bluuebunny/crossref_metadata_2025 huggingface dataset:
Consistency of spatial ability performance in children, adolescents, and young adults
Authors: Morawietz Christina , Dumalski Nils , Wissmann Anna Maria , Wecking Jonas , Muehlbauer Thomas
Published: February 2024

Background

Spatial abilities are essential cognitive skills for many aspects of our everyday life that develop substantially throughout childhood and adolescence. While there are numerous measurement tools to evaluate these abilities, many of them have been designed for specific age groups hampering comparability throughout development. Thus, we determined test–retest-reliability and minimal detectable change for a set of tests that evaluate spatial ability performance in their variety in youth and compared them to young adults.

Methods

Children (age: 11.4 ± 0.5 years, n = 26), adolescents (age: 12.5 ± 0.7 years, n = 22), and young adults (age: 26.1 ± 4.0 years, n = 26) performed a set of five spatial ability tests twice, 20 min apart: Paper Folding Test (PFT), Mental Rotation Test (MRT), Water Level Task (WLT), Corsi Block Test (CBT), and Numbered Cones Run (NCR). Relative and absolute test–retest reliability was determined by calculating the intraclass correlation coefficient (ICC3,1) and the standard error of measurement (SEM), respectively. Further, the minimal detectable change (MDC95%) was calculated to identify clinically relevant changes between repeated measurements.

Results

Irrespective of test, reliability was “excellent” (i.e., ICC3,1 ≥ 0.75) in all age cohorts and the SEM values were rather small. The MDC95% values needed to identify relevant changes in repeated measurements of spatial ability performance ranged between 0.8 and 13.9% in children, 1.1 and 24.5% in adolescents, and 0.7 and 20.8% in young adults.

Conclusion

The determined values indicate that the investigated set of tests is reliable to detect spatial ability performance in healthy children, adolescents, and young adults.
Policy measures and instruments used in European countries to increase biosimilar uptake: a systematic review
Authors: Machado Sara , Cruz Agostinho , Ferreira Pedro Lopes , Morais Carminda , Pimenta Rui Esteves
Published: February 2024

Introduction

While biosimilar medicines can contribute to the sustainability of healthcare systems, their utilization rate varies across European countries. This study aims to identify and systematize policy measures and instruments used in European countries to increase biosimilar market share.

Methods

A systematic review was conducted according to PRISMA 2020 recommendations. Medline-PubMed, Web of Science and ScienceDirect databases were searched using inclusion criteria that required full articles published in English between January 2006 and November 2023. Reviews, letters, reports, editorials and comments or opinion articles were excluded from this study.

Results

Of the 1,137 articles, only 13 met the eligibility criteria for analysis, which covered a total of 28 European countries. Pricing regulation measures were found in 27 of these countries with tendering, price-linkage and internal reference price being the most used. Tendering was used by 27 countries to procure biosimilars in inpatient setting. Prescribing guidelines and recommendations were the widely used instrument. Some European countries adopted physician incentives, quotas, and prescription by international non-proprietary name.

Conclusion

Automatic substitution was not commonly recommended or applied. Interchangeability and switching will become increasingly relevant issues. It is important that the positive results from some countries serve as an example for the future of these medicines in the European market.

Systematic review registration

https://inplasy.com/, Identifier INPLASY2023120032.
Ecological comparison of six countries in two waves of COVID-19
Authors: Liu Meiheng , Shi Leiyu , Yang Manfei , Jiao Jun , Yang Junyan , Ma Mengyuan , Xie Wanzhen , Sun Gang
Published: February 2024

Objective

The purpose of this study is to provide experience and evidence support for countries to deal with similar public health emergencies such as COVID-19 by comparing and analyzing the measures taken by six countries in epidemic prevention and control.

Methods

This study extracted public data on COVID-19 from the official website of various countries and used ecological comparative research methods to compare the specific situation of indicators such as daily tests per thousand people, stringency index, and total vaccinations per hundred people in countries.

Results

The cumulative death toll in China, Germany and Australia was significantly lower than that in the United States, South Africa and Italy. Expanding the scale of testing has helped control the spread of the epidemic to some extent. When the epidemic situation is severe, the stringency index increases, and when the epidemic situation tends to ease, the stringency index decreases. Increased vaccination rates, while helping to build an immune barrier, still need to be used in conjunction with non-drug interventions.

Conclusion

The implementation of non-drug interventions and vaccine measures greatly affected the epidemic prevention and control effect. In responding to public health emergencies such as the COVID-19 epidemic, countries should draw on international experience, closely align with their national conditions, follow the laws of epidemiology, actively take non-drug intervention measures, and vigorously promote vaccine research and development and vaccination.
Premature aging in genetic diseases: what conclusions can be drawn for physiological aging
Authors: Milosic Filip , Hengstschläger Markus , Osmanagic-Myers Selma
Published: February 2024

According to current views the major hallmarks of physiological aging may be subdivided into three categories, primary causes of cellular damage (genomic instability, telomere attrition, loss of proteostasis, epigenetic alterations and compromised macroautophagy), antagonistic hallmarks that represent response to damage (deregulated nutrient sensing, cellular senescence, mitochondrial dysfunction) and integrative hallmarks that represent culprits of the phenotype (stem cell exhaustion, altered intercellular communication, chronic inflammation, dysbiosis). In contrast to physiological aging, premature aging diseases are driven by one or two distinct primary causes of aging, such as genomic instability in the case of Werner syndrome (WS), each displaying other hallmarks of aging to a variable extent. In this review we will focus on primary causes of well-investigated premature aging diseases Hutchinson-Gilford progeria syndrome (HGPS), WS, and Cockayne syndrome (CS) and for each provide an overview of reported aging hallmarks to elucidate resemblance to physiological aging on the mechanistic level and in the context of characteristic age-related diseases. Ubiquitous and tissue specific animal models of premature aging diseases will be discussed as useful tools to decipher fundamental aging-related mechanisms and develop intervention strategies to combat premature aging and age-related diseases.
Enhancing food safety and cultivated meat production: exploring the impact of microplastics on fish muscle cell proliferation and differentiation
Authors: Sun Taozhu , Timoneda Alfonso , Banavar Amiti , Ovissipour Reza
Published: February 2024

Cultivated meat, a sustainable alternative to traditional livestock farming, has gained attention for its potential environmental and health benefits. However, concerns about microplastic contamination pose challenges, especially when sourcing cells from marine organisms prone to microplastic bioaccumulation. Additionally, the pervasive presence of microplastics in laboratory settings, ingredients, and during the production, increases the risk of unintentional contamination. This study focused on Atlantic mackerel (Scomber scombrus) skeletal muscle cell lines to examine the effects of microplastic exposure, represented by fluorescent polyethylene microspheres (10–45 µm) on cell performance including cell proliferation, cell viability, gene expression, and differentiation processes critical for cultivated meat production. The results revealed significant impacts on cell attachment and proliferation at microplastic concentrations of 1 μg/mL, 10 μg/mL, and 50 μg/mL. Notably, the 10 μg/mL concentration exerted the most pronounced effects on cell viability during both attachment and proliferation phases. While the results indicated that both microplastic concentration and size influence cell viability, cell differentiation remained unaffected, and additional contributing factors require further investigation. These findings underscore the necessity of thoroughly exploring microplastic-cell interactions to ensure food safety and safeguard health within the burgeoning cultivated meat industry.
Distributed agency in HRI—an exploratory study of a narrative robot design
Authors: Graf Philipp , Zarp-Falden Christian Sønderskov , Naik Lakshadeep , Lefeuvre Kevin Bruno , Marchetti Emanuela , Hornecker Eva , Sørensen Mads Bergholdt , Hemmingsen Laurits Valberg , Just Christensen Ebbe Vincent , Bodenhagen Leon , Krüger Norbert , Bischof Andreas
Published: February 2024

We explore an alternative approach to the design of robots that deviates from the common envisionment of having one unified agent. What if robots are depicted as an agentic ensemble where agency is distributed over different components? In the project presented here, we investigate the potential contributions of this approach to creating entertaining and joyful human-robot interaction (HRI), which also remains comprehensible to human observers. We built a service robot—which takes care of plants as a Plant-Watering Robot (PWR)—that appears as a small ship controlled by a robotic captain accompanied by kinetic elements. The goal of this narrative design, which utilizes a distributed agency approach, is to make the robot entertaining to watch and foster its acceptance. We discuss the robot’s design rationale and present observations from an exploratory study in two contrastive settings, on a university campus and in a care home for people with dementia, using a qualitative video-based approach for analysis. Our observations indicate that such a design has potential regarding the attraction, acceptance, and joyfulness it can evoke. We discuss aspects of this design approach regarding the field of elderly care, limitations of our study, and identify potential fields of use and further scopes for studies.
Comparative pathogenicity of CA1737/04 and Mass infectious bronchitis virus genotypes in laying chickens
Authors: Ali Ahmed , Farooq Muhammad , Altakrouni Danah , Najimudeen Shahnas M. , Hassan Mohamed S. H. , Isham Ishara M. , Shalaby Adel A. , Gallardo Rodrigo A. , Abdul-Careem Mohamed Faizal
Published: February 2024

Infectious bronchitis virus (IBV) is a respiratory virus causing atropism in multiple body systems of chickens. Recently, the California 1737/04 (CA1737/04) IBV strain was identified as one of the circulating IBV variants among poultry operations in North America. Here, the pathogenicity and tissue tropism of CA1737/04 IBV strain in specific-pathogen-free (SPF) hens were characterized in comparison to Massachusetts (Mass) IBV. In 30 weeks-old SPF hens, Mass or CA1737/04 IBV infections were carried out, while the third group was maintained as a control group. Following infection, we evaluated clinical signs, egg production, viral shedding, serology, necropsy examination, and histopathology during a period of 19 days. Also, certain tissue affinity parameters were investigated, which involved the localization of viral antigens and the detection of viral RNA copies in designated tissues. Our findings indicate that infection with CA1737/04 or Mass IBV strain could induce significant clinical signs, reduced egg production, and anti-IBV antibodies locally in oviduct wash and systemically in serum. Both IBV strains showed detectable levels of viral RNA copies and induced pathology in respiratory, renal, enteric, and reproductive tissues. However, the CA1737/04 IBV strain had higher pathogenicity, higher tissue tropism, and higher replication in the kidney, large intestine, and different segments of the oviduct compared to the Mass IBV strain. Both IBV strains shed viral genome from the cloacal route, however, the Mass IBV infected hens shed higher IBV genome loads via the oropharyngeal route compared to CA1737/04 IBV-infected hens. Overall, the current findings could contribute to a better understanding of CA1737/04 IBV pathogenicity in laying hens.
Deep Domain Adaptation with Correlation Alignment and Supervised Contrastive Learning for Intelligent Fault Diagnosis in Bearings and Gears of Rotating Machinery
Authors: Zhang Bo , Dong Hai , Qaid Hamzah A. A. M. , Wang Yong
Published: February 2024

Deep domain adaptation techniques have recently been the subject of much research in machinery fault diagnosis. However, most of the work has been focused on domain alignment, aiming to learn cross-domain features by bridging the gap between source and target domains. Despite the success of these methods in achieving domain alignment, they often overlook the class discrepancy present in cross-domain scenarios. This can result in the misclassification of target domain samples that are located near cluster boundaries or far from their associated class centers. To tackle these challenges, a novel approach called deep domain adaptation with correlation alignment and supervised contrastive learning (DCASCL) is proposed, which synchronously realizes both domain distribution alignment and class distribution alignment. Specifically, the correlation alignment loss is used to enforce the model to generate transferable features, facilitating effective domain distribution alignment. Additionally, classifier discrepancy loss and supervised contrastive learning loss are integrated to carry out feature distribution alignment class-wisely. The supervised contrastive learning loss leverages class-specific information of source and target samples, which efficiently promotes the compactness of samples of the same class and the separation of samples from different classes. Moreover, our approach is extensively validated across three diverse datasets, demonstrating its effectiveness in diagnosing machinery faults across different domains.
Magnetic Performance of Eddy Current Suppressing Structures in Additive Manufacturing
Authors: Klein Carsten , May Christopher , Nienhaus Matthias
Published: February 2024

Additively manufactured soft-magnetic components are inherently bulky leading to significant eddy current losses when applied to electrical machines. Prior works have addressed this issue by implementing structures based on the Hilbert space-filling curve which include eddy current suppressing gaps, thereby reducing the fill factor of the soft-magnetic component. The present research aims at investigating a number of space-filling curves in addition to sheets in order to find the optimal eddy current suppressing structure from an electromagnetic point of view. By means of both analysis and finite-element simulation, it was shown that sheets are superior at minimizing eddy current losses while space-filling curves excel at maximizing the fill factor.
A Microchannel Device for Droplet Classification by Manipulation Using Piezoelectric Vibrator
Authors: Fujioka Ao , Seo Shoko , Kanda Takefumi , Wakimoto Shuichi , Yamaguchi Daisuke
Published: February 2024

Emulsion formulations should be monodispersed in terms of their stability. Therefore, there is a need for a device that can classify droplets of the desired size from polydispersed emulsions in a fluidized bed manufacturing system. In the previous study, we evaluated the fabrication of a droplet manipulation device using acoustic radiation forces through simulation using the finite element method. In this study, particle manipulation experiments using 1, 6, and 10 µm polystyrene particles were first estimated and evaluated in comparison with their theoretical particle behavior. Based on the results we obtained, the driving conditions and droplet behavior were derived, and the droplet manipulation device using ultrasonic waves to shrink monodisperse emulsions was evaluated. As a result, the droplet classification effect in the microchannel was confirmed to be consistent with the droplet behavior prediction, and the microchannel structure with a constriction component improved its classification effect.
A Hybrid Forecasting Model for Self-Similar Traffic in LEO Mega-Constellation Networks
Authors: Han Chi , Xiong Wei , Yu Ronghuan
Published: February 2024

Mega-constellation network traffic forecasting provides key information for routing and resource allocation, which is of great significance to the performance of satellite networks. However, due to the self-similarity and long-range dependence (LRD) of mega-constellation network traffic, traditional linear/non-linear forecasting models cannot achieve sufficient forecasting accuracy. In order to resolve this problem, a mega-constellation network traffic forecasting model based on EMD (empirical mode decomposition)-ARIMA (autoregressive integrated moving average) and IGWO (improved grey wolf optimizer) optimized BPNN (back-propagation neural network) is proposed in this paper, which makes comprehensive utilization of linear model ARIMA, non-linear model BPNN and optimization algorithm IGWO. With the enhancement of the global optimization capability of a BPNN, the proposed hybrid model can fully realize the potential of mining linear and non-linear laws of mega-constellation network traffic, hence improving the forecasting accuracy. This paper utilizes an ON/OFF model to generate historical self-similar traffic to forecast. RMSE (root mean square error), MAE (mean absolute error), R-square and MAPE (mean absolute percentage error) are adopted as evaluation indexes for the forecasting effect. Comprehensive experimental results show that the proposed method outperforms traditional constellation network traffic forecasting schemes, with several improvements in forecasting accuracy and efficiency.
Effect of Warm-Dry Storage and Supplemental Application of Gibberellins on the Lipid Profile of Chincuya Seeds (Annona purpurea Moc. & Sessé ex Dunal)
Authors: Vidal-Lezama Eloísa , Reyes-Trejo Benito , Villegas-Monter Ángel , Vaquera-Huerta Humberto , Robledo-Paz Alejandrina , Martínez-Palacios Alejandro , Ferreira Gisela
Published: February 2024

Despite ample knowledge of the effect of warm-dry storage on breaking dormancy in chincuya (Annona purpurea Moc. & Sessé ex Dunal) seeds, this paper investigates an important new aspect of this process—the applicability of seed treatment with gibberellic acid and its influence on seed viability and fatty acid profile. Chincuya is an underutilized, tropical wild species native to Mexico, with potential as a biopesticide. The impact of warm-dry storage and gibberellic acid treatment on seed viability and germination was determined to improve that knowledge further. Also, the content and kinetics of fatty acids in chincuya seeds were profiled during warm-dry storage. Seed treatments included storage time (0, 3, 6, 9, and 12 months), seed imbibition for 72 h in gibberellic acid at 350 mg L−1, and distilled water imbibition for 72 h for the control treatment. Seed viability was determined using the TTZ classic test. Imbibed seeds were germinated on paper towels and incubated at 30 °C during the day and 25 °C at night in a 12:12 h dark/light photoperiod. The lipid profile was obtained by gas chromatography. During the storage treatment, seeds stayed in darkness at 25 ± 3 °C. Results showed that high viability remained up to month 9 in storage when it significantly decreased. Freshly harvested seeds germinated at a statistically significantly lower rate (26.1%) than six-month-old seeds (65.6%). The profile of fatty acids breaks down as palmitic acid (33.41%), stearic acid (7.72%), and arachidic acid (1.30%), for a total of 42.44% of saturated fatty acids. The detected unsaturated fatty acids (52.15%) were palmitoleic acid (1.52%), oleic acid (43.37%), and linoleic acid (7.24%). No significant changes were detected in fatty acid content; however, the highest fatty acid content (92.84%) occurred with the highest germination rate. Regression analysis showed significant content changes: palmitoleic and palmitic acids increased while oleic acid decreased during dry storage. Arachidic acid showed a slight downward trend. Also, fatty acid content significantly differed between intact seeds (unstored and unincubated) and latent seeds (unstored, incubated, and ungerminated). The total fatty acids content for latent seeds was significantly lower. These results show that Annona purpurea seeds present morphophysiological dormancy. Also, we document the highest germination rate reported (65.6%) and report the presence of arachidic and palmitoleic acids in chincuya seeds.
A Two-Stage Approach to the Study of Potato Disease Severity Classification
Authors: Xu Yanlei , Gao Zhiyuan , Wang Jingli , Zhou Yang , Li Jian , Meng Xianzhang
Published: February 2024

Early blight and late blight are two of the most prevalent and severe diseases affecting potato crops. Efficient and accurate grading of their severity is crucial for effective disease management. However, existing grading methods are limited to assessing the severity of each disease independently, often resulting in low recognition accuracy and slow grading processes. To address these challenges, this study proposes a novel two-stage approach for the rapid severity grading of both early blight and late blight in potato plants. In this research, two lightweight models were developed: Coformer and SegCoformer. In the initial stage, Coformer efficiently categorizes potato leaves into three classes: those afflicted by early blight, those afflicted by late blight, and healthy leaves. In the subsequent stage, SegCoformer accurately segments leaves, lesions, and backgrounds within the images obtained from the first stage. Furthermore, it assigns severity labels to the identified leaf lesions. To validate the accuracy and processing speed of the proposed methods, we conduct experimental comparisons. The experimental results indicate that Coformer achieves a classification accuracy as high as 97.86%, while SegCoformer achieves an mIoU of 88.50% for semantic segmentation. The combined accuracy of this method reaches 84%, outperforming the Sit + Unet_V accuracy by 1%. Notably, this approach achieves heightened accuracy while maintaining a faster processing speed, completing image processing in just 258.26 ms. This research methodology effectively enhances agricultural production efficiency.
Change in the Physiological Aspects of Soybean Caused by Infestation by Bemisia tabaci MEAM1
Authors: Silva Luciana B. , Almeida Lucas C. , e Silva Maria C. F. , Brito Ramilos R. de , Miranda Rafael de S. , Rodrigues Raimundo H. F. , Santos Carlos M. P. dos , Ribeiro Gilvana da S. , Morais João V. S. , Silva Alisson F. T. da , Mayard Hernesise , Oliveira Thayline Rodrigues de , Costa Lima Vânia Maria Gomes da , Silva Fontes Lucia da , Rocha Neurandir Sobrinho da , Jesus Lacerda Julian de , Pavan Bruno Ettore
Published: February 2024

Whiteflies cause significant crop losses through direct sap feeding, inducing plant physiological disorders and promoting the growth of sooty mold. Moreover, whiteflies can indirectly harm plants by transmitting plant viruses, particularly begomoviruses and criniviruses, resulting in severe viral disease epidemics. This study aimed to evaluate the physiological characteristics of susceptible and resistant soybean cultivars to B. tabaci. The experiments were conducted in a greenhouse. Eleven soybean cultivars were selected and infested with 100 adults of B. tabaci at the V3 stage. The evaluation of photosynthetic parameters, such as photosynthetic rate, leaf transpiration, stomatal conductance, and internal CO2 concentration, revealed that B. tabaci infestation influenced gas exchange in soybean plants. The photosynthetic rate was higher in cultivars AS3810 and M8349 during the V6 stage. Infestations caused alterations in photosynthetic parameters, suggesting increased energy demand to maintain photosynthetic activity. However, the response to infestation varied among the different cultivars, indicating varying levels of resistance and tolerance to the whitefly’s damage. Furthermore, the infestation had a more notable impact during the vegetative phenological stage. In summary, infestation by B. tabaci has a discernible impact on the physiology of soybean plants, resulting in alterations in gas exchange parameters and water use efficiency. The reaction to infestation exhibited variations among different soybean cultivars, indicating potential differences in resistance to the pest. This study underscores the significance of assessing the physiological consequences of whitefly infestations on soybean crops.
Typology for Decision Support Systems in Integrated Pest Management and Its Implementation as a Web Application
Authors: Marinko Jurij , Blažica Bojan , Jørgensen Lise Nistrup , Matzen Niels , Ramsden Mark , Debeljak Marko
Published: February 2024

Decision support systems (DSSs) enable the optimisation of pesticide application timing to increase pesticide efficacy and thus reduce pesticide use without compromising yield quality and quantity. Limited access to information about available DSSs for use in integrated pest management (IPM) is a major barrier to the uptake of DSSs for IPM across Europe. To overcome this barrier, a typology for DSSs for IPM in Europe was developed, introducing a systematic approach to describe the ever-growing number of DSSs for IPM. The developed IPM-DSS typology was implemented in the free web tool “IPM Adviser”, where currently 79 IPM DSSs are described with over 50 attributes describing their structural and performance characteristics. The information about IPM DSSs, which was previously scattered on different websites and difficult to compare, is now standardised and presented in a uniform way, so that it is possible to compare different IPM DSSs on the basis of all the attributes described. The presented IPM-DSS typology implemented in the web tool IPM Adviser facilitates the dissemination and uptake of DSSs for IPM and thus contributes to the achievement of the EU targets for the sustainable use of pesticides.
Genome-Wide Association Analysis of Cowpea Mild Mottle Virus Resistance in Soybean Germplasms from Northeast China
Authors: Luan Yameng , Yang Siqi , Wang Yuting , Zhao Yu , Wu Xiaoyun , Chen Qingshan , Qi Zhaoming , Wu Xiaoxia , Ji Weiqin , Cheng Xiaofei
Published: February 2024

Cowpea mild mottle virus (CpMMV) is an important viral pathogen that seriously influences the yield and seed quality of soybeans worldwide. Resistance breeding is one of the most effective, economical, and environmentally safe strategies for controlling the disease caused by CpMMV. However, only few resistance genes have been identified in soybeans. In this study, the resistance of 169 soybean germplasms from Northeast China to a CpMMV strain isolated from soybean in China was evaluated, and a genome-wide association study (GWAS) was then performed to find possible resistance genes in these soybean germplasms. Nine resistant soybean germplasms were identified and two single nucleotide polymorphism sites (SNPs) were found to be closely associated with CpMMV resistance. A total number of 51 and 25 candidate genes neighboring the resistance-associated SNPs on chromosomes 6 and 12, respectively, were identified, among which one receptor-like kinase (RLK) on chromosome 6 and 2 toll-interleukin-1 receptor nucleotide-binding leucine-rich repeat receptors (TNLs) on chromosome 12 were recognized as the most probable resistance genes, respectively. Together, these data provide new insights on the resistance resources of soybeans to CpMMV, which will benefit the breeding of CpMMV-resistant soybean cultivars.
Prediction of Specific Fuel Consumption of a Tractor during the Tillage Process Using an Artificial Neural Network Method
Authors: Al-Sager Saleh M. , Almady Saad S. , Marey Samy A. , Al-Hamed Saad A. , Aboukarima Abdulwahed M.
Published: February 2024

In mechanized agricultural activities, fuel is particularly important for tillage operations. In this study, the impact of seven distinct parameters on fuel usage per unit of draft power was examined. The parameters are tractor power, soil texture index, plowing speed, plowing depth, width of implement, and both initial soil moisture content and soil bulk density. This study investigated the construction of an artificial neural network (ANN) model for tractor-specific fuel consumption predictions for two tillage implements: chisel and moldboard plows. The ANN model was created based on the collection of related data from previous research studies, and the validation was performed using actual field experiments in clay soil using a chisel plow. The developed ANN model (9-22-1) was confirmed by graphical assessment; additionally, the root-mean-square error (RMSE) was computed. Based on the RMSE, the results demonstrated a good agreement for specific fuel consumption per draft power between the observed and predicted values, with corresponding RMSE values of 0.08 L/kWh and 0.075 L/kWh for the training and testing datasets, respectively. The novelty of the work presented in this paper is that, for the first time, a farm machinery manager can optimize tractor fuel consumption per draft power by carefully controlling certain parameters, such as initial soil moisture content, tractor power, plowing speed, implement width, and depth of plowing. The results show that the input parameters make a significant contribution to the output over the used data with different percentages. Accordingly, the contribution analysis showed that the implement width had a high impact on tractor-specific fuel consumption for both plows at 30.13%; additionally, the chisel and moldboard plows contributed 4.19% and 4.25% in predicting tractor fuel consumption per draft power. This study concluded that practical useful advice for agricultural production can be achieved through optimizing fuel consumption rate by selecting the proper levels of affecting parameters to reduce fuel costs. Moreover, an ANN model could be used to develop future tractor fuel-planning schemes for tillage operations.
Plant Disease Diagnosis Based on Hyperspectral Sensing: Comparative Analysis of Parametric Spectral Vegetation Indices and Nonparametric Gaussian Process Classification Approaches
Authors: Reis Pereira Mafalda , Verrelst Jochem , Tosin Renan , Rivera Caicedo Juan Pablo , Tavares Fernando , Neves dos Santos Filipe , Cunha Mário
Published: February 2024

Early and accurate disease diagnosis is pivotal for effective phytosanitary management strategies in agriculture. Hyperspectral sensing has emerged as a promising tool for early disease detection, yet challenges remain in effectively harnessing its potential. This study compares parametric spectral Vegetation Indices (VIs) and a nonparametric Gaussian Process Classification based on an Automated Spectral Band Analysis Tool (GPC-BAT) for diagnosing plant bacterial diseases using hyperspectral data. The study conducted experiments on tomato plants in controlled conditions and kiwi plants in field settings to assess the performance of VIs and GPC-BAT. In the tomato experiment, the modeling processes were applied to classify the spectral data measured on the healthy class of plants (sprayed with water only) and discriminate them from the data captured on plants inoculated with the two bacterial suspensions (108 CFU mL−1). In the kiwi experiment, the standard modeling results of the spectral data collected on nonsymptomatic plants were compared to the ones obtained using symptomatic plants’ spectral data. VIs, known for their simplicity in extracting biophysical information, successfully distinguished healthy and diseased tissues in both plant species. The overall accuracy achieved was 63% and 71% for tomato and kiwi, respectively. Limitations were observed, particularly in differentiating specific disease infections accurately. On the other hand, GPC-BAT, after feature reduction, showcased enhanced accuracy in identifying healthy and diseased tissues. The overall accuracy ranged from 70% to 75% in the tomato and kiwi case studies. Despite its effectiveness, the model faced challenges in accurately predicting certain disease infections, especially in the early stages. Comparative analysis revealed commonalities and differences in the spectral bands identified by both approaches, with overlaps in critical regions across plant species. Notably, these spectral regions corresponded to the absorption regions of various photosynthetic pigments and structural components affected by bacterial infections in plant leaves. The study underscores the potential of hyperspectral sensing in disease diagnosis and highlights the strengths and limitations of VIs and GPC-BAT. The identified spectral features hold biological significance, suggesting correlations between bacterial infections and alterations in plant pigments and structural components. Future research avenues could focus on refining these approaches for improved accuracy in diagnosing diverse plant–pathogen interactions, thereby aiding disease diagnosis. Specifically, efforts could be directed towards adapting these methodologies for early detection, even before symptom manifestation, to better manage agricultural diseases.
Advancements of UAV and Deep Learning Technologies for Weed Management in Farmland
Authors: Zhang Jinmeng , Yu Feng , Zhang Qian , Wang Ming , Yu Jinying , Tan Yarong
Published: February 2024

With the continuous growth of the global population and the increasing demand for crop yield, enhancing crop productivity has emerged as a crucial research objective on a global scale. Weeds, being one of the primary abiotic factors impacting crop yield, contribute to approximately 13.2% of annual food loss. In recent years, Unmanned Aerial Vehicle (UAV) technology has developed rapidly and its maturity has led to widespread utilization in improving crop productivity and reducing management costs. Concurrently, deep learning technology has become a prominent tool in image recognition. Convolutional Neural Networks (CNNs) has achieved remarkable outcomes in various domains, including agriculture, such as weed detection, pest identification, plant/fruit counting, maturity grading, etc. This study provides an overview of the development of UAV platforms, the classification of UAV platforms and their advantages and disadvantages, as well as the types and characteristics of data collected by common vision sensors used in agriculture, and discusses the application of deep learning technology in weed detection. The manuscript presents current advancements in UAV technology and CNNs in weed management tasks while emphasizing the existing limitations and future trends in its development process to assist researchers working on applying deep learning techniques to weed management.
Common Ragweed—Ambrosia artemisiifolia L.: A Review with Special Regards to the Latest Results in Biology and Ecology
Authors: Knolmajer Bence , Jócsák Ildikó , Taller János , Keszthelyi Sándor , Kazinczi Gabriella
Published: February 2024

Weeds are responsible for a significant proportion of agricultural production losses. Common ragweed (Ambrosia artemisiifolia L.) has become the dominant weed in much of the northern hemisphere over the last century and is projected to further expand northward with climate warming. Not only does it cause damage to agriculture, but it also poses a significant human health risk. With the increasing number of Ambrosia artemisiifolia, around 44 million more people will suffer from ragweed pollen-induced pollinosis in the future just in Europe. The following review provides an overview of the most important and recent research findings on the spread, morphology, life cycle, importance and damage, allelopathic effects, habitat and environmental requirements of common ragweed. These characteristics of the species may explain its success and, based on this knowledge, allow the development of methods for its control.
Exploring the Impact of Endophytic Fungus Aspergillus cejpii DMKU-R3G3 on Rice: Plant Growth Promotion and Molecular Insights through Proteomic Analysis
Authors: Leetanasaksakul Kantinan , Roytrakul Sittiruk , Kittisenachai Suthathip , Lohmaneeratana Karan , Jantasuriyarat Chatchawan , Lueangjaroenkit Piyangkun
Published: February 2024

Rice is a crucial crop for many people worldwide, especially in regions like Asia, Latin America, and parts of Africa. Thailand is one of the largest exporters of rice. Nowadays, farmers use chemicals to control rice disease, which can have negative effects on humans and the environment. Therefore, the objective of this study was to examine the plant-promoting capabilities of the endophytic fungal strains DMKU-R3G3 in greenhouse settings. The endophytic fungi strain DMKU-R3G3, which was isolated from organic rice root, was identified as Aspergillus cejpii based on morphological characteristics and phylogenetic analysis. The production of IAA was detected using Salkowski’s reagent. After 7 days of incubation, the finding revealed that the strain cultivated in PDB supplemented with tryptophan yielded a greater concentration of IAA (25.45 μg/mL). The inoculation with A. cejpii DMKU-R3G3 significantly enhanced rice growth, as evidenced by notable increases in shoot height, root length, and fresh weight. Moreover, the chlorophyll content of the rice plants also increased by 1.78 times more than the control group. In addition, proteomic analysis revealed that rice responded toward the colonization of endophytic fungi by producing auxin-responsive proteins to regulate the IAA content in plant tissue and inducing total chlorophyll production due to the up-regulation of proteins in the chlorophyll biosynthesis pathway. The results obtained from this study lead to the conclusion that the A. cejpii strain DMKU-R3G3 possesses the capability to enhance plant growth through the production of phytohormones in greenhouse conditions. Therefore, endophytic A. cejpii DMKU-R3G3 has the potential to be a promising eco-friendly plant growth promoter for sustainable rice cultivation.
Comparative Study of the Convertibility of Pretreated Miscanthus Straw Using Enzyme Preparations Produced by Different Recombinant Strains of Penicillium verruculosum
Authors: Osipov Dmitrii O. , Dotsenko Anna S. , Semenova Margarita V. , Rozhkova Alexandra M. , Sinitsyn Arkady P.
Published: February 2024

Non-edible cellulosic biomass from perennial herbaceous plants is a promising and abundant feedstock for replacing slow-growing woody plants used in biotechnological applications. Herbaceous plant biomass, as other types of plant biomass, requires pretreatment before biochemical conversion. In this study, miscanthus straw was pretreated using different methods and subjected to enzymatic hydrolysis with Penicillium verruculosum enzyme complexes under laboratory conditions. The convertibility after enzymatic hydrolysis varied from 15% to 66%, depending on the pretreatment method. Dilute alkaline pretreatment showed the highest convertibility compared to other methods, reaching up to 66%. The efficiency of dilute acid pretreatment was relatively low compared to other methods. The maximum convertibility was 37% for sulfuric acid pretreatment (the least efficient) and 51% for nitric acid. Convertibility was almost equal with 43% for white liquor and 46% for hot water. The glucose-to-xylose ratio was 4.7:1 for dilute alkaline pretreatment and 11–13:1 for white liquor. Both sulfuric and nitric acid resulted in a low xylose content in the enzymatic hydrolysates. Low-xylose hydrolysates with less than 2% of the glucose amount can be produced by hot water pretreatment. Preparation C, enriched with endoglucanase I from T. reesei and endoglucanase II from P. verruculosum, was found to be the most effective of the different enzyme preparations (EPs) tested.
Exposure to Coxiella burnetii in Wild Lagomorphs in Spanish Mediterranean Ecosystems
Authors: Castro-Scholten Sabrina , Caballero-Gómez Javier , Cano-Terriza David , Jiménez-Martín Débora , Rouco Carlos , Beato-Benítez Adrián , Camacho-Sillero Leonor , García-Bocanegra Ignacio
Published: February 2024

Coxiella burnetii is an important zoonotic pathogen of worldwide distribution that can infect a wide range of wild and domestic species. The European wild rabbit (Oryctolagus cuniculus) can play a role as a reservoir for this bacterium in certain epidemiological scenarios, but, to date, a very limited numbers of large-scale serosurveys have been conducted for this species worldwide. Although exposure in hare species has also been described, C. burnetii in Iberian hare (Lepus granatensis) has never been assessed. Here, we aimed to determine the seroprevalence and risk factors associated with C. burnetii exposure in wild lagomorphs in the Mediterranean ecosystems of southern Spain. Between the 2018/2019 and 2021/2022 hunting seasons, blood samples from 638 wild lagomorphs, including 471 wild rabbits and 167 Iberian hares, were collected from 112 hunting grounds distributed across all eight provinces of Andalusia (southern Spain). The overall apparent individual seroprevalence was 8.9% (57/638; 95% CI: 6.8–11.4). Antibodies against C. burnetii were found in 11.3% (53/471; 95% CI: 8.4–14.1) of the wild rabbits and 2.4% (4/167; 95% CI: 0.1–4.7) of the Iberian hares. Seropositive animals were detected for 16 (14.3%; 95% CI: 7.8–20.8) of the 112 hunting grounds tested and in all the hunting seasons sampled. A generalized estimating equations model showed that the geographical area (western Andalusia) and presence of sheep were risk factors potentially associated with C. burnetii exposure in wild lagomorphs. A statistically significant spatial cluster (p < 0.001) was identified in the south-west of Andalusia. Our results provide evidence of moderate, endemic and heterogeneous circulation of C. burnetii in wild lagomorph populations in Spanish Mediterranean ecosystems. Risk-based strategies for integrative surveillance programs should be implemented in these species to reduce the risk of transmission of the bacterium to sympatric species, including humans.
Influence of a Mixture of Protein Hydrolysate from Black Soldier Fly Larvae and Schizochytrium on Palatability, Plasma Biochemistry, and Antioxidative and Anti-Inflammatory Capacity in Cat Diets
Authors: Li You , Liu Mingkang , Wei Yu , Li Luyang , Ma Deying , Weng Yuxiao , Wang Haifeng , Xu Xiao
Published: February 2024

The objective of this research was to evaluate palatability, plasma biochemistry, antioxidative and anti-inflammatory capacity, and immune levels in cats by feeding supplementing inclusion of different levels of a mixture of protein hydrolysate from black soldier fly larvae and schizochytrium (BSFPs) in diets. In the feed experiment, a total of 24 adult cats (12 females and 12 males; BW: 3.02 ± 0.06 kg) were randomly divided into four groups: (1) diet with chicken and fish meal as primary protein resource (CON); (2) diet with 5% BSFPs replacing chicken meal, fish meal, chicken oil, and fish oil (5% BSFPs); (3) 10% BSFPs; and (4) 15% BSFPs. The body weight and feed intake were recorded, and a blood sample was collected for analysis. In the palatability experiment, three diets containing 5%, 10%, and 15% BSFPs were evaluated by comparing with CON. These results suggested that different levels of BSFPs could improve palatability in cat diets by enhancing the first sniff, the first bite, and feed intake (p < 0.05). However, no significant influence existed in body weight and average daily feed intake (p > 0.05). In comparison to the CON group, 5% and 15% BSFPs significantly increased the total protein content, and all treatment groups decreased the triglyceride content and enhanced the calcium concentration in plasma; in addition, the activity of aspartate aminotransferase and alanine aminotransferase and the content of creatinine and urea nitrogen were significantly reduced by the supplementation inclusion of BSFPs in the diets (p < 0.05). The enzyme activity of glutathione peroxidase was dramatically enhanced by the supplementation of 10% and 15% BSFPs in diets compared with the CON diet, and the activity of superoxide dismutase was increased and the malondialdehyde concentration was remarkably reduced in all three treatments (p < 0.05). Compared with the CON group, different levels of BSFPs in the diets significantly increased the immunoglobulin A content in plasma; similarly, the immunoglobulin G concentration was significantly enhanced by the supplementation of 10% and 15% BSFPs in the diets (p < 0.05). Furthermore, the interleukin-1β content was significantly reduced in the inclusion of 10% and 15% BSFPs in the diets, and 15% BSFPs remarkably decreased the content of interleukin-8 in plasma compared with the CON diet (p < 0.05). To sum up, the supplementation of different levels of BSFPs exhibited a positive effect on palatability and enhanced the antioxidant, anti-inflammatory, and immune capacity. Particularly, the addition levels of 10% and 15% BSFPs were more effective in antioxidation, anti-inflammation, and immunity.
Pollutant Gases to Algal Animal Feed: Impacts of Poultry House Exhaust Air on Amino Acid Profile of Algae
Authors: Uguz Seyit , Sozcu Arda
Published: February 2024

Algae provide a rich source of proteins, lipids, vitamins, and minerals, making them valuable feed ingredients in animal nutrition. Beyond their nutritional benefits, algae have been recognized for their potential to mitigate the negative environmental impacts of poultry production. Poultry production is crucial for the global food supply but contributes to environmental concerns, particularly in terms of ammonia and carbon dioxide gas emissions. This study emphasizes the importance of reducing greenhouse gas and ammonia production in poultry operations by utilizing algae species suitable for animal consumption, highlighting the need for sustainable feed sources. This study investigated the effects of poultry exhaust air and culture conditions on the amino acid profiles of three microalgae species, namely, Scenedesmus sp. (AQUAMEB-60), Ankistrodesmus sp. (AQUAMEB-33), and Synechococcaceae (AQUAMEB 32). The experiments were conducted in a commercial broiler farm in Bursa, Turkey, focusing on reducing pollutant gas emissions and utilizing poultry exhaust air in algae cultivation. The highest protein content of 50.4% was observed in the biomass of Synechococcaceae with BBM and DI water. Scenedesmus sp. had the highest carbohydrate content of 33.4% cultivated with DI water. The algae biomass produced from Synechococcaceae growth with DI water was found to have the highest content of essential and nonessential amino acids, except for glutamic acid and glycine. The arsenic, cadmium, and mercury content showed variations within the following respective ranges: 1.076–3.500 mg/kg, 0.0127–0.1210 mg/kg, and 0.1330–0.0124 mg/kg. The overall operating costs for producing 1.0 g L−1 d−1 of dry algal biomass with the existing PBR system were $0.12–0.35 L−1 d−1, $0.10–0.26 L−1 d−1, and $0.11–0.24 L−1 d−1 for Scenedesmus sp., Ankistrodesmus sp., and Synechococcaceae, respectively. The operating cost of producing 1.0 g L−1 d−1 of protein was in the range of $0.25–0.88 L−1 d−1 for the three algae species. The results provide insights into the potential of algae as a sustainable feed ingredient in animal diets, emphasizing both environmental and economic considerations. The results demonstrated a considerable reduction in the production costs of dry biomass and protein when utilizing poultry house exhaust air, highlighting the economic viability and nutritional benefits of this cultivation method.