Optimization of anaerobic fermentation and aerobic stability of total mixed ration via wet distiller's grains incorporation: Insights into clean recycling and nitrogen emissions control.

Effects of dietary allicin supplementation on nutrient digestion and gastrointestinal health of Guizhou black goats.

The intensive damage caused by citrus pests such as Phyllocnistis citrella and Prays citri requires the use of efficient, safe, and eco-friendly control measures. This study reports the development, characterization, and evaluation of a novel fluid bed-dried formulation based on Bacillus thuringiensis kurstaki (Btk) strains, namely Lip and Blb1, produced via submerged fermentation on wheat bran. The concentrated pellets using Lip achieved mean values of 9.93 Log10 CFU/g dry matter (gdm) spores and 117mg/gdm proteins, with post-formulation of 9.51 Log10 CFU/gdm and 15mg/gdm, respectively. Number- and volume-based size distribution functions were analysed for dry formulations (Btk Lip, Btk Blb1, and Delfin®) and solubilized suspensions, demonstrating critical safety and application criteria associated with "fine" and "coarse" populations. For the Delfin® suspension, remaining "coarse" particles (>100µm: 21.7%) were specifically reported. Laboratory bioassays against P. citrella, confirmed no significant differences across all formulations, whereas for P. citri, and Spodoptera frugiperda the lethal concentration of 50% (LC50) of Delfin® was significantly lower than Lip- and Blb1 formulations (p<0.001). In a field trial against P. citrella, Lip and Blb1 induced significantly faster mortality (LT50=1.67 d and 1.61 d, respectively) than Delfin® (LT50=2.89 d, p<0.001). This study addresses whether fluid bed-dried formulations of locally isolated Btk strains produced on wheat bran-based media can combine physicochemical robustness, effective dispersion, and high insecticidal efficacy against citrus pests, offering a sustainable alternative to commercial Btk products.

The aim of this study was to determine whether smart data informed genetic variability for dairy merit traits may act as a predictor for fertility dynamics in Murciano-Granadina does. A total of 17,012 AI records performed on 6706 does were used to model fertility across insemination day, buck batch×day, and semen type, defining three fertility dynamics indicators. Cubic regression models resulted best-fitting alternatives to characterize fertility indicators and estimate baseline levels, temporal trends, and nonlinear patterns. Regularized canonical correlation analysis (rCCA) was then applied to relate a first variable set comprising fertility indicators cubic regression parameters to a second set comprising predicted breeding values (PBVs) for dairy merit traits -linear appraisal system (LAS) zoometrics and milk yield and composition traits-. First two canonical functions explained >90% shared variability, linking fertility dynamics to body structure (udder width, rump conformation, chest depth). Milk composition PBVs (dry matter, lactose) were synergistic with fertility, while milk yield and body size were antagonistic. Somatic cell count PBVs negatively correlated with fertility, highlighting the role of udder integrity. Fertility curve parameters also provided information beyond milk and conformation PBVs, supporting their value as complementary genetic descriptors. Overall, fertility dynamics follow nonlinear trajectories captured by cubic regression and show structured relationships with dairy-merit PBVs, indicating that genetic variability in conformation and milk composition predicts fertility over time. Accordingly, integrating fertility curve parameters with dairy-merit PBVs can enable smart data-driven genetic evaluations and improve selection for structural soundness, milk quality, and reproductive performance in Murciano-Granadina goats.

This study investigated the effect of mixing whole milk with hot water extract of cocoa, coffee, or tea on milk intragastric coagulation during dynamic in vitro digestion. Milk diluted with water in the same proportion (70:30v/v) was used as the control. The effect of adding cocoa, coffee, or tea extracts on acid- and pepsin-induced milk coagulation was first studied using a rheometer. The control exhibited a significantly shorter (P<0.0001) gelation time in acid-induced coagulation than the milk mixtures containing extracts. The delaying effect of extracts on pepsin-induced coagulation was even more pronounced with coffee, causing a marked delay in gelation time, while tea and cocoa completely prevented gel formation under our experimental conditions. The milk mixtures, preheated to 60°C, were then studied during simulated gastric digestion using the NEar Real Digestive Tract (NERDT™) dynamic in vitro digestion system. Samples collected at the stomach exit at different time points were investigated for pH, dry matter and microstructure. During gastric digestion of the control, protein coagulation occurred between 5 and 18min (pH6.3±0.01 and 5.7±0.28, respectively), whereas in the presence of cocoa, coffee, or tea, milk coagulation was observed between 18 and 27min (pH5.6±0.07 and 4.84±0.22 respectively). Confocal micrographs revealed larger protein aggregates in samples containing extracts, with entrapped milk fat clearly visible. The observed effects are likely due to the high polyphenol content of the extracts, which are known to interact with milk proteins. Our findings therefore suggest that protein-polyphenol interactions delay casein coagulation in the stomach and may alter gastric emptying and subsequent nutrient absorption along the small intestine.

Yield vs. functionality: Enzyme-assisted extraction of mango peel reduces antioxidant dietary fiber quality

Organic fraction of municipal solid waste (OFMSW) is a valuable feedstock within a circular economy. At well-defined process conditions, enzymatic hydrolysis followed by microbial conversion of hydrolysis products can lead to valuable carboxylic acids. The present study assesses enzymatic hydrolysis of OFMSW at 15% dry matter and thermophilic conditions (55°C). Torque measurements from a four-vessel parallel bioreactor system were made to monitor changes in viscosity of the OFMSW slurry. Additionally, the influence of minimum pH setpoints at pH 5.0 and pH 6.0 on enzymatic hydrolysis as well as on the formation of organic acids was evaluated. Adding enzymes, which are tailored to the substrate, led to a rapid drop in torque at the beginning of the incubation. This reduction in viscosity by liquefaction of the OFMSW slurry can improve the processability of the slurry as well as reduce the energy consumption during stirring. It was possible to correlate the release of glucose as well as the changes in torque to the enzyme addition. A minimum pH setpoint of 6.0 appears to favour organic acid formation from indigenous microorganisms. This resulted in an 26.6% increase of lactic acid to 27.9 ± 0.49 g L -1 and a metabolisation into butyric acid of up to 15.4 ± 1.8 g L -1 . The presented results provide valuable information about the processing of OFMSW for future valorisation within biorefinery processes. • Enzyme addition led to rapid reduction in torque and viscosity. • Liquefaction and reduced disturbances during stirring were achieved. • Substantial concentrations of lactic acid and butyric acid were obtained.

Environmental and economic performance of food surplus upcycling via freeze-drying under current and future energy systems

Effects of coenzyme Q10 on growth performance, rumen fermentation, blood metabolites, antioxidant status, and immune responses of pre-weaned Holstein dairy calves.

Jerusalem artichoke (Helianthus tuberosus L.) (JA) is an underutilized crop valued for its nutritional potential, agronomic adaptability, and suitability for sustainable food systems. Despite increasing interest, comprehensive data on its mineral composition and associated food safety risks remain limited. This study aimed to evaluate the macro- and microelement profiles of ten JA cultivars, assess their bioaccumulation behavior, and estimate potential health risks related to cadmium (Cd) and lead (Pb) intake. Potassium (K) was the dominant macronutrient in tubers (13 052-19 767 mg kg-1 dry matter (DM)), followed by calcium (Ca), magnesium (Mg), and phosphorus (P), with pink-skinned cultivars exhibiting higher K and Mg concentrations. Among microelements, iron (Fe) (9.32-14.7 mg kg-1 DM), zinc (Zn) (5.25-6.67 mg kg-1 DM), copper (Cu) (4.12-5.34 mg kg-1 DM), and manganese (Mn) (1.71-2.58 mg kg-1 DM) predominated, showing pronounced cultivar-specific differences. Bioaccumulation factors indicated efficient uptake of Cu and Zn, whereas Fe and Mn exhibited limited translocation to tubers. The Cd and Pb content varied substantially among cultivars, ranging from 0.01 to 0.30 mg kg-1 DM and 0.21 to 1.86 mg kg-1 DM, respectively. Several cultivars exceeded the maximum levels established under European Commission (EU) Regulation 2023/915. Health risk assessment demonstrated low estimated daily intake contributions to provisional tolerable weekly intake values; target hazard quotient values for individual elements were below 1, and the overall hazard index (0.02-0.18) indicated negligible non-carcinogenic risk. Jerusalem artichoke tubers are a valuable source of essential minerals; however, cultivar-dependent accumulation of Cd and Pb may pose food safety concerns. Careful cultivar selection and systematic soil monitoring are essential to ensure the safe nutritional utilization of this crop. © 2026 Society of Chemical Industry.

Tailoring highly stretchable, ultra-barrier, and transparent gelatin/PVA emulgel-templated oleofilms: Effect of oil saturation degree

Lactational performance of dairy cows fed ad libitum grass silages of different quality supplemented with concentrates high or low in locally sourced ingredients.

Leaf dry matter outperforms leaf area index in developing critical nitrogen dilution curves for nitrogen management of drip-irrigated high-density maize

Performance, carcass traits and meat quality of lambs fed sugarcane silage (Saccharum officinarum) with or without Tithonia diversifolia.

Growth and profitability of Arsi-Bale rams using Brachiaria mutica hay and strategic concentrate supplementation.

Development and evaluation of a mango-based whey drink using three processing techniques: A comparative study of their bioactive and nutritional profiling

The black soldier fly (BSF) (Hermetia illucens) has gained global economic relevance as a sustainable resource for animal feed, organic waste bioconversion, and the production of nutrient-rich frass for agricultural use. Its ability to convert low-value waste streams into high-value proteins, lipids, and fertilisers makes BSF a key component of emerging circular-economy models. However, the influence of vegetableand fruit waste (VFW) substrates on insect performance, nutrient composition, frass quality, and economic efficiency remains poorly defined. This study evaluated five substrate levels obtained by mixing laying hen feed with VFW at 0%, 25%, 50%, 75%, and 100%, assessing their effects on the growth performance, body measurements, chemical composition, frass characteristics, and economic traits of BSF larvae and prepupae. The results showed that up to 75% VFW can be used to rear BSF up to 23days of age without compromising growth traits. Substrate reduction ranged from 67.2% to 89.4%, and larval-to-prepupal conversion increased with feed intake. VFW level significantly affected larval and prepupal nutrient profiles, including dry matter, crude protein, ether extract, nitrogen-free extract, and chitin. Frass from the 100% VFW substrate exhibited the highest nutrient concentration, although this inclusion level impaired feed conversion due to elevated fibre content. Economic analysis indicated that using VFW can reduce substrate costs without negatively affecting revenue. Overall, a VFW inclusion level of up to 75% is recommended as the optimal balance between insect growth efficiency, nutrient recycling, and frass fertilising potential.

Knowledge of diet composition and intake levels in beef cattle is valuable for post hoc feed traceability and for more accurate modelling of the diet impact on methane emissions and performance traits. However, a direct measure of this information can be costly and labour-intensive and is not always feasible. In this study, rumen metagenomic data combined with machine learning algorithms were used to predict diet type, nutritional composition, and intake levels. An external validation to assess the generalizability of the models was also performed. Rumen samples were collected from 142 animals belonging to two breeds, Luing (n = 70) and Charolais crossbred (n = 72), with 425.6 ± 43.5 d old and 461.9 ± 70.2 kg body weight. The animals participated in a 56-d feeding trial and were assigned to diets differing in forage-to-concentrate ratio, with 72 animals receiving a concentrate-based diet and 70 receiving a forage-based diet. Liquid ruminal contents were collected immediately postmortem and subsequently subjected to metagenomic sequencing. Based on these sequences, the relative abundance of microbial genes (MGs), microbial genera (MTs), and phyla were determined. The log-ratio between the abundances of Verrucomicrobia and Chlorobi discriminated diet type with an average classification accuracy of 0.86 ± 0.05, while using the log-ratio transformed abundances of 4769 MTs and MGs as predictors reached 0.90 ± 0.05. All this microbiome information was used in a random forest model to predict continuous values for nutritional diet components starch, crude protein, neutral and acid detergent fibre, and metabolizable and gross energy with external validation prediction accuracy values between 0.77 and 0.83. Microbiome features important for prediction of diet components such as fibre and starch included Mitsuokella, Selenomonas, and MGs involved in flagellar assembly and aminoacyl-tRNA biosynthesis. Microbiome data were more informative for predicting the feed composition than the amount of feed consumed, which reached a prediction accuracy of 0.27 ± 0.12 for dry matter intake (DMI). However, microbiome data can still be used as a screening tool to classify DMI into low, medium, or high with a classification accuracy of 0.74. Incorporating dietary information into linear phenotypic and genetic models to predict methane production (MP) and DMI reduced root mean square error (RMSE) by 26.9% and 9.6%, respectively, in the phenotypic model. In the genetic model, only MP showed a reduction in RMSE, with a 31% improvement. These findings highlight rumen microbiome data as a valuable tool for the post hoc prediction of feed composition in beef cattle.

Optimization of LED-based phototreatments for enhancing antioxidant potential and marketable traits in microgreens

Ecology of the free-living stages of goat gastrointestinal nematodes during spring-summer contamination in Salta province, Argentina.