuable to estimate their distribution online while preserving privacy. We propose AdOBEst-LDP, a new algorithm for adaptive, online Bayesian estimation of categorical distributions under local differential privacy (LDP). The key idea behind AdOBEst-LDP is to enhance the utility of future privatized categorical data by leveraging inference from previously collected privatized data. To achieve this, AdOBEst-LDP uses a new adaptive LDP mechanism to collect privatized data. This LDP mechanism constrains its output to a subset of categories that ‘predicts’ the next user's data. By adapting the subset selection process to the past privatized data via Bayesian estimation, the algorithm improves the utility of future privatized data. To quantify utility, we explore various well-known information metrics, including (but not limited to) the Fisher information matrix, total variation distance, and information entropy. For Bayesian estimation, we utilize posterior sampling through stochastic gradient Langevin dynamics, a computationally efficient approximate Markov chain Monte Carlo (MCMC) method. We provide a theoretical analysis showing that (i) the posterior distribution of the category probabilities targeted with Bayesian estimation converges to the true probabilities even for approximate posterior sampling, and (ii) AdOBEst-LDP eventually selects the optimal subset for its LDP mechanism with high probability if posterior sampling is performed exactly. We also present numerical results to validate the estimation accuracy of AdOBEst-LDP. Our comparisons show its superior performance against non-adaptive and semi-adaptive competitors across different privacy levels and distributional parameters.

Assessing Roles of Aggregate Structure on Hydraulic Properties of Saline/Sodic Soils in Coastal Reclaimed Areas

During coastal reclamation processes, land use conversion from natural coastal saline/sodic soils to agricultural land changes the soil’s physicochemical properties. However, the impact of soil structure evolution on soil hydraulic properties (SHPs, e.g., hydraulic conductivity and soil water retention curves) during long-term reclamation has rarely been reported. In this study, we aimed to evaluate the effect of reclamation duration and land use types on the soil aggregate stability and SHPs of coastal saline/sodic soils and incorporate the aggregate structures into the SHPs. In this study, a total of 90 soil samples from various reclaimed years (2007, 1960, and 1940) and land use patterns (cropland, grassland, forestland, and wasteland) were taken to analyze the quantitative effects of soil saline/sodic characteristics and the aggregate structure on SHPs through pedotransfer functions (PTFs). We found that soil macroaggregate contents in the old reclaimed areas (reclaimed in 1940 and 1960) were significantly larger than those in the new reclamation area (reclaimed in 2007). The soil saturated hydraulic conductivity (Ks) of forestland was larger than that of grassland in each reclamation year. Soil structure contributed to 22.13%, 24.52%, and 23.93% of the total variation in Ks and soil water retention parameters (α and n). The PTFs established in our study were as follows: log(Ks) = 0.524 − 0.177 × Yk3 − 0.093 × Yk1 + 0.135 × Yk4 − 0.054 × Yk2, 1/α = 477.244 − 91.732 × Yα2 − 81.283 × Yα4 + 38.106 × Yα3, and n = 1.679 − 0.086 × Yn2 + 0.045 × Yn1 − 0.042 × Yn3 (Yareprincipalcomponents). The mean relative errors of the prediction models for log(Ks), 1/α, and n were 79.30%, 36.1%, and 9.89%, respectively. Our findings quantify the vital roles of the aggregate structure on the SHPs of coastal saline/sodic soils, which will help us understand related hydrological processes.

Passive self-ligating metal brackets: evaluation of torque and slot measurements

New orthodontic bracket designs have been regularly developed. Their clinical performance depends on reliability of measures, among other factors. Objective: The aim of this study was to evaluate slot measures and torque angle of different passive self-ligating metal brackets, while comparing them with measures provided by manufacturers. Material and methods: Five different passive self-ligating metal bracket brands were selected (n = 10 each): Tellus EX, Tellus EX New, Damon Q, Easy Clip and ID-Logical. Bracket slots images were obtained with the aid of Starrett, MV300 Galileo Vision System. For slot digital measurement, Software M3 Metrology Reabout IV was used. Slot measures were evaluated in cervico-occlusal direction (slot height), buccolingual depth (in-out), and bottom-slot inclination (torque angle). Difference between obtained and provided measures was estimated and expressed as a percentage. Data were subjected to descriptive statistical analysis. Results: Most brackets evaluated by the present study revealed variation in both torque angle and slot measures which were confirmed to be greater than those provided by the manufacturer (Easy Clip, Damon Q and Tellus EX), except for two brackets (Tellus EX New and ID-Logical). The latter presented variation within normality with values accepted by ISO standards (± 1 degree and ± 1 mm variation). Conclusion: Most brackets assessed herein (Easy Clip, Damon Q and Tellus EX) presented variation in torque angle and slot measures. Tellus EX New and ID-Logical brackets remained within standards. Better standardization and control should be assumed by manufacturers in order to promote more reliability and predictability of the orthodontic treatment results.

A TVD neural network closure and application to turbulent combustion

Trained neural networks (NN) have attractive features for closing governing equations. There are many methods that are showing promise, but all can fail in cases when small errors consequentially violate physical reality, such as a solution boundedness condition. A NN formulation is introduced to preclude spurious oscillations that violate solution boundedness or positivity. It is embedded in the discretized equations as a machine learning closure and strictly constrained, inspired by total variation diminishing (TVD) methods for hyperbolic conservation laws. The constraint is exactly enforced during gradient-descent training by rescaling the NN parameters, which maps them onto an explicit feasible set. Demonstrations show that the constrained NN closure model usefully recovers linear and nonlinear hyperbolic phenomena and anti-diffusion while enforcing the non-oscillatory property. Finally, the model is applied to subgrid-scale (SGS) modeling of a turbulent reacting flow, for which it suppresses spurious oscillations in scalar fields that otherwise violate the solution boundedness. It outperforms a simple penalization of oscillations in the loss function.

Isokinetic Dynamometry for External and Internal Rotation Shoulder Strength in Youth Athletes: A Scoping Review.

Accurately measuring shoulder strength in overhead athletes is critical, as sufficient strength is essential for safe and sustained performance during repetitive athletic movements. Isokinetic dynamometry (ID) offers dynamic strength assessments that surpass the capabilities of static methods, such as manual muscle testing and handheld dynamometry. The dynamic assessment provided by ID may enhance upper extremity evaluation, aiding in the prediction of injury risk and the determination of return-to-sport criteria for overhead athletes. The purpose of this review was to examine the existing literature concerning the application of isokinetic shoulder strength testing in rehabilitation and clinical decision-making processes among youth athletes who perform repetitive overhead activities. Scoping review. A comprehensive literature search was conducted using PubMed and EBSCO Host databases, covering publications from 2000-2024. Search terms included "isokinetic dynamometry," "shoulder," and "youth athlete." Inclusion criteria focused on youth athletes (<18 years) engaged in overhead sports, excluding those with neurological conditions or those designated as college or professional athletes. The PRISMA-ScR guidelines were followed. A total of 23 articles met the inclusion criteria. Volleyball and swimming were the most studied sports, with the most common testing position being the seated 90/90 position. Variations in testing speeds and outcome measures, such as peak torque and external rotation (ER) ratios, were identified. Isokinetic dynamometry is a valuable tool for assessing shoulder strength in youth overhead athletes. It provides critical insights into muscle strength dynamics, aiding in injury prevention and rehabilitation. Further research is needed to optimize strength assessment protocols and enhance clinical decision-making for safe return-to-sport practices.

Genetic dissection of flour whiteness through genome-wide association analysis in common wheat (Triticum aestivum L.)

The color of flour products has an important influence on consumer acceptance. Flour color is largely determined and measured by the index of flour whiteness (FW) in China. In this study, an association population comprising 207 wheat (Triticum aestivum) accessions originating from seven countries was used for dissection of FW-related genetic loci through genome-wide association analysis. Six quantitative trait loci (QTLs) significantly associated with FW were identified, accounting for 7.87%–16.53% of the total phenotypic variation. Four KASP markers were developed from single-nucleotide polymorphisms associated with the QTLs QFW.HAAS-1AS, QFW.HAAS-1BL, QFW.HAAS-5AL, and QFW.HAAS-7AL. The phytoene synthase-encoding gene TraesCS7A03G1357000 (TaPsyA1) was identified as a candidate gene for QFW.HAAS-7AL. Two allelic variants of TaPsyA1 (designated PsyA1-a and PsyA1-b) were differentiated on the basis of a 37bp insertion/deletion polymorphism in the second intron. PsyA1-b included the 37bp insertion, which led to a translational frameshift in the gene and was associated with higher FW. The PsyA1-a allele lacked the 37bp insertion and was classified into two haplotypes according to the number of repeated ‘TC’ units in a simple sequence repeat in the promoter region. Of the two PsyA1-a haplotypes, the Type 1 haplotype conferred higher FW, flour brightness, and flour redness, and lower yellow pigment content and flour yellowness. The KASP markers and PsyA1 polymorphic markers developed in the present study are suitable for use in molecular marker-assisted selection for improvement of wheat FW.

Feed Efficiency and Surplus Feed Intake among Norwegian Red Dairy Cows.

Feed in livestock production is a major cost driver and closely linked to GHG emissions from the sector. Hence, there is a lot of interest to improve feed efficiency of livestock and promote economic and environmental sustainability of livestock production. Residual feed intake (RFI) is one common indicator of feed efficiency of dairy cows. However, RFI has both conceptual (e.g., confounding the effects of measurement error and unobserved heterogeneity) and practical limitations (e.g., negative values and non-monotonicity with feed efficiency). Therefore, we estimated feed efficiency of 48 early- to mid-lactation Norwegian Red dairy cows based on intake and performance data collected for 54 d using a stochastic feed requirement frontier (SFRF). The SFRF predicted the minimum feed intake each cow required to support its production and maintenance needs, accounting for parity, lactation stage, body reserve mobilization, unobserved cow-specific heterogeneity, and statistical noise. Feed efficiency of each cow was then estimated in 2 ways: first by computing a feed efficiency score as a ratio of the prediction from the SFRF to the observed feed intake of each cow, and second by computing surplus feed intake (SFI) of each cow as a difference between observed and predicted feed intake. Furthermore, it was shown that feed efficiency can be decomposed into time-invariant and time-varying parts. Results showed that the average feed efficiency score was 89.7% and it was time-invariant for the period covered during the study. The score implies 10.3% of the observed feed intake was SFI. In absolute terms, the SFI amounted to 13.3 kg DM/wk on average. However, cows in the least feed efficient quartile had SFI of almost 5 times higher than cows in the most feed efficient quartile. Furthermore, cow-specific feed intake variation accounted for only 53.9% of the total feed intake variation. The remaining 46.1% of the feed intake variation was due to statistical noise. Out of the cow-specific feed intake variation, 82.1% was due to differences in feed efficiency while the remaining 17.9% was due to other sources of unobserved cow-specific heterogeneity. When implemented with lifetime data, the feed efficiency decomposition approach presented in this study enables understanding of the temporal trajectory of feed efficiency within and across lactations. Furthermore, it allows identification of feed efficiency that is repeatable over lifetime. facilitating the inclusion of feed efficiency in breeding programs.