Tibetan pigs are known for their excellent fat deposition capacity and greater backfat thickness. In this study, scRNA-seq was performed to reveal the cellular heterogeneity of stromal vascular fraction (SVF) cells within porcine neck adipose tissues. Diverse cell types in neck adipose tissue were identified, including mesenchymal stem cells, preadipocytes, mature adipocytes, macrophages, endothelial cells and vascular smooth muscle cells. Tibetan pigs had a higher proportion of mature adipocytes and a greater tendency for preadipocytes to differentiate into mature adipocytes by pseudo-time analysis. Gene ontology analysis highlighted augment pathways related to fatty acid transport and thermogenesis in Tibetan pigs. In vitro experiments further confirmed the superior fat accumulation and fatty acid transport capacities of Tibetan pig SVF cells during adipocyte differentiation, supporting their enhanced fat deposition. Despite their superior adipogenesis, Tibetan pigs had less metabolic activity and oxygen consumption at both the SVF cells and mature adipocyte stages, indicating an adaptation to hypoxic environments at high elevations. This study provides valuable insights into the mechanisms of fat deposition in pigs and highlights the critical role of Tibetan pig adipose cells in hypoxia adaptation, offering guidance for improving fat content and stress resistance in pig breeding programs.
Plastic film mulching (PFM) significantly enhances crop yield and quality by increasing soil temperature, reducing water evaporation and optimizing nutrient cycling. However, improper management of plastic film residues has led to microplastic pollution in farmland, posing a major challenge to sustainable agricultural development. The accumulation of microplastics in soil not only affects soil structure but also profoundly impacts crop growth and ecosystem stability by altering nitrogen-related microbial activities and nitrogen (N) cycling processes. This review synthesizes the effects of PFM and microplastics on soil N pools and cycling, exploring their mechanisms in plant N uptake, microbial immobilization, gaseous emissions (e.g., NH3 and N2O), and N transformation processes (e.g., N fixation, assimilation, mineralization, nitrification and denitrification). Research indicates that PFM and microplastics significantly influence N processes by modifying soil physicochemical properties and microbial community structure, although their effects vary depending on plastic type, environmental conditions and crop growth stages. Future studies should further investigate the long-term ecological impacts of microplastics in complex natural environments and employ advanced statistical methods and models to quantify their dynamic effects on N cycling.
Greenhouse gas (GHG) emissions and their mitigation in food crop production, particularly in tropical regions such as Thailand, remain a knowledge gap in advancing sustainable agricultural systems. This study used a 47-year field experiment to assess the effects of diverse fertilizer application practices on GHG emissions, soil properties and cassava yield. The results revealed that carbon inputs from crop residues (CR) and compost (CP) significantly elevated carbon dioxide emissions, primarily due to enhanced soil microbial respiration. Nitrogen applications, whether from mineral or organic sources, significantly stimulated nitrous oxide (N2O) emissions, with greater N inputs leading to higher N2O releases. At equivalent N application rates, mineral N fertilizers induced greater N2O emissions, having a mean emission factor (EF) of 0.75% compared to CR-derived N with an EF of 0.56%. Additionally, mineral fertilizers led to soil acidification and nutrient accumulation. CR and CP inputs increased soil organic carbon stocks by 42.1% and 53.3%, respectively, relative to the control. CP addition also improved soil pH and significantly enhanced phosphorus and potassium availability. Notably, the combined inputs of NPK fertilizers and CR achieved the lowest GHG emissions per unit yield, highlighting the potential of integrated fertilizer application strategies to mitigate GHG emissions while sustaining crop productivity.
The integration of hyperspectral imaging and deep learning for foreign fiber detection has primarily focused on plastic film. However, detecting various foreign fibers in long-staple cotton, particularly those that are white, transparent or similar in color, remains a significant challenge. The spectral response differences of various foreign fibers across different wavelengths are significant, which makes hyperspectral multi-target detection more complex. To address this challenge, a hyperspectral identification algorithm is proposed. First, hyperspectral image of the experimental samples are captured, and principal component analysis (PCA) is applied to select the optimal feature bands for recognition by a convolutional neural network. Next, the AlexNet model is fine-tuned to optimal parameters using the primary feature bands. After multidimensional experimental validation, the PCA-AlexNet model efficiently identifies foreign fibers. Finally, after analyzing the experimental results from multiple perspectives, the fiber identification model is identified as PCA-AlexNet-23. The results show that the PCA-AlexNet-23 model excels in identifying multiple fibers, achieving an overall accuracy of 97.2%, an average accuracy of 95.2%, and a Kappa coefficient of 93.1%. These accuracy rates outperform those of a support vector machine, artificial neural network, LDA-VGGNet and LDA-LeNet models. In the experimental tests, the overall foreign fiber removal rate exceeds 85%.
Early detection of subclinical mastitis (SM) in dairy cows is important to minimize economic losses and improve dairy cow comfort. This study focused on the identification of threshold temperature of California mastitis test for being positive for SM and determined if it was affected by temperature-humidity index (THI). Six hundred and fifty-eight small and medium scale dairy farms were selected in four regions of Sri Lanka (UP, Up Country; MC, Mid Country; CT, Coconut Triangle; and WP, Western Province) and 4274 udder quarters were captured using thermal camera. SM positive udder quarters had a higher temperature (as mean ± standard deviation; UP, 36.4 ± 1.79 °C; MC, 36.3 ± 1.79 °C; WP, 37.7 ± 1.84 °C; and CT, 38.3 ± 1.01 °C) compared to SM negative samples. The prevalence of SM was statistically significant for udder skin surface temperature (P < 0.05) and the difference between it and flank skin temperature was statistically significant with prevalence of SM (P < 0.05). The threshold temperature differences were (in ΔT °C): UP 2.49; MC, 2.17; WP, 1.90; and CT, 1.86, and these were statistically different (B = −0.080, R = 0.957, R2 = 0.916, P < 0.05) from environmental temperature and tended to be significantly related to the THI. Thus, the threshold value of temperature difference can be applied for early detection of SM taking into consideration that threshold temperature varies with the environmental temperature and THI.
China’s high rice yield is primarily achieved through intensive fertilizer application and substantial water resource consumption, which has resulted in significant environmental risks. There is an urgent need to develop innovative green technologies that simultaneously ensure high yield and production efficiency to achievesustainable rice production. This paper systematically analyzes both nationwide challenges and region-specific constraints affecting rice production. The proposed solutions focus on three key innovations: constructing high-yield populations, coupling aboveground and belowground, and improving soil fertility. Implementation of these green high-yield and high-efficiency technologies demonstrates potential to maintain or increase yields while achieving three critical improvements: enhanced nitrogen use efficiency, reduced irrigation water consumption and decreased greenhouse gas emissions. To facilitate large-scale adoption, priority should be given to developing rice-related products, integrating rice-upland rotating system and establishing localized implementation models based on these technological innovations.
Stabilized fertilizers, enhanced with urease or nitrification inhibitors, have emerged as pivotal tools for China’s agricultural green transition, balancing crop productivity, resource efficiency, and environmental sustainability. Globally, Germany and other EU countries have pioneered inhibitor-integrated fertilizer policies, driving emission reductions. Despite China’s later start, breakthroughs in local production, diversified formulations (covering six major fertilizer categories) and standardized systems have positioned it as a global leader, with 90% of the raw material capacity and 3 Mt annual output (4% of the total fertilizer production). Meta-analysis of over 900 trials (2014–2018) demonstrates stabilized fertilizers increase yields by 9.2%, nitrogen use efficiency by 11.2% and lower N2O emissions by 28.4% in staple crops. Field studies further reveal multifunctional benefits including 60% higher nitrogen efficiency, 60% emission cuts, 20%–50% fertilizer savings and enhanced climate resilience. To maximize impact, advancing technology innovation, refining application protocols and fostering cross-sector collaboration are critical. This paper provides strategic insights to accelerate China’s sustainable agriculture transition and global climate goals.
Due to its high-temperature and high-pressure operating environment, food/feed puffing machines are prone to faults such as cavity blockage and cutter wear. This paper presents the design of a fault diagnosis system for puffing machines (food/feed processing equipment that expands or puffs agricultural products), based on a convolutional neural network and a multi-head attention mechanism model, which incorporates Bayesian optimization. The system combines multi-source information fusion, capturing patterns and characteristics associated with fault states by monitoring various sources of information, such as temperature, noise signals, main motor current and vibration signals from key components. Hyperparameters are optimized through Bayesian optimization to obtain the optimal parameter model. The integration of convolutional neural networks and multi-head attention mechanisms enables the simultaneous capture of both local and global information, thereby enhancing data comprehension. Experimental results demonstrate that the system successfully diagnoses puffing machine faults, achieving an average recognition accuracy of 98.8% across various operating conditions, highlighting its high accuracy, generalization ability and robustness.
The implementation of green technologies has facilitated the sustainable development of China’s agriculture. However, the impact of green technologies in China’s major crops production, their mechanisms of action and their future potential have not been systematically investigated. This study used national statistics data to summarize the impact of technological innovation on production and efficiency of major grain crops in China, and to identify which technologies have made the most important contributions. National statistics data showed changes in grain production (58% increase), total planting area (8.6% increase) and structure, nutrient input (0.83 Mt decrease) and reactive nitrogen losses, and optimized planting and fertilizer structure in 2022 compared to 2000. Of these, the proposal of integrated soil-crop system management significantly decreased reactive nitrogen losses and greenhouse gas emissions by 30% and 11%, respectively. Root zone nutrient regulation techniques, such as in-season nitrogen management, increased yields by 8% and decreased nitrogen rate by 25%. Rhizosphere nutrient regulation technology increased yield by 20.2% and decreased nitrogen rate by 20%–30%. According to predictions, integrated soil-crop system management will demonstrate significant advantages in both unit area yield and total yield by the year 2050. The adoption of integrated soil-crop system management is expected to increase the total production of rice, wheat and maize by 45.8, 115 and 360 Mt, respectively. Currently, China’s agriculture is confronted by significant challenges, including rising food demand, excessive inorganic nutrient inputs, and low utilization rates of organic resources. Three key recommendations arise from this study: the implementation of precise management for organic manure; the promotion of enhanced-efficiency fertilizers; and the adoption of new technologies including integrated soil-crop system management combined with rhizosphere nutrient regulation and intelligent nutrient management. These measures will drive the development of green, high-yield and efficient agriculture.
Agriculture is undergoing a pivotal transformation, shifting from a singular focus on food security to interdisciplinary research that encompasses food security, environmental protection and sustainable use of resources. The growing global population and climate change exert the urgency to adopt sustainable practices that balance crop productivity and environmental stewardship. The merit of the approach of past agricultural research, typically centered on single processes and limited to specific disciplines and goals, is now a subject to debate. There is need for a multi-objective approach, an enhancement of the whole industry chain enhancement (involves service from the initial raw material stage to the final consumer) and a holistic approach for sustainable agricultural development. To address these challenges, this article presents an innovative agricultural system research approach. This approach integrates interdisciplinary research and advocates for a combined top-down and bottom-up strategy. The concept of innovative agriculture refers to redesigning systems through technological integration for large-scale application, ultimately aiming to enhance overall crop production, environmental sustainability and efficiency. The top-down approach sets yield targets and environmental thresholds at various scales, aligning with national objectives for food security, resource use efficiency and ecological sustainability. This method determines the necessary technical systems and integration methods. In contrast, the bottom-up approach based on Science and Technology Backyard, analyzes the factors that constrain high crop yields and efficiency, and develops systematic methods to achieve high yield and high efficiency. The integrated agricultural research approach can simultaneously address food security challenges, enhances resource use efficiency, and protect the environmental sustainability. This is essential for advancing sustainable agricultural practices in the face of increasing global demands and environmental concerns.
