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Solid-state fermentation of lignocellulosic waste to produce feed protein is a means of realising solid waste. However, low efficiency and susceptibility to microbial contamination remain significant challenges in feed protein production through room-temperature solid-state fermentation. In this study, thermophilic microbiomes were enriched. After adaptive and nitrogen acclimation, microbiomes with the combined functions of 'thermophilic-rapid decomposition-nitrogen conversion' were obtained and used for feed protein production. High-throughput sequencing and Kyoto Encyclopedia of Genes and Genomes metabolic pathway prediction techniques were used to assess the mechanisms underlying microbial involvement in substance conversion. The results showed that the microbiomes decomposed 78.21 %-81.73 % of straw within 7 days. After nitrogen acclimation, the nitrogen utilisation rate and the true protein content of the microbiomes improved by 19.22 %-26.96 % and 56.14 %-71.99 %, respectively. Fed-batch enzymatic saccharification and fermentation reduced the fermentation time by 28.5 %. Domesticated microbiomes increased the abundance of bacteria and fungi in the fermentation system, enhancing carbon metabolism and the urea cycle. This study presents a novel approach for the high-value utilisation of lignocellulose waste., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier Ltd. All rights reserved.)

Wheat straw contains a high amount of lignin, hindering the action of cellulase and hemicellulase enzymes, leading to difficulties in nutrient absorption by animals from straw feed. However, currently, the biological treatment of straw relies primarily on fungal degradation and cannot be directly utilized for the preparation of livestock feed. This study focuses on enzymatic co-fermentation of wheat straw to produce high-protein, low-cellulose biological feed, integrating lignin degradation with feed manufacturing, thereby simplifying the feed production process. After the optimization using Box-Behnken Design for the feed formulation, with a glucose oxidase addition of 2.46%, laccase addition of 3.4%, and malonic acid addition of 0.6%, the wheat straw feed prepared in this experiment exhibited a true protein content of 9.35%. This represented a fourfold increase compared to the non-fermented state, and the lignocellulose degradation rate of wheat straw reached 45.42%. These results not only highlight the substantial enhancement in protein content but also underscore the significant advancement in lignocellulose breakdown. This formulation significantly enhanced the palatability and nutritional value of the straw feed, contributing to the industrial development of straw feed.

Rice straw produces protein feed through microbial fermentation, which has rich nutritional value. In this experiment, rice straw was used as the sole carbon source and bran was added as the nitrogen source. Semi-solid fermentation was carried out by Aspergillus niger and Pichia kluyveri 16 composite strains to explore the optimal fermentation conditions for the production of protein feed by mixed bacteria fermentation. The results showed that in the rice straw and bran medium, rice straw:bran = 3:1, the initial pH of the solid medium moisture was 4.0, the initial moisture content was 60%, the inoculation amount of A. niger was 20%, the fermentation time of A. niger was 60 h, the fermentation speed of P. kluyveri 16 was 150 r/min, the inoculation amount of P. kluyveri 16 was 9%, and the fermentation time of P. kluyveri 16 was 4 d. Under this condition, the crude protein content of fermented feed was 17.5%, which was 2.1 times higher than that before fermentation. The true protein content was 14.5%, which was 1.7 times higher than that before fermentation. The cellulose content decreased, and the amino acid content increased exponentially. In this study, the process of semi-solid fermentation of rice straw protein feed by composite strains was explored, which effectively improved the digestibility of rice straw protein feed and significantly improved the nutritional value of rice straw, which was of great significance for the development of new straw protein feed. [ABSTRACT FROM AUTHOR]

Simple Summary: In recent years, forage resources in many countries have been facing the problems of limited planting area and high cost. Rice and Zizania latifolia are widely cultivated, and they produce large amounts of rice straw or sheath and leaves when harvested. However, most of these are discarded or burned, resulting in a waste of resources and environmental pollution. Effective utilization of these by-products is the key to solving the problem of feed shortage in livestock production. The aim of this study was to investigate the effects of fermented total mixed ration containing rice straw and sheath and leaves of Zizania latifolia on heifer growth from the perspective of metabolism and host genetics. Feeding fermented total mixed ration containing 35% rice straw and 31% sheath and leaves of Zizania latifolia could improve the nutrient intake and antioxidant capacity of heifers. And the key metabolites involved in energy metabolism and oxidative balance can be used as candidate markers for heifers' average daily gain. This integrated omics approach highlights the potential to increase livestock productivity and promote sustainable agricultural practices. With the increasing demand for enhancing livestock production performance and optimizing feed efficiency, this study aimed to investigate the effects of fermented total mixed ration (FTMR) containing different proportions of rice straw and sheath and leaves of Zizania latifolia on systemic nutrient metabolism and oxidative metabolism under host genetic regulation and on growth performance of heifers. A total of 157 heifers aged 7–8 months were selected, and their hair was collected for whole-genome sequencing. They were randomly assigned into four groups of 18 to 21 cattle each and fed FTMR containing varying levels of rice straw (21% in LSF, 28% in MSF, 35% in HSF) or 31% sheath and leaves of Zizania latifolia (ZF) for a two-month period. At the end of trial, blood and urine samples were collected to measure biochemical indexes and metabolomics. The results showed that high rice straw content and ZF diets could increase blood glucose and non-protein nitrogen in heifers, that is, blood glucose and urea nitrogen levels in HSF and ZF groups were higher than those in LSF and MSF groups (p < 0.05). Meanwhile, the two diets could improve the antioxidant level of heifers. Urine metabolomics analysis between the groups identified three differential metabolic pathways, including 11 metabolites. Among them, l-homoserine and o-acetylserine had significant SNPs associated with them, which promoted glutathione metabolism. Although there was no significant effect of diet on heifers' average daily gain (ADG) in body weight (p > 0.05), there was substantial inter-individual variation in metabolites among all animals, as further correlation analyses illustrated. Twenty-eight metabolites were significantly associated with ADG (R > 0.3, p < 0.05). Four of them were identified as biomarkers, primarily regulating energy metabolism and oxidative balance. In conclusion, feeding HSF and ZF FTMR enhances glutathione metabolism and antioxidant capacity in heifers, positioning key metabolites as candidates for ADG markers. This integrative omics approach underscores the potential for enhancing livestock productivity and promoting sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

Agro-industrial by-products (AIBPs) could potentially be sustainable feedstuff, yet these materials' practicability shall be studied for their proper application by the livestock sector. The purpose of the current study was to determine the nutritional values and degradability kinetics of orange pulp silage pre-processed with different urea levels using gas production (GP) and nylon bag techniques. For this purpose, two fistulated Ghezzel wethers (body weight 35 ± 1.8 kg) were used for ruminal fluid collection. Experimental treatments included: (1) orange pulp silage pre-processed with 1% urea (OP1%) and (2) orange pulp silage pre-processed with 2% urea (OP2%). Dry matter (DM) and crude protein (CP) degradability and digestion kinetics of the experimental treatments were investigated at different hours of in vivo and in vitro incubation. No significant difference was observed in the proximate analysis of treatments (P > 0.05). A higher value of DM degradability was obtained for OP2% compared with OP1% according to the results of the nylon bag technique after 96 h of ruminal incubation. There was a significant difference in CP degradability and the rate of degradability between treatments (P < 0.05). Pre-processing of the orange pulp with 2% urea resulted in a higher value of effective rumen degradable protein as compared to 1% urea (P < 0.05). However, no significant difference was observed for the rate of GP. It can be concluded that pre-processing of orange pulp with urea in the pre-silage stage affects the degradability of DM and CP. Furthermore, effective utilization of AIBPs, as a valuable feed source, in ruminant's diets could reduce environmental pollution. [ABSTRACT FROM AUTHOR]

Maize (Zea mays) is a critical global crop, serving as a source of food, livestock feed, and industrial raw materials. Climate changes, driven by rising atmospheric carbon dioxide (CO2) levels, have substantial effects on maize physiology, growth, and nutrient content. This review investigates the impact of elevated CO2 on maize, with a particular focus on photosynthesis enhancement as it improves water use efficiency (WUE), which can lead to increased biomass production. Despite this, elevated CO2 results in a decreased concentration of essential nutrients, including nitrogen, phosphorus, potassium, and folate. The reduction in folate, which is vital for both plant development and human nutrition, poses challenges, especially for population heavily reliant on maize. Additionally, biofortification through traditional breeding and genetic engineering is proposed as a strategy to enhance folate level in maize to mitigate nutritional deficiencies. Elevated CO2 stimulates lignin production, improving stress resistance and carbon sequestration capacity. However, the increase in guaiacyl-rich lignin may negatively affect biomass degradability and efficiency in biofuel production. The findings emphasize the importance of balancing maize's stress resilience, nutrient profile, and lignin composition to address future climate challenges. This balance is essential for optimizing maize cultivation for food security, biofuel production, and environmental sustainability. [ABSTRACT FROM AUTHOR]

Remote sensing estimation of maize residue cover (MRC) can rapidly acquire large-scale data on MRC, crucial for monitoring and promoting conservation tillage. Herein, seven tillage indices derived from Sentinel-2 satellite imagery were analyzed alongside measured MRC data to assess their correlation with MRC. MRC estimation models were built using six machine learning algorithms, including back propagation neural network (BPNN), random forest (RF), support vector regression (SVR), extreme gradient boosting (XGBoost), Stacking1, and Stacking2. Model performance was compared using the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The potential for conservation tillage was explored. The results showed that the R2 values of the seven tillage indices in the study area exceeded 0.5, with particularly high correlations for NDTI and STI, with R2 values of 0.755 and 0.751, respectively. When using machine learning algorithms to construct models, the Stacking2 model exhibited the highest estimation accuracy, with an R2 of 0.923, RMSE of 3.32%, and MAE of 0.025, while Stacking1 also demonstrated robust performance, with an R2 of 0.910, RMSE of 3.45%, and MAE of 0.029. Among the base models, XGBoost achieved the highest estimation performance and the lowest error, with R2, RMSE, and MAE values of 0.884, 4.77%, and 0.031, respectively. The R2 values of RF, SVR, and BPNN were 0.865, 0.859, and 0.842, respectively, with RMSE values of 4.06%, 4.76%, and 5.91%, and MAE values of 0.039, 0.047, and 0.059, respectively. These results indicate that the Stacking2 model demonstrates a significant advantage in prediction accuracy. Geostatistical analysis of the inversion results of the Stacking2 model revealed that the proportions of farmland with MRC values exceeding 30% in Changchun, Songyuan, and Siping were 81.90%, 77.96%, and 83.58%, respectively. This indicates that Changchun and Siping have greater potential for implementing conservation tillage. This study demonstrates that the stacking ensemble learning model significantly improves the predictive performance by leveraging the strengths of multiple base models and accurately monitoring the spatial distribution of MRC. [ABSTRACT FROM AUTHOR]

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Copyright of Acta Prataculturae Sinica is the property of Acta Prataculturae Sinica Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)