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The labile fractions of organic carbon (OC), which are a reflection of the properties of soil and its use, appear to be suitable parameters for their use as indicators. The aim of this study was to determine the reliable and relatively simple indicators for detecting the chemical and physical stabilizations of OC, which would respond sensitively to land use. The study includes forest ecosystem (FE) and agroecosystem (AE) with different tillage intensities (reduced tillage, RT and conventional tillage, CT) on real farms. Parameters of the labile C and N were tested. For a depth of < 0.1 m in the FE, the hot water extractable organic carbon (HWEOC) for chemical stabilization and labile nitrogen (N_L) for physical stabilization appear as the most suitable indicators. Higher values of HWEOC indicate the OC stabilization by decreasing decomposition, pH or by increasing carbonates, recalcitrant fractions, and higher values of N_L by OC incorporation into the silt fraction and larger macro-aggregates. In the AE with RT, these are the HWEOC for chemical stabilization and carbon pool index (CPI) or index of carbon lability (LI_C) for physical stabilization. Higher values of CPI and LI_C indicate the stabilization by the formation of size-optimal dry-sieved (DSA; 1–3 mm) and wet-sieved (WSA; 1–2 mm) soil aggregates. In the AE with CT, it was the N_L. Its higher values point to the stabilization through the carbonates, alkaline cations, size-fraction of > 0.01 mm and the formation of DSA (1–3 mm). For a depth of < 0.3 m in the AE, these are the C_L (for RT), higher value of which points to the stabilization by clay and alkaline cations, and HWEOC (for CT), higher value of which indicates the stabilization in the conditions of the soil acidification.

Indonesia, as a leading coconut producer, generates a substantial amount of coconut pulp from coconut milk extraction, which can be further processed into low-fat desiccated coconut. However, the drying process induces browning, reducing its whiteness and overall quality. Sodium metabisulphite is commonly used to prevent browning, but excessive use raises health concerns. In this study, the optimisation of the drying temperature and sodium metabisulphite concentration was conducted to minimise the browning while maintaining the quality of low-fat desiccated coconut. Using Response Surface Methodology (RSM) with a Central Composite Design (CCD), responses such as the browning index (BI), whiteness index (WI), moisture content, yield, free fatty acids (FFAs), ash, fat, protein, total phenolic content (TPC), and crude fibre were examined. The results showed that both the drying temperature and sodium metabisulphite concentration significantly influenced the physicochemical properties. The optimal conditions were identified at 62.505 °C and 380.059 ppm sodium metabisulphite, resulting in a whiteness index of 87.219, browning index of 5.1025, yield of 43.125%, moisture content of 2.3%, and free fatty acid content of 4.45%. These findings highlight an effective strategy for reducing the additive dependency while maintaining the physicochemical quality of low-fat desiccated coconut.

This paper presents the architecture of a cyber-physical system for the automated washing of agricultural machinery, designed to enhance efficiency and intelligent control. The system includes four layers – physical, sensor, computational, and interface and integrates actuators, sensors, decision-making modules, and analytics. A Python-based simulation using Control and SimPy showed an average washing time of 10.4 minutes and 97.5% cycle initiation accuracy under critical contamination. The Control was achieved via gated recurrent unit (GRU) prediction and proportional–integral–derivative (PID) regulation. Despite assumptions like ideal sensors and fixed conditions, the system proved feasible, with the future work targeting real-world validation and digital twin development.

Recent advancements in remote sensing techniques, especially the combination of hyperspectral imaging with analytical algorithms, have greatly improved precision agriculture. This study introduces some algorithms developed for identifying crops and evaluating their growth conditions, focusing on irrigation and fertilisation. The present approach is based on the concept of identifiability of a family of dynamic systems and the differentiation of plants using their spectral signatures. The method uses a repository of spectral data and applies a developed algorithm to compare the measured spectra with the reference database, enabling the identifiability and the recognition of both known and unknown crops. As an application of our approach, we have considered two different crops: mint and rosemary, under different irrigation and fertilisation conditions. The results show that the algorithm achieved a 100% identification rate across the four unknown samples. The minimum spectral distances obtained are 0.01 and 0.03 for rosemary and mint, respectively. Thus, the family of systems was identifiable with a tolerance of η < 0.03. The study concluded that the algorithm effectively classifies the crop type and deduces its growth conditions, demonstrating its effectiveness for agricultural monitoring.

In an era marked by an ageing agricultural workforce and intensifying environmental pressures, agricultural infrastructure plays a crucial role in enhancing green productivity. This study investigates the impact of agricultural infrastructure construction and population ageing on agricultural green total factor productivity (agricultural GTFP), utilising provincial panel data from 2004 to 2022 in China. Our findings reveal that the agricultural infrastructure construction significantly boosts agricultural GTFP and significantly mitigates the negative effects of ageing on agricultural green production at the 0.01 level. Notably, different types of infrastructure exhibit varying impacts, with electricity and irrigation infrastructure demonstrating the most significant positive effects. We further identify a strong mediating effect of farmland transfer and agricultural mechanisation in facilitating infrastructure-driven agricultural GTFP growth. Our analysis reveals a pronounced regional heterogeneity, with non-food producing, central, western regions of China benefiting most from agricultural infrastructure investments. To address the challenges posed by ageing, we recommend giving priority to expanding agricultural infrastructure construction, fostering agricultural socialised services, and tailoring infrastructure programs to regional resource endowments. These strategies aim to compensate for labour shortages, enhance resource utilisation, and ultimately drive improvements in agricultural green productivity.

The capacity for flexibility, personal development, and intrinsic motivation is a crucial aspect needed by employees in the process of transforming agricultural organisations. This paper aims to determine the typically oriented groups of employees in terms of their motivation and verify whether the identified groups are invariant even under changing conditions over time. The data from 2019–2023 (from 374 respondents employed in agricultural enterprises in south-central Slovakia) were evaluated using descriptive and inferential (K-means cluster) statistics. According to preferences and constancy of attitudes, three clusters of employees called ‘Materialists’, ‘Team progressives’, and ‘Preferences settled’ were determined. The clusters were also solved in terms of stability over time. Despite the differences in the preferences of these clusters, relational factors indeed played one of the most critical roles, even in the case of materialistically oriented employees. The practical result of the research is the possibility of designing a differentiated motivation program specifically targeted to individual groups of employees with similar motivational preferences based on a competent statistical analysis of motivation. The results are used by agricultural businesses to design motivation programs for similarly motivationally oriented employees sophisticatedly.

As the strategy for building a robust agricultural nation gains momentum and agricultural science and technology advances, the quality of agricultural products has seen significant improvement, accompanied by an increase in the economic income of agricultural producers and operators. Therefore, the fair and reasonable implementation of the revenue distribution of the agricultural supply chain is of great significance in improving the quality of agricultural products and ensuring the stable operation of the supply chain. The article focuses on the three main bodies of the agricultural supply chain, namely production and price co-integration enterprises, logistics service enterprises and sales enterprises, and utilises the matrix semi-tensor product to establish the Shapley value revenue allocation model of the interval cooperation game, so as to make the revenue allocation of the governance of agricultural products' quality in the digital supply chain more reasonable and scientific. Finally, numerical examples verify the Shapley value model, demonstrating that this revenue allocation scheme, when applied, can boost the overall supply chain's revenue through cooperative agricultural product quality management, elevate agricultural product quality and market competitiveness, and foster collaboration to ensure the stability of supply chain operations.

Climatic microrefugia allow some forest tree species to persist outside their main distribution range by locally decoupling site conditions from the regional climate. At its western, oceanic range margin in the Swiss Prealps, the Swiss stone pine (Pinus cembra L.) occurs on large boulders embedded within subalpine forests dominated by Norway spruce [Picea abies (L.) H. Karst.]. We hypothesised that these landforms generate a continental-like microclimate enabling P. cembra persistence under otherwise sub-oceanic conditions, and we aimed to quantify this phenomenon. Using high-resolution data loggers, we measured air and soil temperature, thermal amplitudes, and soil moisture on the summits and at the bases of ten limestone boulders over a two-year period. Linear mixed-effects models revealed a pronounced microclimatic decoupling between positions. Boulder summits were consistently warmer and drier during the growing season. In contrast, during winter, summits were significantly colder, while boulder bases remained thermally stable due to persistent snow insulation. The strongest microclimatic divergence occurred in spring, when temperatures at the bases remained stable near 0 °C, whereas summit temperatures were markedly warmer and more variable. This continental-like microclimate likely promotes P. cembra persistence. Our results highlight the importance of topographic heterogeneity for maintaining marginal tree populations.

This study aimed to evaluate ozone (O₃) phytotoxic potential using AOT40F (accumulated O₃ concentration over a threshold of 40 ppb for forest protection), document visible foliar O₃ injury across eight forest monitoring plots, analyse MDA (malondialdehyde) content in leaves and needles, and assess the relationship between visible injury and plot conditions. Initial findings are based on data from the 2021 and 2022 vegetation seasons. AOT40F values exceeded the critical level of 5 ppm·h^–1 at all plots, with higher values in 2022. The correlation between AOT40F and visible injury was inconsistent; in 2021, minimal visible O₃ injuries were observed, while these were more frequent in 2022, notably on Fagus sylvatica leaves. The altitude effect on O₃ concentration indicates greater vegetation damage at higher altitudes. In contrast, the AOT40F-altitude relation was not significant. The 2021 vegetation season was characterised by lower temperatures and higher relative air humidity and soil moisture in comparison to 2022. Stomatal conductance conditions were similar in both years, except for lower soil moisture in 2022. Soil moisture, air humidity, and temperature together accounted for about 50% of the variance in visible injury in 2022. The findings suggest that the AOT40F capability for predicting damage to vegetation is limited and highlight the importance of future research focusing on stomatal O₃ flux-based approaches.

In 2007, the Chinese government introduced a temporary corn storage policy targeting four regions: Heilongjiang, Jilin, Liaoning and Inner Mongolia. This policy aimed at stabilising grain markets and ensured farmers' income by providing price support for corn. Its implementation significantly impacted corn prices and the regional distribution of corn cultivation, offering a valuable case for analysing the economic outcomes of China's agricultural policies. This study adopts the adaptive expectations hypothesis to explore the policy's effects, focusing on its influence on farmers' price expectations (mean) and price volatility (variance). Using a Spatial Durbin Model (SDM), we empirically investigate the policy's dynamic regional impacts on corn planting areas. The results show that the temporary corn storage policy significantly increased corn planting areas in the targeted regions, while simultaneously reducing planting areas in non-targeted regions due to negative spatial spillover effects. At the national level, the policy had no statistically significant impact on total corn planting areas, indicating that abolishing the policy alone is unlikely to rationalise or optimise the agricultural planting structure.

The availability of new sensor technologies, such as thermal and hyperspectral imaging, enables early-stage weed detection and species identification and density estimation, both of which are crucial for effective weed management. Thermal imaging successfully distinguished between dicotyledonous (oilseed rape, pea, Stellaria media, Triplerospermum inodorum, Veronica persica) and monocotyledonous species (barley, wheat, sorghum and Echinochloa crus-galli) except Amaranthus retroflexus, during early growth stages. The most pronounced differences in hyperspectral reflectance occurred at 550 nm, where five distinct plant groups were recognisable (sum of squares = 0.7604, F-value = 105.1). The highest hyperspectral reflectance was recorded for oilseed rape, followed by Stellaria media. The same trend was found for the normalised difference index (NDI), which also showed five distinct groups. These findings indicate that thermography and hyperspectral imaging have strong potential as effective tools for supporting weed detection in precision agriculture; however, further research and field validation are required before routine implementation in agricultural practice.

Reliable indicators of early soil biological change remain limited in tropical agroecosystems, where soil organic carbon (SOC) stocks may respond more slowly than microbial processes. We evaluated whether seasonal vegetation dynamics derived from Sentinel-2 fractional vegetation cover (FVC) are associated with spatial variation in SOC stock and microbial indicators in Jembrana, Bali, Indonesia. We mapped seasonal FVC from 2019 to 2024 and derived site-level metrics of mean cover and temporal variability (standard deviation, anomaly, coefficient of variation, and a temporal stability index). In July 2023, we sampled topsoil (0–30 cm) at 12 sites representing contrasting land uses and topographic settings. We calculated SOC stock from organic carbon concentration, bulk density, and sampling depth, and measured basal respiration and culturable microbial density (colony-forming units, CFU). Vegetation cover peaked consistently during the wet season (December to February), and mean site FVC ranged from 0.31 to 0.99. Mean FVC showed positive but non-significant associations with culturable microbial density (Spearman’s ρ = 0.48, P = 0.114) and basal respiration (ρ = 0.29, P = 0.361), whereas higher vegetation variability metrics tended to coincide with lower culturable microbial density (ρ = –0.43 to –0.51, P = 0.090 to 0.163). SOC stock showed near-zero coefficients and no statistical evidence of association with vegetation metrics (ρ = 0.09, P = 0.781) or microbial indicators (ρ = 0.01, P = 0.975). Principal component analysis of FVC traits explained 99.65% of the variance and separated sites along a gradient from stable, high cover to more variable, lower cover. Overall, FVC stability metrics captured spatial differences that were directionally consistent with microbial indicators, but associations were not statistically significant in this dataset (n = 12). Larger, replicated studies with repeated soil sampling are required to evaluate whether seasonal FVC metrics have robust predictive utility for SOC stock and soil biological indicators.

Measures for consumer protection against food adulteration and misleading labelling are integrated into EU legislation, including methods for detecting misleading practices. Verification of the meat content is available for marine products, but not for salmonid fish due to the lack of standard nitrogen factors. This study aimed to establish nitrogen factors for rainbow trout (Oncorhynchus mykiss) and brook trout (Salvelinus fontinalis). The study analysed 340 fish from Czech fisheries obtained in the summer of 2018-2020. According to the established ISO methods, fillet samples with and without skin were analysed for their nitrogen content (protein), dry matter, ash, and fat. The recommended nitrogen factor for rainbow trout fillets with and without the skin is 3.07 ± 0.12 and 3.06 ± 0.14, respectively, and the nitrogen factor for fat-free rainbow trout fillets with and without the skin is 3.33 ± 0.15 and 3.29 ± 0.15, respectively. The recommended nitrogen factor for brook trout fillets with and without the skin is 3.16 ± 0.10 and 3.12 ± 0.09, respectively, and the nitrogen factor for fat-free brook trout fillets with and without the skin is 3.42 ± 0.13 and 3.36 ± 0.12, respectively. The established nitrogen factors will enable the analysis of the meat content to ensure that consumers purchase correctly described and labelled fish products.

Nutrition plays an important role in human life. So far, there have been discussions focusing on the nutritional value of individual foods, separate dishes, or daily meals. However, they have not taken into account the composition of the diet in the longer term. The aim of this work was to evaluate a full-day diet from a currently renowned company that is producing box diets on the Czech market against a full-day diet of twenty randomly selected students. The results showed that the box diet met the required amount of protein, fat, vitamin E, cholesterol, and also the optimal intake of n-6 and n-3 fatty acids. The amount of saturated fatty acids (SFA) was only slightly increased. Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content averaged 38 mg day^-1, which did not meet the current requirements. The students' full-day diet was variable, the individual differences were large. Protein intake could be assessed as sufficient in most cases. The total fat intake ranged from 21 g day^-1 to 126 g day^-1. Seven out of twenty samples would satisfy the recommendation for SFA. The content of the essential acids EPA and DHA was below the detection limit with the exception of one sample (containing herring fillets).

The European Union (EU) provides both financial and expert support for sustainable forest management initiatives and also boosts compliance with such initiatives in Africa. Thus, there is a need to monitor the progress of implementing such initiatives. The objective of this paper is to describe the role of timber harvesting entities in environmental impact discussions, and to also identify the role of EU institutions in promoting forest sustainability in Sierra Leone. Data were collected in a controlled survey from four communities, using a questionnaire formulated according to guidelines recommended by Babbie and Mouton (2010). The reliability test shows a 0.68 internal consistency among the latent variables (Cronbach alpha test). The selected four communities were Bambawo, Dia, Basara, and Menima, with a population of 6 000, 5 400, 7 500, and 5 600 inhabitants, respectively (Stats SL 2021). A Confirmatory Factor Assessment (CFA) was used for a descriptive statistical analysis of the data. The results showed that the environmental impact has an eigenvalue of 1.08, where only variables with a factor loading exceeding 0.5 were used. The paper concludes with discussions and relevant recommendations on mitigating the impacts of timber harvesting on the environment within the study area.

Effective weed management relies on frequent field monitoring, which is difficult to perform in vast areas. Integrating red-green-blue, thermal, hyperspectral, and multispectral sensors with unmanned aircraft systems and artificial intelligence ensures better results in managing the weed menace. Since India depends largely on agriculture, it is still a long way from implementing more advanced weed management methods. Mapping and surveillance of weeds in croplands by employing remote sensing will lead to varied herbicide application rates, thus reducing its overuse. This study reviews the practical application of remote sensing methods and unmanned aircraft systems in weed mapping

Global food security is increasingly threatened by the vulnerability of agricultural systems to climate variability, especially in sub-humid regions. Northeast China, a major maize-producing region, experiences low spring temperatures and erratic rainfall, which have prompted the widespread adoption of plastic-film mulching (PFM) combined with drip irrigation. However, systematic evaluations of how different PFM patterns affect crop productivity and resource use efficiency remain limited. This study systematically evaluated three PFM strategies – full ridge-furrow mulching (FM), ridge mulching (RM), and no mulching (NM) – in combination with 240 kg N/ha and a zero-nitrogen control under drip irrigation to determine their effects on maize (Zea mays L.) yield, water use efficiency (WUE), and nitrogen utilisation. Field experiments over two consecutive growing seasons assessed crop growth, dry matter (DM) accumulation, nitrogen dynamics, grain yield, and related efficiency parameters. Both FM and RM significantly enhanced early maize growth. At the seedling stage, FM and RM increased plant height by 43.0% and 40.1%, and leaf area index (LAI) by 141.4% and 120.4% over NM, respectively. During the same stage, DM accumulation increased by 228.9% (FM) and 224.9% (RM). These improvements reflected favourable soil hydrothermal conditions under PFM. Before heading, PFM treatments increased pre-anthesis DM accumulation by up to 19.6%, and at maturity, FM and RM raised DM by 6.1% and 5.1% over NM. PFM significantly improved grain nitrogen accumulation, with FM and RM increasing it by 31.0% and 26.9% over NM, respectively, and nitrogen harvest index (NHI), with FM and RM increasing it by 6.8% and 6.1% over NM, indicating enhanced nutrient translocation to grain. PFM also improved grain yield, with FM and RM increasing it by 15.0% and 13.5%, WUE by 17.2% and 15.7%, and nitrogen partial productivity by 16.8% and 14.1%. No significant differences in yield or WUE were observed between FM and RM. Fertilisation consistently enhanced these benefits without changing the relative efficiency ranking of treatments. Notably, the advantages of mulching diminished after the heading stage as temperature and rainfall increased. PFM (both FM and RM) under drip irrigation improves maize yield, water use, and nitrogen efficiency in sub-humid regions. This integrated practice offers a scalable and sustainable strategy to increase maize productivity and resource efficiency, supporting food security in regions facing similar climatic challenges.

This study evaluates the efficiency of various facial recognition camera systems used to control access in agri-food production environments, focusing on their ability to identify individuals based on biometric facial traits. It is also important to prevent the movement of unwanted persons into the production premises in the agri-food complex. The main goal was to assess how these factors influence the recognition performance and to determine the most reliable system for preventing unauthorised entry. The results show notable performance disparities between the devices tested. It can be concluded in this research that there are statistically significant differences between the maternal, professional and semi-professional systems. The device that is most suited is the HIKVISION iDS-2CD8426G0/F-I, achieving the best average performance score. This is based on usual recognition times. These tests indicate that the HIKVISION DS-2DE7232IW-AE(S5), which obtained an average rating of 2.216789, is the second-best acceptable device. With a score of 2.842113, HIKVISION DS-2CD2H45FWD-IZS (2.8–12 mm) (B) received, without a doubt, the lowest ranking. Given the outcomes, systems with superior recognition capabilities like the iDS-2CD8426G0/F-I are best to use for critical access control applications and to also minimise the use of facial coverings in sensitive areas to ensure reliable identification and higher levels of security of agri-food complexes.

This study explores the construction of small reservoirs (SRs) as a strategic solution to address water scarcity in Kashkadarya Province, Uzbekistan, where agricultural productivity is heavily dependent on irrigation. By utilising geographic information system (GIS) and remote sensing (RS) technologies, optimal locations for reservoirs were identified, focusing on improving the water availability for irrigation during critical periods. The research highlights the socio-economic and environmental benefits of SRs, including enhanced agricultural yields, increased employment opportunities, and reduced reliance on energy-intensive pumping stations. The findings indicate that the construction of an 18 Mm³ reservoir in the Ayakchisoy River could supply water to 26.5 thousand hectares, thereby improving the region’s resilience to climate variability. This approach offers a sustainable framework for managing water resources in arid regions, contributing to food security and economic stability.

Employing the Comprehensive Demonstration of E-commerce in Rural Areas (CDERA) policy as a quasi-natural experiment, this paper explores the impact of rural e-commerce development on agricultural total factor productivity (ATFP) and its underlying mechanisms, using a difference-in-differences model. The analysis utilises panel data from 1 495 counties in China from 2001 to 2021. The findings indicate that the CDERA policy implementation enhanced ATFP in treated counties by approximately 1.6 percentage points compared to control counties, other factors being equal. Mechanism analysis further reveals that the CDERA policy enhances ATFP by improving agricultural technological efficiency and fostering agricultural industrial development. This study highlights the significant role of CDERA policy in enhancing agricultural productivity in China and offers policy insights for advancing rural e-commerce and promoting sustainable agricultural development.

This experimental study evaluated the therapeutic potential of a liquorice-derived hydroalcoholic extract in managing experimentally induced peritonitis in New Zealand rabbits. The animals were randomly divided into six groups (n = 6): one control group, one negative control group (infected but untreated), three treatment groups that received the liquorice-derived extract at 0.5, 1, and 2 g/kg, and one positive control group treated with enrofloxacin. The confirmation of peritoneal infection relied on histopathological and radiographic tests. The effect of the liquorice extract on the peritoneal infection was evaluated using biochemical, haematological, and ultrasound analyses across the groups. The ultrasound examination, along with the haematological and biochemical evaluation on the 20^th day after induction, showed significant differences between the groups. The results demonstrated that higher doses of 1 g/kg and 2 g/kg were more effective than the lower dose of 0.5 g/kg. The haematological and biochemical analyses revealed significant differences in several variables (including WBC, neutrophils, fibrinogen, and liver enzymes) between the treated and control groups, with the most pronounced improvements observed in the group receiving 2 g/kg of liquorice extract, suggesting a dose-dependent therapeutic effect. The administration of a hydroalcoholic extract of liquorice at different doses, along with the standard treatment with enrofloxacin, affected various haematological and biochemical variables in the context of peritoneal infection management. In conclusion, the effectiveness of the liquorice-derived extract is dose-dependent and could be used as an effective therapeutic agent in peritoneal infections in New Zealand rabbits. These findings showed that the liquorice-derived extract effectively improves the local inflammatory and structural changes associated with peritoneal infection without adversely affecting systemic biochemical homeostasis.

Agribusiness is currently faced with the challenge of providing sufficient quality food for a growing population with limited natural resources. Egg production, as an important source of nutrition, is a dynamically developing sector of livestock production on a global scale. Simultaneously, the increasing public and legal considerations of animal welfare affect egg-producing operations. This paper aims to provide insight into missing evidence in the trade-offs between animal welfare and efficiency in egg-producing farms in the Czech Republic and the European Union. Detailed data were gathered on the extent of the enriched cage and indoor cage-free housing systems (aviaries/barns) among the main 30 Czech table-egg-producers. Original micro data enlarged the information on table-egg producers collected using the Orbis database. For the efficiency analysis at the EU level, data on the housing systems were obtained from Eurostat and combined with aggregated data from the Orbis database. A robust data envelopment analysis was applied which benefits from including animal-welfare variables directly into the efficiency evaluation. The results showed a negative, but statistically insignificant, relationship between the animal welfare and efficiency of the egg producers for the Czech Republic table-egg producers as well as those on the EU-country level.

Growth traits belong to the most important economic traits in livestock. One of the genes involved in vertebrate growth and development is insulin-like growth factor 1 (IGF1). Therefore, in our study we hypothesised that within the sequence of rabbit IGF1 gene it is possible to identify a polymorphism that may influence growth, carcass or meat traits in rabbits. We identified 6 polymorphisms (g.89259430T>C; g.89259338C>G; g.89259328T>C; 89210029A>G; 89210349C>G and g.89194199C>T) within introns of the IGF1 gene. One polymorphism, g.89194199C>T, was analysed using polymerase chain reaction high-resolution melting (PCR-HRM). We performed the association analysis on 370 animals (males to females 1 : 1) of different breeds: New Zealand White × Flemish Giant crossbreds (NZW × FG), Termond White (TW) and Flemish Giant (FG). Results showed that for growth and slaughter traits in TW populations a significant association (P = 0.003) was found for slaughter weight (SW) when CT genotypes showed significantly higher values compared to CC genotypes (2 878.0 g ± 107.0 and 2 678.0 g ± 34.0, respectively). For TW rabbits we found a significant association (P = 0.009) for dissected bone weight in hind leg (HB) when CT genotypes (127.0 g ± 5.8) had significantly higher values compared to CC genotypes (112.0 g ± 2.4). For carcass traits and physical characteristics of meat we found for musculus longissimus lumborum in TW rabbits that the b* parameter value 45 min after slaughter was significantly higher (P = 0.001) for CT genotypes (1.88 ± 0.05) compared to CC genotypes (0.05 ± 0.02). We conclude that the use of identified SNP in breeding may be limited to some breeds.

Forest logging activities negatively affect various soil properties. In this study, we focus on the logging effects on soil water retention and associated pore size distribution. We measured the soil-water characteristic curves (SWCCs) on 21 undisturbed samples from three research plots: a reference area, a clear-cut area and a forest track. A total of 12 SWCC points between saturation and wilting point were determined for each sample with a sand box and pressure plate apparatus. The trimodal behaviour is highlighted by the dependence between soil moisture and suction. Therefore, we proposed a revised model by combining two exponential expressions with the van Genuchten model. The exponential terms describe the influence of macro-and-structural porosities, and the latter is used to calculate textural porosity. This new model with eight independent parameters was suitable to fit trimodal SWCCs in all samples. Results revealed that logging had the most destructive effect on large pores, and the soil on the forest track was the most affected. Both soil-air and available water capacity were reduced and the permanent wilting point increased as a result of damage to the soil structure and pore system. Observed increased organic carbon content in compacted soils can be attributed to slowed decomposition due to reduced air capacity and increased waterlogging susceptibility of damaged soils.

In recent years, China has promoted large-scale hog farming through various approaches. However, this scale-up process may be affected by economic policy uncertainty. This paper empirically examines the impact of policy uncertainty on hog farming scale-up using provincial panel data from 2016–2022 and a fixed-effects model. Our results indicate that economic policy uncertainty significantly inhibits hog farming scale-up, and this effect remains significant even when we increase the criteria for recognising scale-up, alternative estimation methods include two-stage least squares (2SLS), dynamic panel model and panel Poisson model. Mechanism analysis reveals that economic policy uncertainty not only exacerbates the impact of labour and capital factor prices on scale-up hog farming but also exacerbates the volatility of hog prices, which further raises the risks faced by hog farming and inhibits scale-up hog farming. Heterogeneity analysis reveals that the effect of economic policy uncertainty on hog farming scale-up decreases as farm size increases. Higher-level economic policy uncertainty can inhibit scale-up hog farming, while lower-level economic policy uncertainty can instead promote scale-up hog farming. Economic policy uncertainty has a more obvious inhibitory effect on scale-up hog farming in major development areas. These findings have important implications for the promotion of large-scale hog farming and related policy regulation.

Malus domestica is one of the world’s most important deciduous fruit trees. Over a four-year period (2017–2020), temporal variations in flowering were evaluated in ‘Honeycrisp’ apple trees on eight rootstocks (G.30, G.969, G.202, G.41, G.11, M.9T337, M.26 EMLA and V.6) planted in 2014 in Chihuahua, México. Among the variables evaluated were the probability of late-spring frost, winter chill units, growing degree days, flowering period, foliar nutrient concentrations, trunk cross-sectional area, number and weight of fruit per tree, and production efficiency. Significantly different chill unit accumulations occurred over the four years, with values falling between 974 and 1 415, where for the latter value, the start of flower opening was earlier, but there was a higher risk of damage by temperatures ≤ –2 °C. There was no effect of rootstock on the time of onset and end of flowering. The most productive combinations were ‘Honeycrisp’ on G.969, G.11 and V.6 with yield estimates of 35 300, 34 200 and 33 600 kg/ha, respectively. The commercial production of ‘Honeycrisp’ apple trees requires the evaluation of their agronomic performance with different rootstocks. Flowering is particularly important since this phenological stage is so closely linked to productivity and is strongly affected by variations in winter temperatures.

The common vole (Microtus arvalis) is the main pest in agricultural areas of Central Europe. It is particularly important to monitor its numbers during spring, and if high numbers are detected, some form of pest management should be considered. In the Czech Republic, the number of active burrows is monitored using the burrow index, BI, which allows estimation of the total number of rodents, saves time and is easy to use. We aimed to assess the relationship between the burrow index and the relative abundance of the rodent species examined by snap trapping in crop fields. Bayesian MCMC algorithms with a zero-inflation model were used for this analysis. The positive relationship between BI and vole abundance occurred in the total sample of all fields and in alfalfa, winter wheat and barley crop fields. A positive relationship between BI and the abundance of the wood mouse (Apodemus sylvaticus), the second most common pest in the area, was only confirmed in barley, and this relationship was negative in winter rape. The positive influence of the degree of weed cover on BI was confirmed in the total sample and in winter rape and alfalfa, but weed cover has a negative effect on BI in barley and winter wheat. In contrast, weed cover did not affect the relative abundance of both rodent species in any of the sampled crops. The presence of shrubs and forests around the fields reduced BI in the whole sample, especially in alfalfa. The relative abundance of the voles was not affected by the presence of shrubs and forests around the crop. Still, a positive influence was confirmed for the abundances of mice in the whole sample and alfalfa. BI can be a reliable indicator of vole abundance in crops with high densities, but it is not very accurate at low densities and in crop fields rarely used by voles, such as sunflower and maize. 

Farmland transfer is a practical need for China to achieve agricultural mechanisation and modernisation, and also an important way for farmers to optimise their family resource allocation. The existing studies ignore the impact of farmland transfer on the environment, especially carbon emissions. The practical significance of this paper lies in exploring the likely mechanisms driving the effect of the farmland transfer on agricultural carbon emissions from a microeconomic perspective using data from rural households, based on the heterogeneity of land management scale. Results show: (i) Land transfer impacts carbon emissions differently. Land transfer of small-scale farmers increases carbon emissions, while large-scale farmers reduce them. The threshold value of land management scale is 1 ha. (ii) The impact mechanisms are water-saving technology adoption and input of fertilizers and pesticides. Small-scale farmers increase fertiliser and pesticide input after land transfer, increasing carbon emissions. Large-scale farmers mostly reduce irrigation electricity consumption, as well as fertilizer and pesticide input, thus reducing agricultural carbon emissions. In conclusion, it is recommended to guide farmers to expand farmland transfer scale through subsidy policies; guide small-scale farmers' green agricultural production behaviours; and increase the adoption rate of water-saving technologies.

Taking China as an example in this study, we aim to reveal the enabling effects of agricultural science and technology advancement on the progress of rural industrial incorporation at a relatively more refined level. The main innovation in this study lies in the decomposition of agricultural science and technology advancement, followed by an analysis of its effect on rural industrial incorporation along both linear and non-linear dimensions. The study results show that, along the linear dimension, agricultural science and technology advancement, agricultural knowledge advancement and agricultural technology advancement play significant driving roles in the progress of rural industrial incorporation. However, although the estimated coefficient of the integration of agricultural knowledge advancement and technology advancement is positive, it is not statistically significant. Along the non-linear dimension, agricultural science and technology advancement, agricultural knowledge advancement and agricultural technology advancement all exhibit significantly positive effects across different intervals. However, although the integration of agricultural knowledge advancement and technology advancement also shows a positive effect, its significance appears only in the second interval, indicating that the effect of this variable in promoting rural industrial incorporation can be realised only under certain conditions

Applicability of cryopreserved insemination doses is dependent on the quality of the semen after thawing. The aim of the study was to check the options of new markers for the assessment of sperm quality to predict their fertilisation ability. In five bulls of the Pinzgau breed, the sperm fertilising ability was determined using the in vitro fertilisation. Bulls were divided according to the achieved blastocyst rate: bulls with good fertilising ability (NOB – 38.6%, KAZ – 28.9%, GAL – 29.3%) and bulls with low fertilising ability (LOH – 19.4%, NUS – 22.1%). In addition to the sperm motility and morphology, we monitored common physiological sperm characteristics: viability, apoptosis, acrosomal status, capacitation, mitochondrial activity and generation of reactive oxygen species using the flow cytometry procedure. Novel fertility-related biomarkers, such as ubiquitination, overexpression of MKRN1, SPTRX-3 and PAWP proteins or histone modification (H3K4me2), were also analysed by flow cytometry. From all monitored parameters, more proper characteristics of impaired in vitro fertilising ability proved to be high incidence of apoptotic markers (YO-PRO, Caspase 3/7) and higher counts of morphologically abnormal spermatozoa. Although the in vitro fertilisation (IVF) test can be an advantageous method for evaluating the sperm fertilising ability, there are still differences between the in vivo and in vitro fertilisation processes, which must be considered for example, when evaluating the sperm capacitation status.