Aurantiochytrium sp. meal as DHA source in Nile tilapia diet,part II: Body fatty acid retention and muscle fatty acid profile

Nile tilapia juveniles (8.35 ± 0.80 g) were fed on four levels (0.0%; 0.5%; 1.0%; 2.0%, 4.0%) of Aurantiochytrium sp. meal (ALL‐G‐RICH?), a source of docosahexaenoic acid (DHA). The 1% Aurantiochytrium sp. meal diet was compared to a control diet, which contained the same amount of DHA as cod liver oil (CLO) at 1.7% diet. Groups of 25 fish were stocked in 100 L tanks and fed twice daily until apparent satiation, for 57 days, at 28°C. Increasing dietary Aurantiochytrium sp. meal reduced the body retention of DHA and n‐3 polyunsaturated fatty acids (n‐3 PUFA) but increased the body retention of alpha‐linolenic (α‐LNA), linoleic (LOA) and n‐6 polyunsaturated fatty acids (n‐6 PUFA). Fatty acid profile in tilapia muscle was affected by increasing dietary inclusions of Aurantiochytrium sp. meal, with an increase in DHA, α‐LNA, n‐3 PUFA and n‐3 long chain‐polyunsaturated fatty acids (n‐3 LC‐PUFA) but a decrease in monounsaturated fatty acids (MUFA), n‐6 PUFA and n‐6 long‐chain polyunsaturated fatty acids (n‐6 LC‐PUFA). There was a larger body retention of DHA, α‐LNA, LOA, n‐3 PUFA and n‐6 PUFA fatty acids and a higher percentage of DHA, n‐3 PUFA and n‐3 LC‐PUFA in muscle fatty acid profile in fish fed on CLO diets than in those fed on 1% Aurantiochytrium sp. Therefore, Aurantiochytrium sp. meal is an alternative source of DHA for Nile tilapia diets.     

Effects of beneficial bacteria on biomass,photosynthetic parameters and cell composition of the microalga Muriellopsis sp. adapted to grow in seawater

The present study evaluated the effects of five bacterial isolates from the microalga Muriellopsis sp. on the microalgal biomass concentration (g/L), specific growth rate (K), photosynthetic quantum yield (QY), non‐photochemical quenching (NPQ), maximum relative electron transport rates (rETR max) and levels of nutritional components such as carbohydrates, lipids, proteins and carotenoids in Muriellopsis sp. cultivated in seawater under indoor and outdoor conditions. The bacterial strains were Microbacterium sp. Dom 1; Pseudomonas sp. Dom2; Microbacterium sp. Dom 3; Rhizobium sp. Dom 4; and Dietzia sp. Dom 5, as well as the Pseudoalteromonas sp. (SLP1), a bacterium known to promote the growth of microalgae. At the laboratory level, inoculation of the strains SLP1, Dom 1, Dom 3 and Dom 5 resulted in higher specific growth rates and biomass of the microalga. Subsequently, the best results were obtained with a combination of the selected bacterial strains (Dom1, Dom 3, Dom5 and SLP1) under outdoor culture conditions improved the biomass, proteins, carbohydrates and total carotenoids in 22.12%, 48.28%, 19,25% and 48.27%, respectively, compared to cultures without the incorporation of the selected bacteria (control), while no effects were observed on the photosynthetic parameters. Thus, it was demonstrated that positive associations of the selected bacterial strains played an important role in the production of Muriellopsis sp. acclimatized to grow in seawater. This is of crucial importance, especially in desert areas, where solar radiation is high and freshwater is a limited resource.     

Establishment techniques affect productivity,nutritive value and atmospheric N2 fixation of two sunn hemp cultivars

Nitrogen fertilization is a common practice for sustaining forage production in forage systems in southeastern United States. Warm-season annual legumes may be an alternative forage to warm-season perennial grasses that do not require N fertilization. Sunn hemp (Crotalaria juncea L.) is a fast-growing, warm-season annual legume native to India and Pakistan. The objective of this 2-year study was to assess the herbage accumulation (HA), atmospheric N₂ fixation (ANF) and nutritive value of sunn hemp. Treatments were the factorial arrangement of two sunn hemp cultivars (“Crescent Sun” and “Blue Leaf”), three seeding rates (17, 28 and 39 kg seed/ha) and seed inoculation (inoculated or non-inoculated seeds), distributed in a randomized complete block design with four replicates. Crescent sun had greater HA (3,218 vs. 1764 kg DM/ha) and ANF (41 vs. 25 kg N/ha). Blue leaf had greater crude protein (CP) (188 vs. 176 g/kg) and in vitro digestible organic matter (IVDOM) concentrations (564 vs. 531 g/kg) than crescent sun. Non-inoculated seed had greater CP than inoculated seed, 188 and 177 g/kg, respectively, and inoculation did not affect HA. Intermediate seeding rate (28 kg/ha) decreased HA (2002 kg DM/ha), while HA from high and low seeding rates (17 and 39 kg/ha, respectively) did not differ (2,863 and 2,615 kg DM/ha respectively). Planting non-inoculated crescent sun at 17 kg/ha seeding rate is a feasible management practice to produce sunn hemp in subtropical regions; however, inoculation should always be recommended for proper establishment.     

Detection of Ecballium elaterium in hedgerow olive orchards using a low-cost uncrewed aerial vehicle and open-source algorithms

BACKGROUND

Ecballium elaterium (common name: squirting cucumber) is an emerging weed problem in hedgerow or superintensive olive groves under no tillage. It colonizes the inter-row area infesting the natural or sown cover crops, and is considered a hard-to-control weed. Research in other woody crops has shown E. elaterium has a patchy distribution, which makes this weed susceptible to design a site-specific control strategy only addressed to E. elaterium patches. Therefore, the aim of this work was to develop a methodology based on the analysis of imagery acquired with an uncrewed aerial vehicle (UAV) to detect and map E. elaterium infestations in hedgerow olive orchards.

RESULTS

The study was conducted in two superintensive olive orchards, and the images were taken using a UAV equipped with an RGB sensor. Flights were conducted on two dates: in May, when there were various weeds infesting the orchard, and in September, when E. elaterium was the only infesting weed. UAV-orthomosaics in the first scenario were classified using random forest models, and the orthomosaics from September with E. elaterium as the only weed, were analyzed using an unsupervised algorithm. In both cases, the overall accuracies were over 0.85, and the producer's accuracies for E. elaterium ranged between 0.74 and 1.00.

CONCLUSION

These results allow the design of a site-specific and efficient herbicide control protocol which would represent a step forward in sustainable weed management. The development of these algorithms in free and open-source software fosters their application in small and medium farms. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Influence of race and crossbreeding on casein micelles size

Casein (CN) micelles are colloidal aggregates of protein dispersed in milk, the importance of which in the dairy industry is related to functionality and yield in dairy products. The objective of this work was to investigate the correlation of milk CN micelles diameter from Holstein and Zebu crossbreds with milk composition (protein, fat, lactose, total and nonfat solids and milk urea nitrogen), somatic cell count (SCC), age, lactation stage and production. Average casein micelles diameters of milk samples obtained from 200 cows were measured using photon correlation spectroscopy and multiple regression analysis was used to find relationship between variables. CN micelle diameter, SCC and nonfat solids were different between animals with different Holstein crossbreed ratios, which suggests influence of genetic factors, mammary gland health and milk composition. Overall, results indicate the potential use of CN micelle diameter as a tool to select animals to produce milk more suitable to cheese production.     

Effects of different five-day progesterone-based synchronization protocols on the estrous response and follicular/luteal dynamics in dairy cows

This study compared the responses shown by lactating dairy cows to four different P4-based protocols for AI at estrus. Cows with no estrous signs 96 h after progesterone intravaginal device (PRID) removal were subjected to fixed-time AI (FTAI), and their data were also included in the study. In Experiment I, follicular/luteal and endometrial dynamics were assessed every 12 h from the beginning of treatment until AI. The estrous response was examined in Experiment II, and fertility was assessed in both experiments. The protocols consisted of a PRID fitted for five days, along with the administration of different combinations of gonadotropin releasing hormone (GnRH), equine chorionic gonadotropin and a single or double dose (24 h apart) of prostaglandin F_2α. In Experiment I (40 cows), animals receiving GnRH at the start of treatment showed a significantly higher ovulation rate during the PRID insertion period while estrus was delayed. In Experiment II (351 cows), according to the odds ratios, cows showing luteal activity at the time of treatment were less likely to show estrus than cows with no signs of luteal activity. Treatment affected the estrous response and the interval from PRID removal to estrus but did not affect conception rates 28–34 days post AI. Primiparous cows displayed a better estrous response than multiparous cows. Our findings reveal acceptable results of 5-day P4-based protocols for AI at estrus in high-producing dairy cows. Time from treatment to estrus emerged as a good guide for FTAI after a 5-day P4-based synchronization protocol.     

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.