Soil quality assessments in integrated crop–livestock–forest systems: A review

Integrated crop–livestock–forest is a promising strategy to improve soil quality. It comprises four different integrated farming systems: crop–livestock, crop–forest, forest–livestock and crop–livestock–forest. This work systematically reviewed studies about integrated crop–livestock–forest systems and soil quality. A total of 92 papers were retrieved from the Web of Science—Clarivate Analytics platform, and the following information was analysed: publication year, institution, region of the studied site, type of integrated system, soil type, tillage system, maximum soil depth and the soil quality indicators assessed. Most studies were published in the second half of the 2010s. Brazil is a prominent focus of research about soil quality and integrated crop–livestock–forest systems, with significant contribution from its central and southern regions. The Embrapa was the main publishing institution, present in over one‐third of the studies. Crop–livestock was the most common integrated system, Ferralsols was the most common soil group, and most of the studied soils were clayey. No tillage was the main tillage system. Most studies focused on the topsoil, assessing physical and/or chemical soil quality indicators. More emphasis on biological indicators of soil quality is required, as well as assessments integrating biological, physical and chemical indicators of soil quality. Future works should compare different integrated systems, including assessments deeper in the soil profile, especially in systems with the forest component, and also in sandy and silty soils. Soil quality indicators that have been rarely used should be further tested. Novel indicators should be added to better understand the promotion of soil quality by integrated crop–livestock–forest systems.     

The effect of life history events on carcass merit and price of cull dairy cows

Cull dairy cows contribute almost 10% of national beef production in the United States. However, different factors throughout the life of dairy cows affect their weight and overall body condition as well as carcass traits, and consequently affect their market price. Therefore, the objectives of this study were: (1) to assess relationships between price ratio and carcass merit of cull dairy cows sold through several sites of an auction market and (2) to investigate the effect of animal life history events and live weight on sale barn price (BP) and price ratio (as a measure of relative price), as an indicator of carcass merit. Data from 4 dairy operations included 3,602 cull dairy cow records during the period of 2015 to 2019. Life history events data were collected from each dairy operation through Dairy Comp software; live weight and price were obtained periodically from the auction market, and the carcass data were provided by a local packing plant. Cow price in dollars per unit of live weight ($/cwt) and price ratio were the 2 outcome variables used in the analyses. Price ratio was created aiming to remove seasonality effects from BP (BP divided by the national average price for its respective month and year of sale). The association between price ratio and carcass merit traits was investigated using canonical correlation analysis, and the effect of life history events on both BP and price ratio was inferred using a multiple linear regression technique. More than 70% of the cows were culled in the first 3 lactations, with an average live weight of 701.5 kg, carcass weight of 325 kg, and dressing percentage of 46.3%. On average, cull cows were sold at $57.0/cwt during the period considered. The canonical correlation between price ratio and carcass merit traits was 0.76, indicating that price ratio reflected carcass merit of cull cows. Later lactations led to lower BP compared with cows culled during the first 2 lactations. Injury, and leg and feet problems negatively affected BP. Productive variables demonstrated that the greater milk production might lead to lower cow prices. A large variation between farms was also noted. In conclusion, price ratio was a good indicator of carcass merit of cull cows, and life history events significantly affected sale BP and carcass merit of cull cows sold through auction markets.     

Emerging issues in genomic selection

Genomic selection (GS) is now practiced successfully across many species. However, many questions remain, such as long-term effects, estimations of genomic parameters, robustness of genome-wide association study (GWAS) with small and large datasets, and stability of genomic predictions. This study summarizes presentations from the authors at the 2020 American Society of Animal Science (ASAS) symposium. The focus of many studies until now is on linkage disequilibrium between two loci. Ignoring higher-level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, the selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make the computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWASs using small genomic datasets frequently find many marker-trait associations, whereas studies using much bigger datasets find only a few. Most of the current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit the computation of P-values from genomic best linear unbiased prediction (GBLUP), where models can be arbitrarily complex but restricted to genotyped animals only, and single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top-ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as 1 SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. Although many issues in GS have been solved, many new issues that require additional research continue to surface.     

Questionnaire on the process of recovering horses from general anesthesia and associated personnel injury in equine practice

ObjectiveTo collect data about the current practice of recovering horses from general anesthesia and recovery personnel safety.Study designOnline survey.MethodsAn online questionnaire, including questions on general demographic data, recovery drugs, modality and characteristics of equine recovery and morbidity and mortality, was designed and distributed via e-mail to equine practitioners worldwide.ResultsPractitioners from 22 countries completed 373 questionnaires; 53% of the participants were board-certified equine surgeons, and the remainder were board-certified anesthesiologists (18%), large animal residents (8%), general practitioners (7%), large animal interns (6%), anesthesia residents (4.5%) and veterinary technicians (1.6%). Respondents were employed by academia (58%) or private practice (42%). Of the respondents employed at a university, 93% had a board-certified anesthesiologist on staff compared with 7% of respondents employed at a private practice. Most of the respondents assist horses during recovery, with 23% assisting every recovery and 44% assisting recovery in the majority of cases. Reasons for choosing to assist horses during recovery were: orthopedic procedures (57%), neurological deficits (49%), bad health (47%), history of poor recovery (44%), foals (42%), draft breeds (30%), magnetic resonance imaging (17%) and computed tomography (16%). Unacceptable recoveries were reported by 77% of participants. Commonly reported complications during recovery with any method were: orthopedic injury (66%), myopathy (54%), skin abrasion (53%) and airway obstruction (37%). The incidences of unacceptable quality of recovery (p = 0.09) or personnel injury (p = 0.56) were not different between assisted and nonassisted recoveries; however, more equine fatalities were reported for assisted recoveries (p < 0.006). Practitioners in academia reported more unacceptable recoveries (p < 0.0007) and personnel injuries (p < 0.002) compared with those in private practice.ConclusionsThe method of recovery differs among hospitals. Recovery personnel injuries associated with assisting horses during recovery are an important and previously unreported finding.