This study aims to evaluate the influence of rumen-protected methionine (RPM) on the milk yield and milk compositions of dairy cows by employing a meta-analysis method. The articles in the publication databases between January 2010 and January 2022 which reported on various concentrations of RPM supplements in dairy cow diets and then monitored the milk yield and milk compositions were searched. A total of 14 studies were included, covering 27 treatments with a total of 623 dairy cows. Comprehensive Meta-Analysis V3 was used for statistical analysis, the forest map was drawn by the standard mean difference (SMD) with a 95% confidence interval (95% CI), and the SMD was calculated by a random effect model. The dose effect curve was drawn by fitting the SMD and RPM dose of each study to explore the optimal dosage of RPM. Compared with the basal diet, the RPM supplement significantly increased the percentages of milk fat (SMD (95% CI): 1.017% [0.388, 1.646]) and milk protein (SMD (95% CI): 0.884 [0.392, 1.377]). However, the milk yield (SMD (95% CI): 0.227 kg/d [−0.193, 0.647]) and lactose concentration (SMD (95% CI): 0.240% [−0.540, 1.020]) were not affected. The subgroup analysis found that the effect of the RPM supplement on the milk fat and milk protein was greater in the high-protein feed than in the low-protein feed. Multiple regression analysis showed that feeding RPM significantly improved the milk yield and milk protein percentage of dairy cows. The results of the dose–effect analysis show that the optimal range for the RPM was 7.5–12.5 g/d. RPM supplements in a dairy diet can improve the milk protein percentages and milk fat percentages of dairy cows.

The effects of sodium selenite or selenium yeast on the meat quality of broilers were searched in the literature published in the Chinese National Knowledge Infrastructure (CNKI), Wanfang Database, China Science and Technology Journal Database (VIP), PubMed, Web of Science, and Science Direct databases from January 1, 2010 to December 31, 2022. Meta-analysis was performed with Stata software (StataCorp. 2011), and the standardized mean difference (SMD) and its 95% confidence interval (CI) were calculated using a random effects model. Twenty of the identified 846 literature sources, which included 791 broilers, were screened. The meat quality indices considered were shear force, drip loss, cooking loss, water holding capacity (WHC), pH, and color. The source of heterogeneity was studied using sensitivity and subgroup analyses, and publication bias was evaluated using funnel plots. The results showed that the supplementation of selenium in the broiler diet significantly reduced the shear force (SMD = -0.67, 95% CI [-1.12, -0.22], P < 0.05) and drip loss (SMD = -0.84, 95% CI [-1.39, -0.30], P < 0.05) and increased the pH (SMD = 0.38, 95% CI [0.01, 0.75], P < 0.05) of broiler breast muscle; however, it had no significant effects on other indices. Funnel plots revealed a slight publication bias in the shear force and pH of breast muscle but none in the drip loss of breast muscle. The sensitivity analysis showed that the results were stable and reliable. In conclusion, selenium supplementation in broiler feed can improve some indices of broiler meat quality, and its inclusion in broiler diets is recommended, in conjunction with other minerals, which is of great significance to improve the quality, preservation time and economic benefits of chicken products.

With the establishment of the action plan for the goal of “carbon peaking and carbon neutrality”, how to achieve high-quality agricultural development, help implement the construction of the green Longjiang River, reduce agricultural carbon emissions, and increase the level of agricultural carbon sink is a key problem that must be solved for Heilongjiang Province to achieve the goal of “double carbon”. This article uses the Life Cycle Assessment (LCA) method to estimate the carbon emissions of animal husbandry in Heilongjiang Province and 13 cities from 2000 to 2020. By constructing the Tapio decoupling model, Kaya identity, and the LMDI model, the relationship between animal husbandry economy and carbon emissions in Heilongjiang Province and the driving factors affecting animal husbandry carbon emissions are explored. The results indicate that: (1) From 2000 to 2020, the carbon emissions of animal husbandry in Heilongjiang Province showed an overall slightly upward trend. From the perspective of various emission links, the highest carbon emissions are from the gastrointestinal fermentation environment (42.49%), with beef cattle, cows, and live pigs being the main livestock and poultry in Heilongjiang Province with carbon emissions. (2) The Tapio decoupling model results indicated that from 2000 to 2020, the relationship between the economic development of animal husbandry in Heilongjiang Province and carbon emissions was mainly characterized by weak decoupling. (3) The main driving force behind the continuous increase in carbon emissions from animal husbandry in Heilongjiang Province is the changing factors of agricultural population returns and changes in the production structure of animal husbandry; The driving factors that suppress the increase in carbon emissions from animal husbandry in Heilongjiang Province are changes in animal husbandry production efficiency, population and urban development levels, and population mobility factors. Finally, based on the decoupling effect status and driving factors of decomposition between Heilongjiang Province and its various cities, it is recommended to implement countermeasures and suggestions for the transformation of animal husbandry in the province towards green and low carbon at the macro level. This can be achieved through the adoption of sustainable and eco-friendly practices such as the use of renewable energy sources and the reduction of greenhouse gas emissions. Additionally, promoting research and development in sustainable agriculture and animal husbandry can also contribute to the transformation towards a more environmentally friendly industry.

This study aimed to investigate the effects of dietary metabolizable energy levels on various performance indicators of medium-sized geese, with the goal of predicting the optimal range of these energy levels. A comprehensive literature search was conducted across several databases, including Chinese National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, PubMed, Web of Science, and ScienceDirect, covering the period from January 1, 2000, to July 1, 2024. The gathered studies focused on the impact of dietary metabolizable energy levels on the production performance of medium-sized geese. Following the literature review, a network meta-analysis was conducted by Stata software (StataCorp version 14.0). The analysis included tests for inconsistencies in the results by inconsistency model, assessment of publication bias by funnel plots, and data sorting through the robust error meta-regression model. Additionally, nonlinear dose-response curves were plotted by the restricted cubic spline method to explore the relationships between metabolizable energy levels and production performance indicators. Out of 2267 identified studies, 25 met the inclusion criteria and were incorporated into the systematic review, representing a total sample of 3538 geese. The production performance indicators examined included average daily gain, average daily feed intake, feed-to-gain ratio, and abdominal fat percentage. The results of the network meta-analysis revealed that both direct and indirect comparisons could be made across different dietary metabolizable energy levels reported in the studies. It was observed that increasing dietary metabolizable energy levels significantly impacted certain performance indicators of medium-sized geese. The findings were robust and reliable for further analysis. The dose-response meta-analysis indicated optimal dietary metabolizable energy levels within the existing ranges, specifically 13 to 13.5 MJ/kg for medium-sized geese during the brooding stage, and 12 to 13 MJ/kg during the growing stage. Future research should explore the effects of dietary metabolizable energy levels in large-sized geese, small-sized geese, and diets with higher energy levels to broaden the understanding of energy optimization across different goose sizes and developmental stages.

Many factors influence the effects of exogenous organic chromium (EO-Cr) on the growth performance and carcass qualities of weaned and growing-finishing pigs, such as pig growth stages, types of EO-Cr, period of supplementation, and farm management. However, it is challenging to comprehensively consider all factors in one study. To solve this problem, we searched all relative literature published from 1 January 2000 to 1 January 2023, to systematically analyze and review the effects of EO-Cr on pig growth performance and carcass qualities via meta-analysis. Thirty-five papers were filtered and analyzed, which involved 4366 pigs. The results showed that, for weaned piglets, EO-Cr diets significantly increased the average daily gain (ADG, p < 0.001) and average daily feed intake (ADFI, p = 0.022) but reduced the feed–gain ratio (p = 0.004). In addition, for growing-finishing pigs, EO-Cr supplementation significantly increased the ADG (p < 0.001), carcass lean ratio (p = 0.020), and loin muscle area (p < 0.001), but had no significant effect on the ADFI (p = 0.071), feed–gain ratio (p = 0.692), dressing percent (p = 0.989), or back fat thickness (p = 0.142). Moreover, the effect of EO-Cr was greater in weaned piglets than in growing-finishing pigs. In terms of the dose effect of the supplement, chromium nicotinate is the most suitable EO-Cr type for weaned piglets with an optimal dosage range of 0.125–0.150 mg/kg. On the other hand, chromium picolinate is the most suitable EO-Cr type for growing-finishing pigs with an optimal dosage range of 0.250–0.300 mg/kg. In conclusion, EO-Cr supplementation is beneficial for enhancing the growth performance and carcass qualities of both weaned and growing-finishing pigs.