Search Results (13)

The use of non-invasive methods can contribute to the development of predictive models for measuring carcass yield (CY) and hot carcass weight (HCW) in domestic ruminants. In this study, in vivo measurements of subcutaneous fat thickness (SFT) and ribeye area (REA) were performed on 111 Nellore heifers using ultrasound imaging. The animals were managed in crop–livestock integrated systems with different supplementation levels (SL). Four multiple regression equations were developed to estimate CY and HCW, using five predictor variables: SFT, REA, REA per 100 kg of body weight (REA100), live weight (LW), and SL. For the CY prediction models, when ultrasound measurements (SFT, REA, and REA100) were considered, the generated equations showed low R² and concordance correlation coefficient (CCC) values, indicating low predictive capacity for this trait. For HCW, the predictor variables stood out due to their high R² values. Additionally, the equation based solely on ultrasound measurements achieved a CCC greater than 0.800, demonstrating high predictive capacity. Based on these results, it can be concluded that ultrasound-derived measurements are effective for generating useful models to predict HCW. Thus, it will be possible to estimate the amount of carcass that will be produced even before the animals are sent to slaughterhouses. Full article

Modern agriculture faces the challenge of increasing production without expanding cultivated areas, promoting sustainable practices that ensure food security and environmental preservation. Integrated crop–livestock systems (ICLSs) stand out as an effective strategy, diversifying and intensifying agricultural production in a sustainable manner, ensuring adequate soil cover, and improving nutrient cycling efficiency. Thus, this study aimed to explore and compare integrated crop–livestock systems with Zuri guinea grass (Panicum maximum cv. BRS Zuri) and Quênia guinea grass (Panicum maximum cv. BRS Quênia) against the conventional soybean/maize succession method in a tropical region, and how these systems affect biomass decomposition, C:N ratio, nutrient cycling, and fertilizer equivalents. A field experiment was conducted in two phases: the first in the second-crop season and the second in the main season, using a randomized block design with four replicates. The treatments consisted of two ICLS systems, one with Zuri and Quênia guinea grasses established after soybean, and a succession system with maize established after soybean. The results indicated that Quênia guinea grass showed greater desiccation efficiency, with an injury rate of 86.5% at 21 days, 8.5% higher compared to Zuri guinea grass. In terms of biomass, Zuri and Quênia guinea grasses had average productions of 7021.1 kg ha⁻¹, which was 43.25% higher compared to maize biomass. The biomass decomposition of the grasses was faster due to their lower C:N ratio, resulting in greater nutrient release into the soil. Both forage grasses (Zuri and Quênia guinea grasses) are suitable for integrated crop–livestock systems, as they showed similar biomass production and nutrient accumulation. Soybean yield was not influenced by the different cropping systems, showing similar results between the biomass of Zuri and Quênia guinea grasses and maize. However, grass biomass enriches the soil more through the return of fertilizer equivalents, which in future studies could be considered for the reduction of mineral fertilizers, ensuring greater sustainability of agricultural systems. Full article

In the Brazilian Cerrado region, the soils have significant agricultural potential; however, they are naturally acidic soils due to the constitution of the source material and the high weathering process. Liming has been the main tool for correcting acidity and supplying Ca²⁺ and Mg²⁺ to the soil; however, the effect of the corrector is limited to the soil surface. Consequently, the benefits of liming are restricted to the surface layer of the soil and do not solve the subsurface acidity problems. The objective of this work was to evaluate the effect of the subsoiling operation together with the application of a soil acidity corrector on the nutrition and productivity of soybean crops. The experiment was carried out in the experimental area of the Federal University of Jataí in the state of Goias, Brazil. The experimental design was a randomized block design, consisting of six treatments and four replications. The experiment was implemented in 2018, and it utilized the following treatments: T1: control (without subsoiling and liming); T2: the application of superficial limestone, without incorporation at a dose of 1 Mg ha⁻¹; T3: limestone applied through gravity up to 60 centimeters (cm) deep using a subsoiler, with a spacing between the rods of 0.37 meters (m), at a dose of 2.82 Mg ha⁻¹; T4: limestone applied with the same implement used in T3, at the same dose, but with a spacing between the rods of 0.75 m; T5: subsoiling, without the use of liming; and T6: subsoiling and, subsequently, liming on the surface at a dosage of 1 Mg ha⁻¹. The superficial application of the oxide increases the mineral nutrition of plants, the production components, and the productivity of soybeans. There is no agronomic feasibility for using the subsoiler to incorporate limestone. Full article

The aims of this study were (i) to evaluate the effect of density, lineage, age, and time of day on dorsal surface temperature and (ii) to evaluate the effect of density and lineage on performance and carcass condemnations in broiler grillers. The evaluations were carried out in barns with the Dark House system, with two densities, 17 and 19 chickens/m² and two lineages, Cobb and Ross. The dorsal surface temperature of the chickens was measured by infrared thermography at 7, 14, 21, 23, 25 and 27 days of age, four times a day. The average daily weight gain, feed conversion, mortality, partial carcass condemnations, as well as those due to arthritis and dermatosis were also evaluated. The highest dorsal surface temperatures were observed in Cobbs housed at a density of 17 chickens/m², and in Ross housed at a density of 19 chickens/m². Cobbs housed at a 17 chickens/m² density showed the lowest feed conversion compared to Ross at the same density. Ross showed higher dorsal surface temperatures when compared to Cobbs at 14, 21, and 27 days. Cobbs showed higher percentages of partial carcass condemnation and arthritis compared to Ross. The higher density of broiler grillers in the Dark House system does not influence the dorsal surface temperature, performance, dermatosis, arthritis, and partial carcass condemnations. Full article

Automated activity monitoring (AAM) systems are critical in the dairy industry for detecting estrus and optimizing the timing of artificial insemination (AI), thus enhancing pregnancy success rates in cows. This study developed a predictive model to improve pregnancy success by integrating AAM data with cow-specific and environmental factors. Utilizing data from 1,054 cows, this study compared the pregnancy outcomes between two AI timings—8 or 10 h post-AAM alarm. Variables such as age, parity, body condition, locomotion, and vaginal discharge scores, peripartum diseases, the breeding program, the bull used for AI, milk production at the time of AI, and environmental conditions (season, relative humidity, and temperature–humidity index) were considered alongside the AAM data on rumination, activity, and estrus intensity. Six predictive models were assessed to determine their efficacy in predicting pregnancy success: logistic regression, Bagged AdaBoost algorithm, linear discriminant, random forest, support vector machine, and Bagged Classification Tree. Integrating the on-farm data with AAM significantly enhanced the pregnancy prediction accuracy at AI compared to using AAM data alone. The random forest models showed a superior performance, with the highest Kappa statistic and lowest false positive rates. The linear discriminant and logistic regression models demonstrated the best accuracy, minimal false negatives, and the highest area under the curve. These findings suggest that combining on-farm and AAM data can significantly improve reproductive management in the dairy industry. Full article

The objective of this research was to determine the potential for hay production of Quenia guinea grass (Megathyrsus maximus cv. BRS Quenia), Congo grass (Urochloa ruziziensis), and Xaraes palisade grass (Urochloa brizantha cv. Xaraes) following soybean cultivation (Glycine max) in the Brazilian Cerrado. The experimental field was divided into 12 plots, with 4 replicates of each grass species. Chemical composition, forage mass (FM), and the potential for milk and carcass production were determined for the three grasses. Principal component analysis showed that the total digestible nutrients (TDN) had the most significant influence on milk and carcass potential. Quenia guinea grass reached maximum forage accumulation at 134 days after soybean harvest, representing 4191.51 kg ha⁻¹ of FM. Congo grass and Xaraes palisade grass produced 4033.51 kg ha⁻¹ and 4437.22 kg ha⁻¹, respectively, in cuts made at 154 and 138 days. Quenia guinea grass had 20.71% soluble protein in its composition when harvested at 115 days. Regarding milk production potential, Congo grass, on the other hand, showed a linear reduction in milk production as the number of days after soybean harvest increased. As for carcass production potential, Congo grass demonstrated the highest carcass production potential (110.65 kg Mg⁻¹ FM) at 107 cutting days. Xaraes palisade grass had the highest FM production, while Quenia guinea grass stood out in soluble protein. Conversely, Congo grass showed greater potential for hay production when overseeding in soybeans, as it excelled in carcass production potential. Therefore, for this grass, the ideal point for haymaking should occur within up to 107 days after sowing. Full article

The quantification of forage availability in tropical grasses is generally done in a destructive and time-consuming manner, involving cutting, weighing, and waiting for drying. To expedite this process, non-destructive methods can be used, such as unmanned aerial vehicles (UAVs) equipped with high-definition cameras, mobile device images, and the use of the normalized difference vegetation index (NDVI). However, these methods have been underutilized in tropical pastures. A literature review was conducted to present the current state of remote tools’ use in predicting forage availability and quality in tropical pastures. Few publications address the use of non-destructive methods to estimate forage availability in major tropical grasses (Megathyrsus maximus; Urochloa spp.). Additionally, these studies do not consider the fertility requirements of each cultivar and the effect of management on the phenotypic plasticity of tillers. To obtain accurate estimates of forage availability and properly manage pastures, it is necessary to integrate remote methods with in situ collection of soil parameters. This way, it will be possible to train machine learning models to obtain precise and reliable estimates of forage availability for domestic ruminant production. Full article

This study aimed to assess the impact of intercropping pigeon pea (Cajanus cajan cv. Super N) with maize (Zea mays cv. AG 5055) and Paiaguás palisadegrass (Urochloa brizantha cv. BRS Paiaguás) on grain yield, silage chemical composition, and post-harvest grazing forage. The experiment was conducted on the School Farm of Instituto Federal Goiano, Campus Iporá. The experiment treatments consisted of three cropping systems: pigeon pea and Paiaguás palisadegrass intercropping (PPPG), maize and Paiaguás palisadegrass intercropping (CPG), and maize, pigeon pea, and Paiaguás palisadegrass intercropping (CPPPG), respectively. It was observed after the fermentation process that the PPPG silage promoted the lowest values of forage mass (FM) and a reduction in the dry matter (DM) concentration. The PPPG silage showed higher values of crude protein (75.28 g kg⁻¹ DM), while the CPPPG silage showed proportionately higher values of total digestible nutrients (616.11 g kg⁻¹ DM). The intercropping did not affect the corn grain productivity, thus obtaining an average value of 4.78 Mg ha^-1. After the silage harvest, during the dry season, a similar forage availability was obtained between the treatments (3.73 Mg ha⁻¹). All three cultivation strategies produced abundant forage for grazing, showing that integrated intercropping systems can mitigate the seasonality in tropical forage production. Full article

Crop–livestock integrated production systems (CLISs) combine cash-crop production and forage production in succession. There are plenty of options of forage cultivars with differences in production aspects and seeds cost, and there is little information on how the choice of forage cultivar can affect the results of a CLIS. We hypothesized that different forage cultivars can have important economic impacts on production systems. Thus, we evaluated the two-year economic results of using three forage species in a CLIS: (1) Urochloa ruziziensis; (2) Megathyrsus maximus cv. BRS Zuri e; and (3) Megathyrsus maximus cv. BRS Tamani. The system was evaluated during 2018 and 2019 with no-tillage soybean (Glycine max) cultivation from November to March and grazing of cattle from May to August. The seed costs were, on average, USD 25.27 ha⁻¹ for Ruziziensis grass, USD 39.97 ha⁻¹ for Zuri guinea grass, and USD 64.13 ha⁻¹ for Tamani guinea grass. Animal production varied from 96.4 to 147.5 kg of live weight per hectare per year and mean two-year soybean yields varied from 3849 to 4217 kg per hectare, both without differences between forage cultivars. However, the lowest values for animal and soybean yields were obtained with Ruziziensis grass, and the highest were obtained with Zuri grass. Thus, Zuri guinea grass presented a net income (NI) of USD 1039.87 ha⁻¹ with an annual return on equity (ROE) equal to 11.19%, while Ruziziensis grass obtained an NI equal to USD 612.65 ha⁻¹ with an ROE of 6.47%, demonstrating the economic impact of forage resource choice in CLISs. Therefore, the choice of forage cultivars adequate for the conditions of an individual farm can correspond to an increase of 69.7% in net income, which highlights the importance of continuing efforts to develop new cultivars and the simultaneous evaluation of these cultivars in different production scenarios in order to better recommend forage genetic resources for particular production environments. Full article

Purpose: The objective of this review is to describe the main technologies (automated activity monitors) available commercially and under research for the detection of estrus and calving alerts in dairy cattle. Sources: The data for the elaboration of the literature review were obtained from searches on the Google Scholar platform. This search was performed using the following keywords: reproduction, dairy cows, estrus detection and parturition, electronic devices. After the search, the articles found with a title related to the objective of the review were read in full. Finally, the specific articles chosen to be reported in the review were selected according to the method of identification of estrus and parturition, seeking to represent the different devices and technologies already studied for both estrus and parturition identification. Synthesis: Precision livestock farming seeks to obtain a variety of information through hardware and software that can be used to improve herd management and optimize animal yield. Visual observation for estrus detection and calving is an activity that requires labor and time, which is an increasingly difficult resource due to several others farm management activities. In this way, automated estrous and calving monitoring devices can increase animal productivity with less labor, when applied correctly. The main devices available currently are based on accelerometers, pedometers and inclinometers that are attached to animals in a wearable way. Some research efforts have been made in image analysis to obtain this information with non-wearable devices. Conclusion and applications: Efficient wearable devices to monitor cows’ behavior and detect estrous and calving are available on the market. There is demand for low cost with easy scalable technology, as the use of computer vision systems with image recording. With technology is possible to have a better reproductive management, and thus increase efficiency. Full article

Legume–grass intercropping systems are a sustainable option to improve nutritional quality of animal feed and decrease livestock greenhouse gas emissions. Thus, the present study evaluated yield, chemical composition and in vitro gas production of silages produced with intercropped palisade grass (Urochloa brizantha.(A.Rich.) R.D.Webster), pigeon pea (Cajanus cajan cv. Super N) and corn (Zea mays. L.). Forage was harvested and placed inside micro-silos, which were opened after 100 days and samples were collected for chemical composition and in vitro gas production analyses. Intercropped silage had higher crude protein, acid detergent fiber, and lignin content than corn silage. Moreover, intercropped silage decreased total gas and methane production. Therefore, intercropped silage showed potential to increase conserved feed nutritional quality and reduce methane emissions in livestock production systems. Full article

Heat stress is considered a limiting factor for sheep production. We used information from physiological characteristics linked to heat tolerance to determine whether infrared thermography temperatures were able to separate groups of animals and determine the most important variables in this differentiation. Forty-eight four-month-old male lambs from eight genetic groups were used. Physiological (rectal temperature–RT, heart rate–HR, respiratory rate–RR) and blood traits, infrared thermography temperatures, heat tolerance indices, body measurements, weight and carcass traits were measured. Statistical analyses included variance, correlations, factor, discrimination and regression. Observing the correlations between physiological characteristics (RT, RR and HR) with temperatures measured by infrared thermography, regions for further studies should include the mean temperature of flank, nose and rump. Results show that there are strong relationships between thermograph measurements and RR, RT and HR in lambs, which are suggested to be directly correlated with heat tolerance capacity of the different genetic groups evaluated in this study. The assessment of body surface temperature measured by the thermograph could be used as a noninvasive tool to assess heat tolerance of the animals. Full article