Developing policies to reduce carbon emissions in agriculture is crucial for achieving the ‘dual carbon’ goal. Therefore, scientifically analysing the temporal and spatial distribution characteristics of agricultural carbon sinks and their driving factors holds paramount importance for the coordinated and integrated development of regional agriculture and the realization of sustainable development. Based on the perspective of carbon cycle in agricultural production, the measurement system of agricultural net carbon sink was established from the perspective of carbon sink/carbon source, this study conducted an analysis of the temporal and spatial variation characteristics as well as driving mechanisms of agricultural net carbon sinks. The findings are as follows: (1) The agricultural net carbon sink exhibited an increasing trend from 2009 to 2020, with favourable intensity and level. (2) Agricultural land use and livestock and poultry production constituted the primary sources of agricultural carbon emissions. Notably, agricultural carbon emissions demonstrated a decreasing trend during the study period. (3) The net agricultural carbon sink displayed local spatial aggregation, indicating significant regional differences. (4) Factors such as rural economic level, urbanization level and agricultural employment significantly promoted the net carbon sink. In contrast, the rural industrial structure, technical level and crop seeding had inhibitory effects. Therefore, it is imperative to promote the reduction of agricultural carbon emissions in the Beijing-Tianjin-Hebei region. This entails accelerating the construction of new agriculture and rural areas, facilitating industrial upgrading, promoting the development of low-carbon-sink regions into high-carbon-sink regions and actively fostering the coordinated and integrated development of regional agriculture.

Varietal identification plays a pivotal role in viticulture for several purposes. Nowadays, such identification is accomplished using ampelography and molecular markers, techniques requiring specific expertise and equipment. Deep learning, on the other hand, appears to be a viable and cost-effective alternative, as several recent studies claim that computer vision models can identify different vine varieties with high accuracy. Such works, however, limit their scope to a handful of selected varieties and do not provide accurate figures for external data validation. In the current study, five well-known computer vision models were applied to leaf images to verify whether the results presented in the literature can be replicated over a larger data set consisting of 27 varieties with 26 382 images. It was built over 2 years of dedicated field sampling at three geographically distinct sites, and a validation data set was collected from the Internet. Cross-validation results on the purpose-built data set confirm literature results. However, the same models, when validated against the independent data set, appear unable to generalize over the training data and retain the performances measured during cross validation. These results indicate that further enhancement have been done in filling such a gap and developing a more reliable model to discriminate among grape varieties, underlining that, to achieve this purpose, the image resolution appears to be a crucial factor in the development of such models.

The use of silvopastoral systems with tree legumes is a viable alternative to recover and develop pastures, as they add N to the system influencing pasture growth. This study hypothesized that the herbage and litter of signalgrass (Urochloa decumbens Stapf) is affected by legume trees in the pasture. Treatments were composed of (1) signalgrass + Mimosa caesalpiniifolia Benth.; (2) signalgrass + Gliricidia sepium Jacq.; and (3) signalgrass monoculture. The 3-year experiment followed a randomized complete block design with three replications. Tree legumes were planted in double rows (15 × 1 × 0.5 m), in 1 ha paddocks. Litter samples were taken in five distance points (0, 1.8, 3.7, 5.6 and 7.5 m) perpendicular to tree legume rows. Signalgrass was taller at longer distances from the trees (P < 0.05). Signalgrass height differed between treatments, with taller signalgrass found in pastures mixed with G. sepium (15.6 cm) compared to M. caesalpiniifolia (9 cm) (P < 0.05). Herbage N content decreased with increasing distance from tree rows (P < 0.05). Litter N content followed a similar pattern, ranging from 23 g/kg under the trees to 12 g/kg at 7.5 m away from tree rows. Signalgrass did not grow under the tree crown (0–1.8 m), especially when intercropped with M. caesalpiniifolia. The findings of this study suggest that the type of legume trees used in the silvopastoral system has the potential to modify the pattern of grass growth and content of N in pasture litter.

The study evaluated forage and livestock performance in different grazing systems over two years. Treatments were three contrasting grazing systems: (I) N-fertilized bahiagrass (Paspalum notatum Flüggé) in the summer overseeded during the winter by N-fertilized ryegrass (Lolium multiflorum) and oat (Avena sativa L.) (Grass + N); (II) unfertilized bahiagrass during the summer overseeded with ryegrass + oat and a blend of clovers (Trifolium spp.) in the winter (Grass + Clover); (III) unfertilized bahiagrass and rhizoma peanut (RP; Arachis glabrata Benth.) mixture during summer, overseeded during winter by ryegrass + oat + clovers mixture (Grass + Clover + RP). Average daily gain (ADG), gain per area (GPA), and stocking rate (SR) in the winter did not differ across treatments and averaged 0.87 kg/d (P = 0.940), 303 kg/ha, and 2.72 AU/ha. In the summer, Grass + Clover + RP had greater ADG than Grass + N (0.34 vs. 0.17 kg/d, respectively). During the summer, the GPA of Grass + Clover + RP was superior to Grass + N (257 vs. 129 kg/ha, respectively), with no difference in SR among treatments at 3.19 AU/ha. Over the entire year, ADG and GPA tended to be greater for Grass + Clover + RP. Annual SR differed between treatments, where Grass + N was greater (3.37 AU/ha) than the other treatments, which averaged 2.76 AU/ha. Integration of legumes into pasture systems in the summer and winter contributes to developing a sustainable grazing system, reducing N fertilizer use by 85% while tending to increase livestock productivity even though SR was decreased by 18%.

Simplified cereal-based crop rotations are widely grown due to economic reasons, leading to the cultivation of wheat after wheat and associated yield losses. In this study, a crop rotation trial was conducted in Northern Germany on a Stagnic Luvisol from 2006 to 2018 with winter wheat after the four most widely used preceding crops in the region (sugar beet, winter wheat, silage maize and winter oilseed rape) in different crop rotations to evaluate potential benefits of different preceding crops. Additionally, the effects of two different sowing dates (2016–2018) and higher crop residue input (whole period) were investigated.

While the pre-preceding crop had no effect, preceding crops winter oilseed rape and sugar beet led to a significantly higher yield of about 1.00 and 0.43 t/ha, respectively, compared to wheat after wheat. This was not modified by crop rotational diversity, including wheat monoculture. Wheat yield tended to be higher for the late sowing date after sugar beet, maize and wheat, while there was no effect of sowing date after oilseed rape. Higher crop residue input led to a significantly higher yield (0.30 t/ha) in wheat after wheat (after pre-preceding crop sugar beet). Overall, sugar beet and winter oilseed rape were found to be favourable preceding crops for winter wheat under the given site conditions. The effect of sowing date on yield and potential modifications of the preceding crop effect by sowing date needs further research in appropriate long-term trials.

This study was conducted to determine the effect of reducing calcium (Ca) and available phosphorus (AvP) on performance, carcass yield, tibia traits and jejunum histomorphology in broilers. For this purpose, 480 one-day-old Ross 308 male chicks were distributed into four trial groups with eight subgroups. During the starter period, birds were fed with recommended or reduced Ca and AvP contents of 66.7 and 62.5 g/kg, respectively. Calcium and AvP contents of the groups were as follows: control: 8.70 g/kg Ca, 4.40 g/kg AvP for grower and 7.80 g/kg Ca, 3.90 g/kg AvP for finisher; LCP1: 8.30 g/kg Ca, 4.20 g/kg AvP for grower and 7.10 g/kg Ca, 3.50 g/kg AvP for finisher; LCP2: 7.90 g/kg Ca, 4.00 g/kg AvP for grower and 6.00 g/kg Ca, 3.00 g/kg AvP for finisher; LCP3: 7.00 g/kg Ca, 3.80 g/kg for grower and 5.00 g/kg Ca, 3.00 g/kg AvP for finisher. Performance variables have been calculated from the data of each period, and samples were obtained from the slaughtered birds on the final day of the trial (42nd day) for carcass and tibia traits and jejunum histomorphology. Reducing dietary Ca and AvP did not affect the broiler performance, carcass yield and mortality. Tibia ash decreased in LCP2 and LCP3 groups (P < 0.01). Villus width and villus surface area increased in LCP2 and LCP3. Overall, feeding with a diet 100 g/kg lower than the recommended Ca and AvP did not affect performance in broilers, but improved jejunal development.

This study investigates the genetic and phenotypic aspects of early growth performance in the Murciano-Granadina goat breed, using data collected between 2016 and 2022 from a private dairy farm in Ghale-Ganj city, located in the southern area of Kerman province, Iran. Pedigree and data information were collected on several early body weight traits, including birth weight (BW), weaning weight (WW), average daily gain (ADG), Kleiber ratio (KR) and growth efficiency from birth to weaning (GE). Nine univariate animal models included direct additive genetic effects and different combinations of maternal effects were compared by using Akaike information criterion (AIC). Among the tested models, the best genetic analysis model for BW, included direct additive, maternal additive, maternal permanent and maternal temporary environmental effects. The best model for ADG, KR and GE included direct additive, maternal permanent and litter effects. For WW, the best model was determined to be one that included direct additive and maternal additive genetic effects. The estimated direct heritabilities were low values of 0.04, 0.07, 0.08, 0.05 and 0.07 for BW, ADG, KR, GE and WW, respectively. The estimates of genetic correlations among the studied traits were positive and low to high in magnitude which ranged from 0.11 for BW-KR to 0.91 for BW-GE. The phenotypic correlations ranged from 0.03 for KR-WW to 0.87 for ADG-KR. The positive correlations observed among the studied growth traits of the Murciano-Granadina goat breed indicate no negative genetic or phenotypic changes associated with selection for these traits.

Soil available phosphorus (SAP) and potassium (SAK) are indispensable for crops, and their stocks are important for food production needed for a growing global population. This study analysed 991 soil profiles across a large part of Romania covering forestland, grassland and cropland in almost all ecological regions. This study investigated SAP and SAK stocks for different soil depths and characterized their magnitude and variability within land uses under different environmental ecosystems, soil classes and soil types, for a better soil and land management under a temperate-continental climate. Cropland soils present the highest SAP and SAK stocks. Chernozems, Phaeozems and Vertosols possess the highest SAP and SAK stocks in Romania, representing the largest country's pool. Both SAP stocks and SAK stocks are significantly correlated with basic environmental properties, existing direct correlations between SAP, SAK, soil organic carbon (SOC) and total nitrogen (TN) stocks. For all land uses, SAP and SAK stocks correlated significantly and directly with each other, as well as with annual temperature, clay content, pH and sum of base cations, and inversely with altitude, slope and annual precipitation. The best predictive values using multiple regression models and basic environmental driving factors were found for forestland stocks of SAP and SAK, followed by grassland stocks, while the lowest prediction occurred for cropland stocks, probably due to the long-term additional nutrient input performed by farmers in cropland that changed the natural conditions otherwise present in grassland, and especially in forestland. Based on these results some management measures are discussed.

Information related to the climate, sowing time, harvest, and crop development is essential for defining appropriate strategies for agricultural activities, which helps both producers and responsible bodies. Paraná, the second largest soybean producer in Brazil, has high climatic variability, which greatly influences planting, harvesting, and crop productivity periods. Therefore, the objective of this study was to regionalize the state of Paraná, considering decennial metrics associated with climate variables and the enhanced vegetation index (EVI) during the soybean cycle. Individual and global analyses of these metrics were conducted performed using multivariate techniques. These analyses were carried out in agricultural scenarios with low, medium, and high precipitation, corresponding to harvest years 2011/2012, 2013/2014, and 2015/2016, respectively. The results obtained from the scores of the retained factors and the cluster analysis were the profile of the groups, with Group 1 presenting more favourable climatic and agronomic conditions for the development of soybean crops for the three harvest years. The opposite occurred for Groups 2 (2011/2012 and 2013/2014) and Group 3 (2015/2016). During the soybean reproductive phases (R2 – R5), precipitation values were inadequate, especially for Group 2 (2011/2012 and 2013/2014) with high water deficit, resulting in a drop in soybean productivity. The climatic and agronomic regionalization of Paraná made it possible to identify the regions most suitable for growing soybeans, the effect of climatic conditions on phenological stages, and the variability of soybean productivity in the three harvest years.

Climate change is a global challenge to ecosystem services, altering crop yields and food security worldwide. In the context of climate change, Onobrychis viciifolia Scop. (sainfoin) can offer a multitude of ecosystem services conferred by its multifaceted beneficial properties. We reviewed the morphological, biochemical and physiological responses to environmental stressors of O. viciifolia, summarized its ecological, agronomic, nutritional and biological interests, and we discussed its use under climate change. Onobrychis viciifolia is a hemicryptophyte forage legume adapted to arid and semiarid regions by evolving a diverse array of protective mechanisms against abiotic stressors at morphological, biochemical and physiological levels. In the present scenario of climate change, O. viciifolia has desirable forage characteristics such as high nutritive value, high voluntary intake and palatability to grazing animals, leading to satisfying animal performance for milk, meat, honey and wool production. Recent studies suggest that O. viciifolia has several highly beneficial phytochemical properties including condensed tannins and polyphenol content, which have been demonstrated to have anthelmintic activities, enhance protein utilization, and prevent bloating. In addition, O. viciifolia also has the potential to reduce greenhouse gas emissions and sequestrate atmospheric carbon and nitrogen into the soil. Ethnobotanical investigations show that O. viciifolia possesses antimicrobial, antiseptic and vulnerary activities. This review could be helpful for understanding of O. viciifolia characteristics, interests and uses, thus promoting its reasonable cultivation under a changing climate.

The objective was to develop equations to predict carcass weight (CW), use CW to predict empty body weight (EBW); and carcass gain (CG) to predict empty body weight gain (EBWG) and retained energy (RE) in hair sheep. To generate the prediction models, a data set was composed of individual measurements from 569 sheep encompassing intact males (n = 416), castrated males (n = 51), and females (n = 102). Validation analyses were performed by using the Model Evaluation System (MES). The prediction equations for CW, EBW, and EBWG were not influenced by sex class (P > 0.05), and the following equations were generated, respectively: CW (kg) = − 0.234 (±1.1358) + 0.485 (±0.0387) × FBW; EBW (kg) = 1.367 (±0.5472) + 1.681 (±0.0210) × CW and EBWG (kg) = 0.004 (±0.0026) + 1.679 (±0.0758) × CG. There was an effect of sex class on the intercept (P = 0.0013) of the relationship between RE and CG: RE (MJ/day) = 1.448 (±0.0657) × EBW0.75 × CG0.797 (±0.0399); RE (MJ/day) = 1.522 (±0.0699) × EBW0.75 × CG0.797 (±0.0399) and RE (MJ/day) = 1.827 (±0.0739) × EBW0.75 × CG0.797 (±0.0399) for intact males, castrated males and females, respectively. This study highlights the importance of incorporating carcass information into EBW, EBWG, and RE predictions. Replacing empty body weight gain with carcass gain might be a suitable alternative to estimate the retained energy of hair sheep. In addition, the generated equations will provide support for meat production systems in carcass weight prediction.

The interest in the search for alternatives to antibiotics in poultry production has been increasing, especially with the focus on essential oils due to their remarkable bioactive properties. This study aimed to investigate the effects of dietary supplementation of essential oils on the performance and gut morphometry of broilers, by using an approach of systematic review and meta-analysis. In the conduction of the systematic review, three electronic databases (PubMed, Science Direct and Scielo) were consulted in January 2023. Out of an initial amount of 162 papers, only 27 met the requisites to be included in the database. Furthermore, after the use of established criteria for the meta-analysis, only 16 papers were qualified for the evaluation of the aimed parameters. In the meta-analysis, it was observed that the supplementation had significant impact (P < 0.05) of 2.88% in weight gain, in comparison to the basal diet. In addition, the supplementation of essential oils significantly improved (P < 0.05) gut morphometry parameters such as villus height in the ileum (15.66% higher), and 8.26% increase in the villus height to crypt depth ratio in jejunum compared to the basal diet. Dietary essential oils improve the growth performance and gut histomorphometry of broilers, even when combined with antibiotics as growth promoters.

Silvopastoral systems (SPSs) constitute a modality of agroforestry systems in which trees or shrubs, pastures and animals mutually grow, interacting with the environment, and providing several ecosystem services. This review aims to comprehensively discuss the ecosystem services provided by SPSs in different countries, highlighting the diverse ways these systems can contribute to human well-being and environmental sustainability, also emphasizing the importance of management strategies, the differences among systems and the main shortcomings and challenges to optimizing ecosystem service delivery from SPSs. The review focused on global studies, mainly those published between 2010 and 2024, directly relevant to the topic. We used Google Scholar, Scopus and Web of Science databases for literature screening. SPSs have demonstrated worldwide potential to enhance human food and forage production, nutrient cycling, soil fertility, biological nitrogen fixation, carbon sequestration, greenhouse gas mitigation, erosion control, microclimate regulation, pollination, control of pests and diseases, biodiversity, residue absorption, water quality, spiritual enrichment, recreation and aesthetic experiences. However, most ecosystem services provided by SPSs depend on climate conditions, soil type, choice of species, system design and management practices to ensure that such benefits are not provided at the cost of other important services. Interaction among components is a major challenge for system management and evaluations. Adopting SPSs has the potential to promote sustainable agriculture. Long-term studies are needed to elucidate the implications of multiple interactions within the system and their impact on ecosystem service delivery. Public policies, including evaluating ecosystem services, should be developed to promote the adoption of SPSs.

Accurately converting satellite instantaneous evapotranspiration (λETi) over time to daily evapotranspiration (λETd) is crucial for estimating regional evapotranspiration from remote sensing satellites, which plays an important role in effective water resource management. In this study, four upscaling methods based on the principle of energy balance, including the evaporative fraction method (Eva-f method), revised evaporative fraction method (R-Eva-f method), crop coefficient method (Kc-ET0 method) and direct canopy resistance method (Direct-rc method), were validated based on the measured data of the Bowen ratio energy balance system (BREB) in maize fields in northwestern (NW) and northeastern (NE) China (semi-arid and semi-humid continental climate regions) from 2021 to 2023. Results indicated that Eva-f and R-Eva-f methods were superior to Kc-ET0 and Direct-rc methods in both climatic regions and performed better between 10:00 and 11:00, with mean absolute errors (MAE) and coefficient of efficiency (ɛ) reaching <10 W/m2 and > 0.91, respectively. Comprehensive evaluation of the optimal upscaling time using global performance indicators (GPI) showed that the Eva-f method had the highest GPI of 0.59 at 12:00 for the NW, while the R-Eva-f method had the highest GPI of 1.18 at 11:00 for the NE. As a result, the Eva-f approach is recommended as the best way for upscaling evapotranspiration in NW, with 12:00 being the ideal upscaling time. The R-Eva-f method is the optimum upscaling method for the Northeast area, with an ideal upscaling time of 11:00. The comprehensive results of this study could be useful for converting λETi to λETd.

Temperature increase may cause some regions in the world to become marginal or unsuitable for Arabica coffee cultivation, due to either heat and/or marked water deficit. The feasibility of sustainable coffee production in these regions promotes good opportunity of income and value addition for rural producers within an expanding market. This study aimed to identify short-stature Arabica coffee cultivars with the best agronomic and qualitative performance in a low-altitude region. The experiment was located in northeastern São Paulo state, Brazil, at 565 m above sea level. During the experimental period (2014–2018) the average annual and November temperatures were 23.0 and 24.3°C, respectively, with an average annual water deficit of 109 mm. The experimental design was randomized blocks, with four replicates, and the treatments consisted of 17 short-stature cultivars. The cultivars Catuaí Amarelo IAC 62, Catuaí Vermelho IAC 99, IAC Ouro Amarelo, Obatã IAC 1669-20, Obatã IAC 4739, Tupi IAC 1699-33, IAC 125 RN and IPR 100 stood out in terms of yield, reaching approximately 50 bags/ha. The appropriate choice of Arabica coffee cultivar in a low-altitude region may result in yield increment of up to 74%. The cultivars Catuaí Vermelho IAC 99, Tupi IAC 1699-33 and IAC 125 RN produced grains with the best quality and highest hundred-grain weight, processing yield and percentage of grains retained on sieve 17. Therefore, it is possible for an Arabica coffee cultivar to have high yield and high grain and beverage quality in a low-altitude region, promoting production alternatives for farmers.