bluuebunny/crossref_metadata_2025 huggingface dataset:
Politico-Administrative Culture and Public Service Reform in Post-Independence Kazakhstan
Authors: Karini Artan
Published: October 2024

Classical organizational management literature draws clear parallels between organizational culture and climate and effective use of power and influence as key to successful policy implementation of reforms in public sector organizations. On the other hand, the public policy literature, in particular, policy transfer as a strand within policy studies, emphasizes the role of the national context, more specifically, ‘facilitators’ and ‘constraints’ of ‘‘politico-administrative culture” within the national context, as crucial to understanding processes of transfer, convergence, and diffusion of public policy. There is a plethora of studies by Western scholars of public management who have successfully utilized these theoretical underpinnings to study the effectiveness of public service reforms in mature policy environments such as the UK, the US, Australia, New Zealand, and others. However, the public policy and comparative public management literature only offers a limited number of case studies from developing, middle-/upper-middle countries, which rely on concepts of organizational management in addition to narratives on the impact of policy learning from global doctrines, such as Weberianism, New Public Management (NPM), and New Public Governance (NPG), and national politics, on the implementation of administrative reforms in those contexts. Kazakhstan, as a resource-affluent post-Soviet country and a bastion of modernization and ‘open government’ in Central Asia or the Commonwealth of Independent States (CIS) in the post-Soviet era is a case in point. Based on ethnographic research consisting of interviews with elite academics, civil servants, and think-tank activists, as well as reviews of OECD and government strategy reports in Astana, the findings point to a potential abatement of the impact of context constraints such as large power distance and collectivist behavior by context facilitators such as those surrounding the use of ‘trilingualism’ and public diplomacy towards reforms in Kazakhstan particularly in recent years.
An Analysis of a Complete Aircraft Electrical Power System Simulation Based on a Constant Speed Constant Frequency Configuration
Authors: Grigore-Müler Octavian
Published: October 2024

Recent developments in aircraft electrical technology, such as the design and production of more electric aircraft (MEA) and major steps in the development of all-electric aircraft (AEA), have had a significant impact on aircraft’s electrical power systems (EPSs). However, the EPSs of the latest aircraft produced by the main players in the market, Airbus with the Neo series and Boeing with the NG and MAX series are still completely traditional and based on the constant speed constant frequency (CSCF) configuration. For alternating current ones, the EPS is composed of the following: prime movers, namely the aircraft turbofan engine (TE); the electrical power source, i.e., the integrated drive generator (IDG); the command and control system, the generator control unit (GCU); the transmission and the system distribution system; the protection system, i.e., the CBs (circuit breakers); and the electrical loads. This paper presents the analysis of this system using the Simscape package from Simulink v 8.7, a MATLAB v 9.0 program, which is actually the development of some systems designed in two previous personal papers. For the first time in the literature, a complete MATLAB modelled EPS system was presented, i.e., the aircraft turbofan engine model, driving the constant speed drive system (CSD) (model presented in the first reference as a standalone type and with different parameters), linked to the synchronous generator (SG) (model presented in second reference for lower power and rotational speed) in the so-called integrated drive generator (IDG) and electrical loads.
Joint Optimization of Cost and Scheduling for Urban Air Mobility Operation Based on Safety Concerns and Time-Varying Demand
Authors: Wang Yantao , Li Jiashuai , Yuan Yujie , Lai Chun Sing
Published: October 2024

As the value and importance of urban air mobility (UAM) are being recognized, there is growing attention towards UAM. To ensure that urban air traffic can serve passengers to the greatest extent while ensuring safety and generating revenue, there is an urgent need for a transportation scheduling plan based on safety considerations. The region of Beijing–Tianjin–Hebei was selected as the case study in this research. A real-time demand transportation scheduling model for a single day was constructed, with the total service population and total cost as objective functions, and safety intervals, eVTOL performance, and passenger maximum waiting time as constraints. A Joint Optimization of Cost and Scheduling Particle Swarm Optimization (JOCS-PSO) algorithm was utilized to obtain the optimal solution. The optimal solution obtained in this study can serve 138,610,575 passengers during eVTOLs’ entire lifecycle (15 years) with a total cost of CNY 368.57 hundred million, with the cost of CNY 265.9 per passenger. Although it is higher than the driving cost, it saves 1–1.5 h and thus has high cost effectiveness during rush hours.
The Development of a Prediction Model Related to Food Loss and Waste in Consumer Segments of Agrifood Chain Using Machine Learning Methods
Authors: Nijloveanu Daniel , Tița Victor , Bold Nicolae , Popescu Doru Anastasiu , Smedescu Dragoș , Smedescu Cosmina , Fîntîneru Gina
Published: October 2024

Food loss and waste (FLW) is a primary focus topic related to all human activity. This phenomenon has a great deal of importance due to its effect on the economic and social aspects of human systems. The most integrated approach to food waste analysis is based on the study of FLW alongside the agrifood chain, which has also been performed in previous studies by the authors. This paper presents a modality of determination of food loss and waste effects with an emphasis on consumer segments in agrifood chains in the form of a predictive model based on statistical data collected based on specific methods in Romania. The determination is made comparatively, using two predictive machine learning-based methods and separate instruments (software), in order to establish the best model that fits the collected data structure. In this matter, a Decision Tree Approach (DTA) and a Neural Network Approach (NNA) will be developed, and common methodologies of the approaches will be applied. The results will determine predictive outcomes for a specific food waste (FW) agent (e.g., consumer) based on pattern recognition of the collected data. The results showed relatively high-accuracy predictions, especially for the NN approach, with lower performances using the DTA. The effects of the application of this predictive model will be expected to improve the food loss prevention measures within economic contexts when applied to real-life scenarios.
Increasing Productivity and Fruit Quality of ‘Mutsu’ Apple Orchard by Dwarfing Treatments
Authors: Małachowska Maria , Majak Tomasz , Krupa Tomasz , Tomala Kazimierz
Published: October 2024

The aim of this 2022 study was to evaluate the effect of tree growth-limiting treatments on the tree yield and quality of ‘Mutsu’ apples. The experiment was established on 7-year-old trees on M.9 rootstock in a commercial orchard in Wilga near Warsaw. Growth-limiting treatments included unilateral root pruning, spraying the trees with Regalis Plus 10 WG at various times, and spraying with Flordimex 480 SL. Eight combinations were used, with four replicates of 20 trees per repetition. The measurements included fruit set, length of this year’s shoots, yield per tree, average fruit weight, and the size structure of the yield. The distinctive physiological status of the apples was assessed directly after harvest, directly after 8 months of storage under CA conditions (1.5% CO2, 1.5% O2, 1 °C, >92% RH) and after an additional 7 days of shelf-life. Spraying trees with Regalis Plus 10 WG from the balloon stage onwards, irrespective of the treatment with root pruning, was most effective in both inhibiting long-stem growth and increasing tree yield (by almost two times) by increasing the number of apples per tree. The growth response of long-stemmed apple trees to both unilateral root pruning and Ethephon spray was significantly lower than it was to Regalis Plus 10 WG spray and had relatively little effect on their yield. Regalis Plus 10 WG resulted in a clear reduction in average fruit weight (by about 100 g), which, in the case of the large-fruited cultivar ‘Mutsu’, should be seen as an advantage. Its application from the balloon stage onwards promoted higher apple firmness at harvest and after simulated handling preceded by long-term storage.
Two-Stage Multimodal Method for Predicting Intramuscular Fat in Pigs
Authors: Liu Wenzheng , Liu Tonghai , Zhang Jianxun , Wang Fanzhen
Published: October 2024

Intramuscular fat (IMF) content significantly influences pork tenderness, flavor, and juiciness. Maintaining an optimal IMF range not only enhances nutritional value but also improves the taste of pork products. However, traditional IMF measurement methods are often invasive and time-consuming. Ultrasound imaging technology offers a non-destructive solution capable of predicting IMF content and assessing backfat thickness as well as longissimus dorsi muscle area size. A two-stage multimodal network model was developed in this study. First, using B-mode ultrasound images, we employed the UNetPlus segmentation network to accurately delineate the longissimus dorsi muscle area. Subsequently, we integrated data on backfat thickness and longissimus dorsi muscle area to create a multimodal input for IMF content prediction using our model. The results indicate that UNetPlus achieves a 94.17% mean Intersection over Union (mIoU) for precise longissimus dorsi muscle area segmentation. The multimodal network achieves an R2 of 0.9503 for IMF content prediction, with Spearman and Pearson correlation coefficients of 0.9683 and 0.9756, respectively, all within a compact model size of 4.96 MB. This study underscores the efficacy of combining segmented longissimus dorsi muscle images with data on backfat thickness and muscle area in a two-stage multimodal approach for predicting IMF content.
KOALA: A Modular Dual-Arm Robot for Automated Precision Pruning Equipped with Cross-Functionality Sensor Fusion
Authors: Vikram Charan , Jeyabal Sidharth , Chittoor Prithvi Krishna , Pookkuttath Sathian , Elara Mohan Rajesh , You Wang
Published: October 2024

Landscape maintenance is essential for ensuring agricultural productivity, promoting sustainable land use, and preserving soil and ecosystem health. Pruning is a labor-intensive task among landscaping applications that often involves repetitive pruning operations. To address these limitations, this paper presents the development of a dual-arm holonomic robot (called the KOALA robot) for precision plant pruning. The robot utilizes a cross-functionality sensor fusion approach, combining light detection and ranging (LiDAR) sensor and depth camera data for plant recognition and isolating the data points that require pruning. The You Only Look Once v8 (YOLOv8) object detection model powers the plant detection algorithm, achieving a 98.5% pruning plant detection rate and a 95% pruning accuracy using camera, depth sensor, and LiDAR data. The fused data allows the robot to identify the target boxwood plants, assess the density of the pruning area, and optimize the pruning path. The robot operates at a pruning speed of 10–50 cm/s and has a maximum robot travel speed of 0.5 m/s, with the ability to perform up to 4 h of pruning. The robot’s base can lift 400 kg, ensuring stability and versatility for multiple applications. The findings demonstrate the robot’s potential to significantly enhance efficiency, reduce labor requirements, and improve landscape maintenance precision compared to those of traditional manual methods. This paves the way for further advancements in automating repetitive tasks within landscaping applications.
Optimization of Operating Parameters for Straw Returning Machine Based on Vibration Characteristic Analysis
Authors: Gao Yuanyuan , Hu Yongyue , Yang Yifei , Feng Kangyao , Han Xing , Li Peiying , Zhu Yongyun , Song Qi
Published: October 2024

For the mechanized technical mode of total wheat straw returning to field, there are problems such as large vibration during the operation of the straw returning machine that, in turn, affect the effect of stubble breaking. This study took the Tongtian 1-JHY-220 straw returning machine as the research object to conduct field experiments, with wheat stubble height, forward velocity, and PTO speed as experimental parameters. And the vibration characteristics at different positions of the machine and the final stubble breaking rate were used as evaluation indicators. Combined with the orthogonal experiment and response surface analysis method, this article analyzes and discusses the influence of various parameters on vibration characteristics and operational effectiveness. The results show that PTO speed and wheat stubble height were the main factors affecting the vibration and operation quality of the straw returning machine. Low PTO speed and high stubble height can improve the stubble breaking rate of the straw returning machine and reduce its operation vibration. Furthermore, the multi-objective optimization results show that when the forward velocity in the range of 8.5–9 km/h, the PTO speed is 540 r/min, and the stubble height is in the range of 200–250 mm, the stubble breaking rate of the straw returning machine is greater than 86%. At this time, the total vibration of the straw returning machine and tractor rear axle is relatively small. This study can lay a foundation for further studying the impact of the vibration of the straw returning machine on the stubble breaking effect and provide a reference for the preparation of high-quality seedbed under conservation tillage.
Identification of High-Photosynthetic-Efficiency Wheat Varieties Based on Multi-Source Remote Sensing from UAVs
Authors: Feng Weiyi , Lan Yubin , Zhao Hongjian , Tang Zhicheng , Peng Wenyu , Che Hailong , Zhu Junke
Published: October 2024

Breeding high-photosynthetic-efficiency wheat varieties is a crucial link in safeguarding national food security. Traditional identification methods necessitate laborious on-site observation and measurement, consuming time and effort. Leveraging unmanned aerial vehicle (UAV) remote sensing technology to forecast photosynthetic indices opens up the potential for swiftly discerning high-photosynthetic-efficiency wheat varieties. The objective of this research is to develop a multi-stage predictive model encompassing nine photosynthetic indicators at the field scale for wheat breeding. These indices include soil and plant analyzer development (SPAD), leaf area index (LAI), net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO2 concentration (Ci), stomatal conductance (Gsw), photochemical quantum efficiency (PhiPS2), PSII reaction center excitation energy capture efficiency (Fv’/Fm’), and photochemical quenching coefficient (qP). The ultimate goal is to differentiate high-photosynthetic-efficiency wheat varieties through model-based predictions. This research gathered red, green, and blue spectrum (RGB) and multispectral (MS) images of eleven wheat varieties at the stages of jointing, heading, flowering, and filling. Vegetation indices (VIs) and texture features (TFs) were extracted as input variables. Three machine learning regression models (Support Vector Machine Regression (SVR), Random Forest (RF), and BP Neural Network (BPNN)) were employed to construct predictive models for nine photosynthetic indices across multiple growth stages. Furthermore, the research conducted principal component analysis (PCA) and membership function analysis on the predicted values of the optimal models for each indicator, established a comprehensive evaluation index for high photosynthetic efficiency, and employed cluster analysis to screen the test materials. The cluster analysis categorized the eleven varieties into three groups, with SH06144 and Yannong 188 demonstrating higher photosynthetic efficiency. The moderately efficient group comprises Liangxing 19, SH05604, SH06085, Chaomai 777, SH05292, Jimai 22, and Guigu 820, totaling seven varieties. Xinmai 916 and Jinong 114 fall into the category of lower photosynthetic efficiency, aligning closely with the results of the clustering analysis based on actual measurements. The findings suggest that employing UAV-based multi-source remote sensing technology to identify wheat varieties with high photosynthetic efficiency is feasible. The study results provide a theoretical basis for winter wheat phenotypic monitoring at the breeding field scale using UAV-based multi-source remote sensing, offering valuable insights for the advancement of smart breeding practices for high-photosynthetic-efficiency wheat varieties.
A Spatial Analysis of Coffee Plant Temperature and Its Relationship with Water Potential and Stomatal Conductance Using a Thermal Camera Embedded in a Remotely Piloted Aircraft
Authors: Santos Luana Mendes dos , Ferraz Gabriel Araújo e Silva , Carvalho Milene Alves de Figueiredo , Campos Alisson André Vicente , Neto Pedro Menicucci , Xavier Letícia Aparecida Gonçalves , Mattia Alessio , Becciolini Valentina , Rossi Giuseppe
Published: October 2024

Coffee is a key agricultural product in national and international markets. Physiological parameters, such as plant growth indicators, can signal interruptions in these processes. This study aimed to characterize the temperature obtained by a thermal camera embedded in a remotely piloted aircraft (RPA) and evaluate its relationship with the water potential (WP) and stomatal conductance (gs) of an experimental coffee plantation using geostatistical techniques. The experiment was conducted at the Federal University of Lavras, Minas Gerais, Brazil. A rotary-wing RPA with an embedded thermal camera flew autonomously at a height of 10 m and speed of 10 m/s. Images were collected on 26 November 2019 (rainy season), and 11 August 2020 (dry season), between 9:30 am and 11:30 am. Data on gs and WP were collected in the field. The thermal images were processed using FLIR Tools 5.13, and temperature analysis and spatialization were undertaken using geostatistical tools and isocolor maps by Kriging interpolation in R 4.3.2 software. Field data were superimposed on final crop temperature maps using QuantumGIS version 3.10 software. The study found that with decreasing WP, stomatal closure and reduction in gs occurred, increasing the temperature due to water deficit. The temperature distribution maps identified areas of climatic variations indicating water deficit.
Exogenously Applied Gibberellic Acid Alters Cannabinoid Profile in Cannabis sativa L.
Authors: Oultram Jackson M. J. , Pegler Joseph L. , Eamens Andrew L. , Gordon Rebecca , Korbie Darren J. , Grof Christopher P. L.
Published: October 2024

Cannabis sativa (C. sativa L.) has garnered significant attention worldwide due to its widespread use as a pharmaceutical agent. With the increasing clinical application of C. sativa and cannabinoid therapeutics, there is strong interest in the development of superior plant varieties and optimisation of growth conditions to enhance secondary metabolite yield. Our RNA sequencing analysis revealed differential expression of hormone-related transcripts in developing C. sativa trichomes, suggesting the involvement of hormone signalling pathways in cannabinoid production. Leveraging the potency of exogenous hormones on plants, this study sought to determine if the application of cytokinin (CK), gibberellic acid (GA) and jasmonic acid (JA) modified trichome morphology and the cannabinoid profile over an 8-week period following the induction of flowering. Exogenous hormone application led to alterations in trichome morphology, with each treatment significantly reducing trichome head width by the final week of assessment. Interestingly, GA application also resulted in a significant reduction in the concentration of Δ-9-tetrahydrocannabinol (THC), Δ-9-tetrahydrocannabinolic acid (THCA), cannabidiol (CBD) and cannabidiolic acid (CBDA) by week 8 post floral induction, however, JA and CK treatment did not consistently modulate the accumulation of these cannabinoids. The minor cannabinoids, cannabidivaranic acid (CBDVA), cannabicyclolic acid (CBLA), cannabicyclol (CBL), cannabichromene (CBC), cannabigerolic acid (CBGA) and cannabigerol (CBG), were also affected by hormone treatments, with varying degrees of accumulation observed. These findings underscore the intricate interplay between phytohormones and secondary metabolite biosynthesis in C. sativa. Our study highlights the potential of hormone modulation as a strategy to enhance cannabinoid yield and offers some insights into the regulatory mechanisms governing cannabinoid biosynthesis in C. sativa trichomes.
The Use of Anaerobic Digestate for Greenhouse Horticulture
Authors: Jankauskienė Julė , Laužikė Kristina , Kaupaitė Samanta
Published: October 2024

Agricultural crop production practices are being developed for organic, sustainable, and environmentally friendly farming systems. Developing efficient and resourceful crop fertilizers is significantly important for future agriculture. Various biofertilizers, such as animal manures, composts, and vegetable byproducts, have been successfully applied in agriculture. Anaerobic digestate, organic matter obtained from animal or plant waste processing during anaerobic digestion into biomass, has become popular due to its versatility, multiple purposes, and facile application methods. Digestate has recently been widely used in agriculture to enrich the soil with nutrients and thus increase crop yields. Several studies have shown that anaerobic digestate is a valuable fertilizer that can be used as a biofertilizer in field and greenhouse horticulture. Also, research has been carried out on the use of digestate in hydroponic horticulture. This review presents the research results and discusses the possibilities of using anaerobic digestate in greenhouse horticulture. Its objective is to provide a comprehensive understanding of the application of digestate from various sources and its impact on the growth, progress, yield, and quality of greenhouse-grown vegetables.
Unravelling the Current Status of Rice Stripe Mosaic Virus: Its Geographical Spread, Biology, Epidemiology, and Management
Authors: Mas-ud Md. Atik , Chowdhury Md. Rayhan , Juthee Sadiya Arefin , Rabbee Muhammad Fazle , Matin Mohammad Nurul , Kang Sang Gu
Published: October 2024

Rice stripe mosaic virus (RSMV) belongs to the Cytorhabdovirus species in the Rhabdoviridae family. Recently, RSMV was widely spread in East Asia and caused severe yield losses. RSMV is transmitted by the planthopper vectors, Recilia dorsalis, Nephotettix virescens, and Nilaparvata lugens, that mostly affect rice. The adult vectors can hibernate, transmit the virus, lay eggs on rice plants, and, finally, multiply in subsequent generations, resulting in new infection outbreaks. RSMV-infected rice varieties display striped mosaicism, mild dwarfism, stiff and twisted leaves, delayed heading, short panicles with large unfilled grains, and yield reduction. In nature, the infection of multiple pathogens in the same host is widespread, which is defined as co-infection. It can be antagonistic or synergistic. Pathological synergistic effects between RSMV and other viruses can generate strains with new genetic characteristics, leading to unpredictable epidemiological consequences. After the first identification of RSMV in 2015, significant advancements in understanding the disease’s characteristics, symptoms, cycles, geographic distribution, potential vectors, and synergistic interaction, as well as its management strategies, were developed. To reduce the damage due to RSMV infection, many scientists have recommended pest control techniques to target adult vectors. It is also essential to confirm the actual time of monitoring, development of resistant varieties, and changes in cultivation systems. Due to the limitations of the conventional plant disease control technologies, improvements in efficiency and safety are in high demand. Therefore, to find efficient and environmentally safe controls to mitigate these challenges, reviews of research are the foremost step. In this review, we summarize the basic epidemiological information about the origin of RSMV and its infection symptoms in the field, synergistic interaction with viruses during co-transmission, yield losses, formulation of the disease cycle, and control strategies from several case studies. Finally, we recommend the formulation of the disease cycle and management strategies of RSMV infection.
Effects of the Radicle Sheath on the Rhizosphere Microbial Community Structure of Seedlings in Early Spring Desert Species Leontice incerta
Authors: Xue Xiaolan , Mamut Jannathan
Published: October 2024

Most research on plant–microbe interactions emphasize the effects of micronutrients on the rhizosphere microbial community structure. However, the influence of seed structures, particularly the radicle sheath, on microbial diversity at the seedling root tips under varying temperatures and humidity has been less explored. This study conducted controlled indoor experiments in the northern desert of Xinjiang to assess the radicle sheath’s impact on microbial community composition, diversity, and function. The results indicated no significant changes in the Chao1 index for bacteria and fungi, but notable differences were observed in the Shannon and Simpson indices (p < 0.05). Under drought conditions, the radicle sheath significantly reduced bacterial infections without affecting fungi. Genus-level analysis showed an increased abundance of specific dominant bacterial groups when the radicle sheath was retained. NMDS analysis confirmed its significant effect on both bacterial and fungal community structures. LEfSe analysis identified 34 bacterial and 15 fungal biomarkers, highlighting the treatment’s impacts on microbial taxonomic composition. Functional predictions using PICRUSt 2 revealed that the radicle sheath facilitated the conversion of CH4 to CH3OH and various nitrogen cycle processes under drought. Overall, the radicle sheath plays a crucial role in maintaining rhizosphere microbial community stability and enhancing the functions of both bacteria and fungi under drought conditions.
Temporal Changes in Jejunal and Ileal Microbiota of Broiler Chickens with Clinical Coccidiosis (Eimeria maxima)
Authors: Miska Katarzyna B. , Campos Philip M. , Cloft Sara E. , Jenkins Mark C. , Proszkowiec-Weglarz Monika
Published: October 2024

Coccidiosis in broiler chickens continues to be a major disease of the gastrointestinal tract, causing economic losses to the poultry industry worldwide. The goal of this study was to generate a symptomatic Eimeria maxima (1000 oocysts) infection to determine its effect on the luminal and mucosal microbiota populations (L and M) in the jejunum and ileum (J and IL). Samples were taken from day 0 to 14 post-infection, and sequencing of 16S rRNA was performed using Illumina technology. Infected birds had significantly (p < 0.0001) lower body weight gain (BWG), higher feed conversion ratio (FCR) (p = 0.0015), increased crypt depth, and decreased villus height (p < 0.05). The significant differences in alpha and beta diversity were observed primarily at height of infection (D7). Analysis of taxonomy indicated that J-L and M were dominated by Lactobacillus, and in IL-M, changeover from Candidatus Arthromitus to Lactobacillus as the major taxon was observed, which occurred quicky in infected animals. LEfSe analysis found that in the J-M of infected chickens, Lactobacillus was significantly more abundant in infected (IF) chickens. These findings show that E. maxima infection affects the microbiota of the small intestine in a time-dependent manner, with different effects on the luminal and mucosal populations.
Validation of a Remote Sampling Sensor for Measuring Urine Volume and Nitrogen Concentration in Grazing Dairy Cattle
Authors: Mangwe Mancoba C. , Beale Nigel , Beckett Paige , Tey Lucas , Curtis Jeffery , Burgess Riki , Bryant Racheal H.
Published: October 2024

The purpose of this research was to validate a urine sensor (Lincoln University PEETER V2.0, Canterbury, New Zealand) that records the time and volume of urination events for dairy cows in addition to collecting a proportional urine sample from all urination events. Sixteen multiparous Holstein × Jersey mid-lactating cows (101 ± 5 days in milk, 498 ± 24.2 kg body weight, 26.2 ± 3.07 kg/d milk yield; mean ± standard deviation) were allocated herbage diets ranging in protein and sodium content to generate a range of urine volumes and urine nitrogen (UN) concentrations. Total collection of individual urination events occurred during a 72-h measurement period where PEETER V2.0 sensors were attached to cows. A mixed model ANOVA using lme4 package (version 1.1-35.5) in R (version 4.3.3) were used to compare the means. The average urine event size was 2.65 ± 1.1 L for total collection by observers and 2.68 ± 1.1 L as recorded by the sensor (mean ± standard deviation; p = 0.730). The urine nitrogen concentration was 5.76 ± 1.2 g N/L for samples collected by observers and 5.85 ± 1.3 g N/L for the samples collected by the sensor (p = 0.583). The calculated UN excretion was 156 ± 45.1 g/day for direct measurements and 162 ± 40.0 g/day for the sensor (p = 0.539. Contrasts with simultaneously measured data were undertaken using Lin’s Concordance Correlation Coefficient (CCC) and a Pearson correlation coefficient (r). Correlations between the actual values and sensor values were strong, with little to moderate variability in the urine volume (CCC = 0.936, r = 0.937; n = 222), UN concentration (CCC = 0.840, r = 0.837, n = 48) and total UN excretion (CCC = 0.827, r = 0.836, n = 24). Considering the findings, the PEETER V2.0 urine sensor has the potential to reliably measure urine volumes and UN concentrations for estimations of the UN excretion of dairy cattle under grazing systems.
The Effect of Synbiotics and Probiotics on Ochratoxin Concentrations in Blood and Tissues, Health Status, and Gastrointestinal Function in Turkeys Fed Diets Contaminated with Ochratoxin A
Authors: Mazur-Kuśnirek Magdalena , Lipiński Krzysztof , Antoszkiewicz Zofia , Śliżewska Katarzyna
Published: October 2024

The aim of this study was to evaluate carcass quality and analyze gastrointestinal functional status, ochratoxin A (OTA) accumulation in tissues and organs, and the health status of turkeys fed diets contaminated with OTA and supplemented with synbiotic preparations in comparison with commercial probiotic feed additives. The research involved 120 female BIG 6 turkeys, divided into six treatment groups (five replicates, four birds per replicate). Wheat naturally contaminated with OTA (662.03 μg/kg) was used in turkey diets. Turkeys in group 1 received an OTA-contaminated diet without additives. Groups 2 and 3 received 0.4 g/kg of probiotic preparation BioPlus 2B or Cylactin. Groups 4, 5, and 6 received 0.5 g/kg of synbiotics S1, S2, or S3. The following parameters were monitored: growth performance, carcass quality, gastrointestinal tract structure and digesta pH, health status, and concentrations of OTA in the blood and tissues of turkeys. The study found no significant differences in the growth performance and carcass quality of turkey. However, the introduction of probiotics or synbiotics into OTA-contaminated feed mixtures resulted in a reduced pH of the digesta in certain sections of the turkey digestive tract (p < 0.05). Additionally, the tested synbiotic additives significantly reduced liver weight in turkeys at weeks 6 and 15 (p < 0.05). The addition of probiotic and synbiotic preparations based on lactic acid bacteria strains, inulin, and S. cerevisiae yeasts to OTA-contaminated diets in commercial turkey farming may improve health status (p < 0.05) and reduce mycotoxin accumulation in organs and tissues of poultry (p < 0.05).
Impact of Heat Stress on Milk Yield, Milk Fat-to-Protein Ratio, and Conception Rate in Thai–Holstein Dairy Cattle: A Phenotypic and Genetic Perspective
Authors: Boonkum Wuttigrai , Teawyoneyong Watcharapong , Chankitisakul Vibuntita , Duangjinda Monchai , Buaban Sayan
Published: October 2024

Heat stress severely affects dairy cattle production and reproduction performances in tropical regions. Genetic selection to maintain adequate yield and reproductive performance while enhancing their ability to withstand heat is essential for improving the genetics of dairy cows. Therefore, in this study, we aimed to estimate genetic parameters affecting production and reproduction performances under heat stress conditions in dairy cattle and to investigate the threshold point of heat stress for milk yield (MY), milk fat-to-protein ratio (FPR), and conception rate (CR) in Thai–Holstein dairy cattle. The data included 168,124 records related to MY and milk FPR and 21,278 records of CR in Thai–Holstein dairy cattle, covering the period from 1990 to 2007. A multiple-trait threshold-linear random regression model based on a Bayesian approach via Gibbs sampling was used to estimate variance components, genetic parameters (heritability values, and genetic correlations), and decline rates for each studied trait. The threshold point of heat stress was identified as a temperature and humidity index (THI) of 76. At THI76, a decline was observed in the MY, milk FPR, and CR of Thai dairy cattle. The heritability estimates for MY, milk FPR and CR were 0.347 ± 0.032, 0.293 ± 0.021, and 0.032 ± 0.001, respectively. The genetic correlation between MY and milk FPR and MY and CR were −0.24 and −0.53, respectively, whereas those between milk FPR and heat tolerance as well as between CR and heat tolerance were −0.48 and −0.49, respectively. In addition, the decline rates in MY, milk FPR, and CR were found to be associated with a high percentage of Holstein genetics. In conclusion, the results obtained in this study reveal that the simultaneous consideration of the MY, milk FPR, CR, and heat tolerance traits of Thai–Holstein dairy cattle is possible. In addition, developing a genetic model that incorporates THI is essential for sustainably addressing heat stress problems.
Effects of Methionine on Milk Performance and Milk Constituents of Lactating Donkeys
Authors: Huang Fei , Du Xinyi , Ma Zongjie , Liu Guiqin , Wang Changfa , Zhou Miaomiao
Published: October 2024

This study investigated the effects of adding methionine (Met) in milk production and the milk and blood metabolites of lactating donkeys. Eighteen healthy multiparous donkeys in early-stage lactation were selected for this study. The donkeys were randomly divided into three groups and fed diets with different levels of Met: control group (C, Met 0 g/d), Met group I (M1, Met 5 g/d), and Met group II (M2, Met 15 g/d). The total duration of the experiment was 5 weeks. Donkey milk and blood samples were collected at the end of the experiment. The milk yield and composition, milk, and serum metabolites were analyzed. The results showed that the addition of 5 g of Met significantly increased milk yield as well as the milk composition contents of protein, fat, lactoferrin, polyunsaturated fatty acid (PFA), solids, and solids-not-fat (SNF) (p < 0.05). Significant differences in metabolites were detected among the different samples of milk (p < 0.05). The addition of Met increased the levels of milk metabolites, such as myristic acid, d-glutamine, l-aspartic acid, and LPS 16:0. A total of 753 metabolites were detected in the serum, including 17 differential metabolites between C and M1 and 48 differential metabolites between C and M2. The levels of serum metabolites, such as l-ascorbate, inositol, and l-lysine, were up-regulated by the addition of Met (p < 0.05). The above results indicated that Met increased donkey milk production and milk composition yield and improved milk metabolites by regulating serum metabolites. These results provide a foundation for improving the nutritional needs of lactating donkeys and the nutritional regulation of donkey milk synthesis.
Physiological and Genetic Basis of High-Altitude Indigenous Animals’ Adaptation to Hypoxic Environments
Authors: Zhao Pengfei , Li Shaobin , He Zhaohua , Ma Xiong
Published: October 2024

Adaptation is one of the fundamental characteristics of life activities; humans and animals inhabiting high altitudes are well adapted to hypobaric hypoxic environments, and studies on the mechanisms of this adaptation emerged a hundred years ago. Based on these studies, this paper reviews the adaptive changes in hypoxia-sensitive tissues and organs, as well as at the molecular genetic level, such as pulmonary, cardiovascular, O2-consuming tissues, and the hemoglobin and HIF pathway, that occur in animals in response to the challenge of hypobaric hypoxia. High-altitude hypoxia adaptation may be due to the coordinated action of genetic variants in multiple genes and, as a result, adaptive changes in multiple tissues and organs at the physiological and biochemical levels. Unraveling their mechanisms of action can provide a reference for the prevention and treatment of multiple diseases caused by chronic hypoxia.
Molecular Diversity of the Casein Gene Cluster in Bovidae: Insights from SNP Microarray Analysis
Authors: Malewski Tadeusz , Kamiński Stanisław , Śmiełowski Jan , Oleński Kamil , Bogdanowicz Wiesław
Published: October 2024

The casein gene cluster spans 250 to 350 kb across mammalian species and is flanked by non-coding DNA with largely unknown functions. These regions likely harbor elements regulating the expression of the 4 casein genes. In Bovidae, this cluster is well studied in domestic cattle and to a lesser extent in zebu and water buffalo. This study used a cattle-specific SNP microarray to analyze 12 Bovidae taxa and estimate casein gene cluster variability across 5 bovid subfamilies. Genotyping identified 126 SNPs covering the entire casein gene cluster and 2 Mb of upstream and downstream regions. Dairy cattle, watusi, and zebu showed the highest polymorphism: 63.7–68.2% in the 5′-upstream region, 35.6–40.0% in the casein cluster, and 40.4–89.4% in the 3′-downstream region. Among wild bovids, only a ‘semi-aquatic’ lechwe revealed high polymorphism similar to cattle. Other species exhibited lower variability, ranging from 9.1–27.3% in the 5′-upstream, 8.9–20.0% in the casein, and 4.2–10.6% in the 3′-downstream regions. For the first time, genome variability data were obtained for impala, waterbuck, and lechwe. It appears that higher variability in cattle’s casein gene cluster may relate to its intense expression. This study confirms the effectiveness of cattle-derived microarrays for genotyping Bovidae.
Intestinal Tissue, Digestive Enzyme, and Antioxidant Enzyme Activities in the Early Development Stage of Endangered Brachymystax tsinlingensis
Authors: Song Rongqun , Wang Zhenlu , Lin Shaoqing , Guo Xingchen , Wang Yizhou , Zhang Lin , Ye Huan , Shao Jian
Published: October 2024

This work explores the digestive system characteristics of Brachymystax tsinlingensis during early developmental stages and aims to solve the problem of high lethality of fry during the transgression period, which is crucial for the artificial propagation and population conservation of endangered fishes. This study was carried out on intestinal tissue, digestive enzymes, and antioxidant enzyme activities in the early development stage of Brachymystax tsinlingensis. Ten random samples during endogenous nutrition (7, 10, and 11 days after hatching), mixed nutrition (13 and 19 DAH), and exogenous nutrition (31, 33, 39, 45, and 73 DAH) were collected by histological and biochemical analysis methods. The results showed that the intestine of Brachymystax tsinlingensis already has four layers initially at 7 DAH, and the intestinal gland tissue is evident at 73 DAH. The contents of total protein (TP) and the activities of lipase (LPS) and trypsin (TPS) were maximal at 39 DAH, and the activities were 3.20 ± 0.26 mg/mL, 2.52 ± 0.69 U/g, and 2717.45 ± 295.26 U/mg, respectively. Catalase (CAT) and glutathione peroxidase (GSH-PX) activities both showed the lowest values at 39 DAH, which were 0.57 ± 0.11 U/mg and 3.35 ± 0.94 U/mg, respectively. The activity of amylase (AMS) and the content of malonaldehyde (MDA) increased, and the highest values were reached at 45 DAH (1.32 ± 0.41 U/mg) and 73 DAH (1.29 ± 0.43 nmoL/mg), respectively. Superoxide dismutase (SOD) and GSH-PX activities both showed a peak value at 7 DAH (126.58 ± 20.13 U/mg and 6.47 ± 1.86 U/mg). Overall, the changes in intestinal tissue, digestive enzymes, and antioxidant enzyme activities at 39 DAH of Brachymystax tsinlingensis are inseparable from different vegetative stages during the developmental period, and these results can provide a reference for the proliferation and cultivation of Brachymystax tsinlingensis resources.
Effects of Dietary Net Energy Concentration on Reproductive Performance, Immune Function, Milk Composition, and Gut Microbiota in Primiparous Lactating Sows
Authors: Gu Fang , Hou Lei , Gao Kaiguo , Wen Xiaolu , Mi Shuyun , Qin Guoxi , Huang Lijun , Wu Qiwen , Yang Xuefen , Wang Li , Jiang Zongyong , Xiao Hao
Published: October 2024

This study aimed to determine the optimal dietary net energy concentration for the reproductive performance, immune function, milk composition, and gut microbiota of primiparous sows during lactation. Forty primiparous lactating sows (Landrace × Yorkshire) with similar body backfat thicknesses were randomly allocated into five treatment groups and fed diets with different dietary net energy concentrations of 10.05 MJ/kg, 10.47 MJ/kg, 10.89 MJ/kg, 11.30 MJ/kg, and 11.72 MJ/kg. The results showed that there were no differences in the performance of piglets, while there was a decrease in the daily feed intake of sows (p = 0.079, linear) as dietary net energy concentration increased. With the increasing dietary net energy concentration, the plasma insulin levels of sows increased (p < 0.01, linear), the plasma glucose levels tended to increase (p = 0.074, linear), and the blood urea nitrogen levels tended to decrease (p = 0.063, linear). Moreover, the plasma total superoxide dismutase activity of sows increased (p < 0.05, quadratic) and the plasma malondialdehyde content of sows decreased (p < 0.05, quadratic) by increasing the dietary net energy concentration. Interestingly, with the increase in dietary net energy concentration, the plasma immunoglobulin M content of sows increased, the milk immunoglobulin M, immunoglobulin G, immunoglobulin A and the percentage of milk fat increased (p < 0.05, linear), and the milk secretory immunoglobulin A content also increased (p < 0.05, linear and quadratic). The milk immunoglobulins and milk fat content of sows fed with net energy concentration of 11.72 MJ/kg were highest. Moreover, there were significant differences in the α-diversity, β-diversity, and relative abundance of gut microbiota in sows fed with different dietary net energy concentrations. At the phylum level, Spirochaetota and Bacteroidota in the gut microbiota of sows were mainly affected by increasing the dietary net energy concentration. Furthermore, the correlation analysis showed that milk immunoglobulin content had a significant negative correlation with the relative abundance of Bacteroidota, and plasma malondialdehyde content also had a significant negative correlation with the relative abundance of Spirochaetota. In summary, these results suggest that increasing the dietary net energy concentration to 11.72 MJ/kg can increase immunological substances in milk, improve milk quality, and alter the composition of gut microbiota in primiparous lactating sows.
Microplastic-Enhanced Cadmium Toxicity: A Growing Threat to the Sea Grape, Caulerpa lentillifera
Authors: Zhou Weilong , Zheng Haolong , Wu Yingyin , Lin Junyi , Ma Xiaofei , Xing Yixuan , Ou Huilong , Vasquez Hebert Ely , Zheng Xing , Yu Feng , Gu Zhifeng
Published: October 2024

The escalating impact of human activities has led to the accumulation of microplastics (MPs) and heavy metals in marine environments, posing serious threats to marine ecosystems. As essential components of oceanic ecosystems, large seaweeds such as Caulerpa lentillifera play a crucial role in maintaining ecological balance. This study investigated the effects of MPs and cadmium (Cd) on the growth, physiology, biochemistry, and Cd accumulation in C. lentillifera while elucidating the underlying molecular regulatory mechanisms. The results demonstrated that exposure to MPs alone significantly promoted the growth. In contrast, exposure to Cd either alone or in combination with MPs significantly suppressed growth by reducing stem and stolon length, bud count, weight gain, and specific growth rates. Combined exposure to MPs and Cd exhibited the most pronounced inhibitory effect on growth. MPs had negligible impact while Cd exposure either alone or combined with MPs impaired antioxidant defenses and exacerbated oxidative damage; with combined exposure being the most detrimental. Analysis of Cd content revealed that MPs significantly increased Cd accumulation in algae intensifying its toxic effects. Gene expression analysis revealed that Cd exposure down-regulated key genes involved in photosynthesis, impairing both photosynthetic efficiency and energy conversion. The combined exposure of MPs and Cd further exacerbated these effects. In contrast, MPs alone activated the ribosome pathway, supporting ribosomal stability and protein synthesis. Additionally, both Cd exposure alone or in combination with MPs significantly reduced chlorophyll B and soluble sugar content, negatively impacting photosynthesis and nutrient accumulation. In summary, low concentrations of MPs promoted C. lentillifera growth, but the presence of Cd hindered it by disrupting photosynthesis and antioxidant mechanisms. Furthermore, the coexistence of MPs intensified the toxic effects of Cd. These findings enhance our understanding of how both MPs and Cd impact large seaweed ecosystems and provide crucial insights for assessing their ecological risks.
Modulation of NRF2/KEAP1 Signaling by Phytotherapeutics in Periodontitis
Authors: Tossetta Giovanni , Fantone Sonia , Togni Lucrezia , Santarelli Andrea , Olivieri Fabiola , Marzioni Daniela , Rippo Maria Rita
Published: October 2024

Periodontitis affects up to 40% of adults over 60 years old and is a consequence of gingivitis. Periodontitis is characterized by a chronic inflammation, periodontal damage, and alveolar bone resorption. The nuclear factor erythroid 2-related factor 2 (NFE2L2 or NRF2)/Kelch-like ECH-Associated Protein 1 (KEAP1) (NRF2/KEAP1) signaling pathway plays a key role in periodontitis by modulating redox balance and inflammation of the periodontium. However, NRF2 expression is decreased in gingival tissues of patients with periodontitis while oxidative stress is significantly increased in this pathology. Oxidative stress and lipopolysaccharide (LPS) produced by gram-negative bacteria favor the production of inflammatory causing periodontal inflammation and favoring alveolar bone. In this review, we analyzed the current literature regarding the role of natural and synthetic compounds in modulating the NRF2/KEAP1 pathway in in vitro and in vivo models of periodontitis in order to evaluate new potential treatments of periodontitis that can improve the outcome of this disease.