bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring time evolution characteristics of the collaborative mode in emergency information release of public health emergencies: A network analysis of response to COVID-19 from the central government of China
Authors: Liu Jida , Song Yuwei , An Shi , Dong Changqi , Lian Chenxi
Published: August 2022

Emergency information release during public health emergencies is a governance measure to slow down the spread of the epidemic and guide the public in scientific protection. Because of the uncertainty and life-cycle characteristics of public health emergencies, emergency information release represents the process of time dynamics. At present, it is an inevitable trend to establish a collaborative mechanism for emergency information release of public health emergencies to improve the release efficiency and respond to public demand. To determine time evolution characteristics of organizational collaboration in emergency information release, this study took the response to COVID-19 from the central government of China as an example and conducted research based on social network analysis. Based on information from COVID-19-related press conferences held by China's central government, the emergency information release collaborative networks (EIRCNs), and Emergency Organizations-Emergency Information Release Matters (EOs-EIRMs) 2-mode network were constructed. With the time evolution, the tightness, convergence, stability, and connectivity of EIRCNs in public health emergencies presented the process of lowering and then raising. At different stages, the core emergency organization (EO) nodes in EIRCNs continued to maintain a certain degree of activity. Their dynamic processes showed the characteristics of diversification rather than homogeneity. The time evolution of emergency information release matters (EIRMs) reflected the dynamic adjustment of the government's prevention and control measures and responded to the diversification of the public's understanding and protection needs during different stages of the COVID-19 pandemic. The study further examined the driving factors and implementation mechanism of the time evolution characteristics of the collaborative mode of emergency information release. The implementation of EIRMs at different stages had different resource requirements, which were usually achieved by introducing new EOs (Adding resource increment) or increasing the collaborative frequencies among EOs (Activating resource stock). In addition, further research prospects and feasibility interpretation were proposed.
Saltwater-responsive bubble artificial muscles using superabsorbent polymers
Authors: Gosden Daniel , Diteesawat Richard Suphapol , Studley Matthew , Rossiter Jonathan
Published: August 2022

Robots operating in changing underwater environments may be required to adapt to these varying conditions. In tidal estuaries, for example, where the degree of salinity cycles in step with the level of the water, a robot may need to adapt its behaviour depending on the position of the tide. In freshwater bodies, the unexpected presence of a pollutant may also require the robot to respond by altering its behaviour. Embodying this sensing and response in the body of the robot means that adaptivity to the environment can be achieved without resorting to centralised control. This can also allow direct responsivity using ‘free’ environmental energy, actuating without requiring stored onboard energy. In this work we present a soft artificial muscle, the contraction of which varies in response to the salinity the water surrounding it. The novel actuator uses a super-absorbent polymer gel encapsulated within a series of discrete cells. This gel readily absorbs water through the membrane wall of the actuator, and can swell to over 300 times its initial volume. This swelling generates significant pressure, changing the shape of the cells and driving the contraction of the muscle. The degree of swelling is significantly reduced by the presence of salts and pollutants in the surrounding water, so transitioning from a freshwater to a saltwater environment causes the muscle to relax. In this paper, we discuss the design and fabrication of these superabsorbent polymer-based Bubble Artificial Muscle (SAP-BAM) actuators. The tensile properties of the muscle under actuated (fresh water) and relaxed (salt water) conditions are characterised, showing a maximum generated force of 10.96N. The length response under constant load for a full actuation cycle is given, showing a maximum contraction of 27.5% of the initial length at 1N load, and the performance over repeated actuation and relaxation cycles is shown. The SAP-BAM muscles are straightforward to fabricate and are composed of low-cost, freely-available materials. Many existing pneumatically-actuated muscles can be modified to use the approach taken for this muscle. The muscle presented in this work represents the first example of a new class of super-absorbent polymer-driven environmental soft artificial muscles.
What Is Acne and What Causes It?
Authors: Mulhearn Jenna , Richmond Jillian M.
Published: August 2022

Most people have experienced waking up with a bright red pimple on their faces. Pimples can be painful, embarrassing, and downright annoying! But what causes these pesky blemishes known as acne? And is there anything we can do to treat or prevent them? This article explores the common types of acne found in adolescents and what causes them. It also discusses treatments for acne and the impact of acne on a person’s mental health and self-esteem.
Characterizing athletic healthcare: A perspective on methodological challenges, lessons learned, and paths forward
Authors: Lam Kenneth C. , Snyder Valier Alison R. , Valovich McLeod Tamara C. , Marshall Ashley N.
Published: August 2022

Recently, there has been an emphasis on collecting large datasets in the field of sports medicine. While there have been great advances in areas of sport performance and sport epidemiology, there have been fewer efforts dedicated to understanding the effectiveness and impact of athletic healthcare, including injury prevention programs and rehabilitation interventions provided at the point-of-care. In 2009, the Athletic Training Practice-Based Research Network (AT-PBRN) was launched to address this need, with the mission of improving the quality of care provided by athletic trainers. Unlike other research efforts in sports and medicine, such as sport epidemiology, there are fewer methodological best practices specifically related to clinical data in athletic healthcare. As a result, the AT-PBRN has encountered several methodological challenges during its tenure and has established guidelines based on various sources within the fields of sports and medicine to address these challenges. Therefore, the purpose of this perspective is to identify the challenges and describe strategies to address these challenges related to characterizing athletic healthcare using a large database. Specifically, challenges related to data entry (data quality and reliability) and data extraction and processing (data variability and missing data) will be discussed. Sharing challenges and perspectives on solutions for collecting and reporting on athletic healthcare data may facilitate a greater consistency in the approach used to collect, analyze, and report on clinical data in athletic healthcare, with the goal of improving patient outcomes and the quality of care provided by athletic trainers.
Comparison of florfenicol depletion in dairy goat milk using ultra-performance liquid chromatography with tandem mass spectrometry and a commercial on-farm test
Authors: Richards Emily D. , Pereira Richard V. , Davis Jennifer L. , Rowe Joan D. , Clapham Maaike O. , Wetzlich Scott E. , Rupchis Benjamin A. , Tell Lisa A.
Published: August 2022

Florfenicol is a broad-spectrum antibiotic commonly prescribed in an extra-label manner for treating meat and dairy goats. Scientific data in support of a milk withdrawal interval recommendation is limited to plasma pharmacokinetic data and minimal milk residue data that is limited to cattle. Therefore, a rapid residue detection test (RRDT) could be a useful resource to determine if milk samples are free of drug residues and acceptable for sale. This study compared a commercially available RRDT (Charm® FLT strips) to detect florfenicol residues in fresh milk samples from healthy adult dairy breed goats treated with florfenicol (40 mg/kg subcutaneously twice 4 days apart) with quantitative analysis of florfenicol concentrations using ultra-performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS). In addition, storage claims for testing bovine milk using the RRDT were assessed using stored goat milk samples. Milk samples were collected every 12 h for a minimum of 26 days. Commercial RRDT strips remained positive in individual goats ranging from 528 to 792 h (22–33 days) after the second dose, whereas, UPLC-MS/MS indicated the last detectable florfenicol concentration in milk samples ranged from 504 to 720 h (21–30 days) after the second dose. Results from stored milk samples from treated goats indicate that samples can be stored for up to 5 days in the refrigerator and 60 days in the freezer after milking prior to being tested with a low risk of false-negative test results due to drug degradation. Elevated somatic cell counts and bacterial colony were noted in some of the milk samples in this study, but further study is required to understand the impact of these quality factors on RRDT results.
Sound Scattering by Gothic Piers and Columns of the Cathédrale Notre-Dame de Paris
Authors: Weber Antoine , Katz Brian F. G.
Published: August 2022

Although the acoustics of Gothic cathedrals are of interest to researchers, the acoustic impact of their many columns is often neglected. The construction of the Cathédrale Notre-Dame de Paris spanned several centuries, including a wide variety of architectonic elements. This study investigates the sound scattering of a selection of seven designs that are relevant to this building as well as to the architectural style itself. These were measured on scale models (1:8.5 to 1:12), using a subtraction method, for receivers at about 3 m at full scale and a far-field source. They were also numerically simulated using a finite-difference time-domain method in two-dimensional space with an incident plane wave. The method integrates a finite volume framework to employ an unstructured mesh conforming to the complex geometries of interest. The two methods are in strong agreement for the considered configurations. Relative levels to the direct sound of backscattered reflections between −10 dB and 2 dB and between −15 dB and −6 dB in the transverse directions were estimated for the dimensions considered, relative to reported reflection audibility thresholds. Cross-sections with smaller scale geometrical elements on their perimeter can produce diffuse reflections similar to those of surface diffusers.
Numerical and Experimental Validation of Active Vibration Control Logic Performance of a Hybrid Noise Control-Based Brick
Authors: Ronconi Ilaria , Salierno Roberta , Liu Ling , Giglio Andrea , Ripamonti Francesco , Paoletti Ingrid
Published: August 2022

The limitations of active noise control (ANC) in coping with low frequencies and of passive noise control (PNC) in coping with middle-high frequencies are objects of research that present the potentialities of hybrid noise control (HBC). It aims at combining both of the behaviours by broadening the range of absorbed frequencies. Among the several application fields, the AEC (architecture, engineering, and construction) market can take advantage for those applications in which the noise conditions are caused by sound sources that tune in a broad frequencies range. In this frame, the paper describes the numerical and experimental validation of the active behaviour of an under-development project of a hybrid noise control-based acoustic bricks. The latter intends to embed the potentialities of active vibrational noise control (AVC) and passive destructive interference (PDI) in a unique design of an easy-to-mount, 3D-printed, customisable smart acoustic blocks. Active vibration control, the object of this paper, is provided by a 5-mm thick aluminium circular plate with an attached piezoelectric patch. The vibration of the latter, depending on a specific control law, defines the vibration of the plate itself achieving an abatement of the reflection coefficient. Through mathematical modelling and tests in an impedance tube, the results show that the control logic can reach an average abatement of the reflection coefficient of 82% in the frequency range 144–1007 Hz.
Lateral Stability Analysis of 4WID Electric Vehicle Based on Sliding Mode Control and Optimal Distribution Torque Strategy
Authors: Wang Hongwei , Han Jie , Zhang Haotian
Published: August 2022

In this paper, we propose a lateral stability control strategy for four-wheel independent drive (4WID) electric vehicles. The control strategy adopts a hierarchical structure. First, a seven-degree-of-freedom (7DOF) 4WID electric vehicle model is established. Then, the upper controller adopts the integral sliding mode control (ISMC) method to obtain the desired yaw moment by controlling both the yaw rate and the sideslip angle. A new sliding mode reaching law (NSMRL) is designed to reduce chattering and make state variables converge faster, and the superiority of NSMRL is verified by theoretical analysis. The lower controller proposes a new optimal allocation algorithm, which selects the tire utilization rate and the standard deviation coefficient of the tire utilization rate as the objective function. The safety performance of vehicle is improved, and the instability caused by the significant difference in the stability margin between the four wheels under extreme road conditions is avoided. Finally, a simulation is carried out to verify the effectiveness of the proposed control strategy under single-lane-change and J-turn maneuvers.
Genome-Wide Identification, In Silico Analysis and Expression Profiling of SWEET Gene Family in Loquat (Eriobotrya japonica Lindl.)
Authors: Li Binqi , Ali Muhammad Moaaz , Guo Tianxin , Alam Shariq Mahmood , Gull Shaista , Iftikhar Junaid , Yousef Ahmed Fathy , Mosa Walid F. A. , Chen Faxing
Published: August 2022

SWEETs (sugars will eventually be exported transporters) have various physiological and biochemical roles in plant growth, including pollen development, seed nourishment, nectar secretion, and longer-distance sugar transportation. The SWEET genes were identified in various plant species, but they have not yet been thoroughly characterized. Here, we discovered 21 putative SWEET genes from the Eriobotrya japonica Lindl. genome. For further elucidation, comprehensive bioinformatics analysis was utilized to determine the physicochemical properties, gene organization, conserved motifs, cis-regulatory elements, gene duplication, and phylogenetic relationships of EjSWEET genes. Most of the SWEET proteins were predicted to be located on the plasma membrane or vacuole. Gene organization and motif analysis showed that the numbers of exons and motifs in each gene ranged strikingly, between 5 and 6 and between 5 and 8, respectively. Synteny analysis showed that the tandem or segmental duplication played a dynamic role in the evolution of SWEET genes in loquat. Likewise, we analyzed the expression patterns of EjSWEET genes in the root, stem, leaf, flower, and fruit of loquat. Some genes exhibited varying expression in loquat tissues, indicating their potential roles in plant development. The relative expression levels of EjSWEET1, EjSWEET3, and EjSWEET16 were noticeably higher in ripened fruits, suggesting their possible role in the transportation and unloading of sugars in fruits. The present study provides initial genome-wide identification and characterization of the SWEET gene family in loquat and lays the foundation for their further functional analysis.
Identification of Selection Preferences and Predicting Yield Related Traits in Sugarcane Seedling Families Using RGB Spectral Indices
Authors: Todd James , Johnson Richard , Verdun David , Richard Katie
Published: August 2022

The early stages of the United States Department of Agriculture (USDA) Louisiana commercial sugarcane breeding program involve planting large numbers of genetically unique seedlings that require time and resources to evaluate. Selection is made quickly, is subjective, and related to the appearance of yield and vigor. Remote sensing techniques have been used to predict yield of several crops over large areas using areal images. To understand selection preferences better and if remote sensing techniques could be used to increase efficiency, twelve sugarcane seedling families each having approximately 263 seedlings were planted in two replications at the USDA-ARS Ardoyne farm. Stalk height, number and diameter ratings were taken on 50 stools of each replication of each family. Red-Green-Blue images were taken of the seedling field in plant cane and first ratoon before selection. Spectral indices were derived from the images for each plot. Height had the largest influence on visual selections of the field measurements evaluated. Several spectral indices such as the Green Area (GA) correlated highly with important traits including Height (>0.80), selection rates (>0.70), and Brix (>0.60). The results show the potential for seedling evaluation by remote sensing methods.
Automatic Position Detection and Posture Recognition of Grouped Pigs Based on Deep Learning
Authors: Ji Hengyi , Yu Jionghua , Lao Fengdan , Zhuang Yanrong , Wen Yanbin , Teng Guanghui
Published: August 2022

The accurate and rapid detection of objects in videos facilitates the identification of abnormal behaviors in pigs and the introduction of preventive measures to reduce morbidity. In addition, accurate and effective pig detection algorithms provide a basis for pig behavior analysis and management decision-making. Monitoring the posture of pigs can enable the detection of the precursors of pig diseases in a timely manner and identify factors that impact pigs’ health, which helps to evaluate their health status and comfort. Excessive sitting represents abnormal behavior when pigs are frustrated in a restricted environment. The present study focuses on the automatic recognition of standing posture and lying posture in grouped pigs, which shows a lack of recognition of sitting posture. The main contributions of this paper are as follows: A human-annotated dataset of standing, lying, and sitting postures captured by 2D cameras during the day and night in a pig barn was established, and a simplified copy, paste, and label smoothing strategy was applied to solve the problem of class imbalance caused by the lack of sitting postures among pigs in the dataset. The improved YOLOX has an average precision with an intersection over union threshold of 0.5 (AP0.5) of 99.5% and average precision with an intersection over union threshold of 0.5–0.95 (AP0.5–0.95) of 91% in pig position detection; an AP0.5 of 90.9% and an AP0.5–0.95 of 82.8% in sitting posture recognition; a mean average precision with intersection over union threshold of 0.5 (mAP0.5) of 95.7% and a mean average precision with intersection over union threshold of 0.5–0.95 (mAP0.5–0.95) of 87.2% in all posture recognition. The method proposed in our study can improve the position detection and posture recognition of grouped pigs effectively, especially for pig sitting posture recognition, and can meet the needs of practical application in pig farms.
Characterizing Agricultural Diversity with Policy-Relevant Farm Typologies in Mexico
Authors: LaFevor Matthew C.
Published: August 2022

The effective targeting of agricultural policy interventions across heterogenous agricultural landscapes requires an integrated understanding of farm diversity. One pathway to this understanding is through farm typologies—classification systems that synthesize farm complexity into a limited number of ‘types’. Farm typologies are typically constructed at local or regional levels and seldom demonstrate policy relevance through example. This study has two objectives: (1) to construct a policy-relevant farm typology that characterizes agricultural diversity in Mexico, and (2) to demonstrate, through case study example, how the typology could be used to target policy interventions. Hierarchical agglomerative cluster (HAC) analysis is used to group municipalities (n = 2455) based on farm characteristics (n = 10) and cropping patterns (n = 10). Two clustering solutions were chosen based on statistical goodness-of-fit measures and topical relevance. The first set of clusters (Typology A) grouped municipalities into one of three types: (A1) southern lowland farms, (A2) northern midland farms, and (A3) southern-central highland farms. The second (Typology B) grouped municipalities into 12 sub-types illustrating lower-order distinctions. Each typology was described, validated, and mapped at the national level. The typologies were then used to illustrate the targeting soil erosion interventions across Mexico. Here, multiple correspondence analysis (MCA) was used to examine relationships between the typologies and two priority targeting criteria. Farms of the southern lowland region (Type A1) and two of its subtypes (B1 and B12) were identified as priority areas for interventions. In sum, this study: (1) creates a series of new, typology-based conceptualizations of regional agricultural diversity in Mexico, and (2) demonstrates how such typologies can serve as actionable tools for agricultural policy.
Causal Linkage among Agricultural Insurance, Air Pollution, and Agricultural Green Total Factor Productivity in United States: Pairwise Granger Causality Approach
Authors: Ahmed Nihal , Hamid Zeeshan , Mahboob Farhan , Rehman Khalil Ur , Ali Muhammad Sibt e , Senkus Piotr , Wysokińska-Senkus Aneta , Siemiński Paweł , Skrzypek Adam
Published: August 2022

Agricultural insurance and green agriculture are strongly related. Agricultural insurance not only motivates farmers to adopt environmentally friendly production technology and enhances the effectiveness of production, but it also accomplishes the goal of lowering the number of chemicals that are put into the environment. This article investigates the dynamic relationship between agricultural insurance, air pollution, and agricultural green total factor productivity. To complete the aim, the authors used the panel auto-regressive distributed lags method (PMG method) and panel data from 50 states of the United States between 2005 and 2019. The empirical findings demonstrate a considerable co-integration and a cross-sectional reliance between agricultural insurance, air pollution, and agricultural green total factor production. Expanding agricultural insurance may boost agricultural green whole factor output but also exacerbate air pollution. However, significant air pollution does not increase agricultural production’s green total factor productivity. The panel Granger causality test shows a one-way causal relationship between agricultural insurance, green total factor productivity, and air pollution. A one-way causal relationship exists between air pollution and agricultural green total factor productivity. The author concluded that improving agricultural insurance coverage or cutting down on air pollution will boost agricultural green total factor output. These findings have long-term policy and management repercussions, particularly for those involved in agriculture policy and environmental management.
The Grassland Ecological Compensation Policy Drives the Differentiation of Herders’ Livelihoods in Inner Mongolian Desert Grassland
Authors: Chang Hong , Liu Xinchao , Xie Yu , Liu Yahong , Yang Wu , Niu Jianming
Published: August 2022

Herders’ livelihood strategies are functions of the capitals at their disposal. Although this thesis has been proved, it has not been applied to livelihood research in the context of conservation initiatives. The Chinese government implemented the Grassland Ecological Compensation Policy (GECP) in 2011. However, the impact of the policy on herders’ livelihoods is still unclear. This study measured the variation in herders’ livelihood strategies in the desert grassland of Inner Mongolia, China, after the implementation of the GECP. This study also analyzed the impacts of livelihood capitals on the livelihood strategies, revealing the shortages of different livelihood strategies. The results showed the following: After the GECP, (1) herders’ livelihood strategies could be grouped into five types based on livelihood capitals. The livelihood capitals of herders varied greatly, resulting in large economical gaps among households with different livelihood strategies. (2) The herders’ livelihood strategies were affected by factors including the education, age, social communication, amount of livestock, income, and subsidy of the herders. (3) The main income sources of different livelihood strategies were both subsidy and livestock husbandry. In general, the GECP drives the differentiation of herders’ livelihoods remarkably. Future conservation initiatives should take the shortages of different livelihood strategies into account.
16S Amplicon Sequencing of Nitrifying Bacteria and Archaea Inhabiting Maize Rhizosphere and the Influencing Environmental Factors
Authors: Ayiti Oluwatobi Esther , Ayangbenro Ayansina Segun , Babalola Olubukola Oluranti
Published: August 2022

Nitrifying bacteria and archaea are ubiquitous and can transform ammonia locked up in soil or manure into nitrate, a more soluble form of nitrogen. However, nitrifying bacteria and archaea inhabiting maize rhizosphere have not been fully explored. This study evaluates the diversity and abundance of nitrifying bacteria and archaea across different growth stages of maize using 16S amplicon sequencing. Moreover, the influence of environmental factors (soil physical and chemical properties) on the nitrifying communities was evaluated. Rhizosphere soil DNA was extracted using Nucleospin Soil DNA extraction kit and sequenced on Illumina Miseq platform. MG-RAST was used to analyze the raw sequences. The physical and chemical properties of the soil were measured using standard procedure. The results revealed 9 genera of nitrifying bacteria; Nitrospira, Nitrosospira, Nitrobacter, Nitrosovibrio, Nitrosomonas, Nitrosococcus, Nitrococcus, unclassified (derived from Nitrosomonadales), unclassified (derived from Nitrosomonadaceae) and 1 archaeon Candidatus Nitrososphaera. The Nitrospirae phyla group, which had the most nitrifying bacteria, was more abundant at the tasselling stage (67.94%). Alpha diversity showed no significant difference. However, the Beta diversity showed significant difference (p = 0.01, R = 0.58) across the growth stages. The growth stages had no significant effect on the diversity of nitrifying bacteria and archaea, but the tasselling stage had the most abundant nitrifying bacteria. A correlation was observed between some of the chemical properties and some nitrifying bacteria. The research outcome can be put into consideration while carrying out a biotechnological process that involves nitrifying bacteria and archaea.
Contour Resampling-Based Garlic Clove Bud Orientation Recognition for High-Speed Precision Seeding
Authors: Liu Jian , Yuan Jin , Cui Jiyuan , Liu Yunru , Liu Xuemei
Published: August 2022

Achieving fast and accurate recognition of garlic clove bud orientation is necessary for high-speed garlic seed righting operation and precision sowing. However, disturbances from actual field sowing conditions, such as garlic skin, vibration, and rapid movement of garlic seeds, can affect the accuracy of recognition. Meanwhile, garlic precision planters need to realize a recognition algorithm with low-delay calculation under the condition of limited computing power, which is a challenge for embedded computing platforms. Existing solutions suffer from low recognition rate and high algorithm complexity. Therefore, a high-speed method for recognizing garlic clove bud direction based on deep learning is proposed, which uses an auxiliary device to obtain the garlic clove contours as the basis for bud orientation classification. First, hybrid garlic breeds with the largest variation in shape were selected randomly and used as research materials, and a binary image dataset of garlic seed contours was created through image sampling and various data enhancement methods to ensure the generalization of the model that had been trained on the data. Second, three lightweight deep-learning classifiers, transfer learning based on MobileNetV3, a naive convolutional neural network model, and a contour resampling-based fully connected network, were utilized to realize accurate and high-speed orientation recognition of garlic clove buds. Third, after the optimization of the model’s structure and hyper-parameters, recognition models suitable for different levels of embedded hardware performance were trained and tested on the low-cost embedded platform. The experimental results showed that the MobileNetV3 model based on transfer learning, the naive convolutional neural network model, and the fully connected model achieved accuracy of 98.71, 98.21, and 98.16%, respectively. The recognition speed of the three including auxiliary programs was 19.35, 97.39, and 151.40 FPS, respectively. Theoretically, the processing speed of 151 seeds per second achieves a 1.3 hm2/h planting speed with single-row operation, which outperforms state-of-the-art methods in garlic-clove-bud-orientation recognition and could meet the needs of high-speed precise seeding.
Morphological, Molecular, and Pathogenic Characterization of Neofabraea alba, a Postharvest Pathogen of Apple in Serbia
Authors: Vukotić Jelena , Stojšin Vera , Nagl Nevena , Petreš Mladen , Hrustić Jovana , Grahovac Mila , Tanović Brankica
Published: August 2022

Neofabraea spp. is one of the major causal agents of the postharvest decay of apple fruit. Bull’s eye rot can cause fruit rot, as well as tree canker. In Serbia, during February and March, 2017 and 2018, 56.3% of collected stored rotten apple fruits were found to be infected with Neofabraea spp. Using polymerase chain reaction, phylogenetic analysis, and morphological characterization, Neofabraeaalba was identified as the causal agent of Bull’s eye rot. Twenty-five selected isolates were analyzed by DNA sequencing of the internal transcribed spacer and 16 S mitochondrial ribosomal RNA. The phylogenetic analyses provided information on the distance between Neofabraea spp., while merged phylogenetic tree was required to give insight and clarify the relationships between isolates of Neofabraeaalba. N. alba demonstrated pathogenicity on apple fruit as well as on branches, with significantly different aggressiveness among the isolates. Isolates were able to produce larger cankers and acervuli on apple branches with abundant sporulation All identified isolates were separated into two morphotypes and described based on their macromorphological characteristics on culture media. It was noticed that different culture media, pH, and temperature could affect macromorphological characteristics and development. Representative isolates were able to grow at a temperature range of 0 to 25 °C, above which only one isolate was able to grow on culture media. All isolates showed growth at a pH range of 2–10, with significant differences detected between isolates at different pH values. The type of cultivation medium significantly affected the size and shape of conidia, while the presence of the microconidia was recorded within isolates. The aim of this study was to identify the causal agents of Bull’s eye rot on stored apples in Serbia in the period 2017–2018 and characterize the obtained isolates based on pathogenic, morphological, physiological, and molecular criteria.
Does Adoption of Biofortification Increase Return on Investment? Evidence from Wheat Farmers in China
Authors: Zeng Jing , Li Han , Tang Yifan , Qing Ping
Published: August 2022

Biofortification is a new agricultural intervention to alleviate hidden hunger in China and even the world. Exploring the impact of farmers′ adoption of biofortification on return on investment (ROI), which is calculated from farmers′ production net income and profitability, can provide empirical support for the development of sustainable agriculture. This paper examines the impact of the adoption of biofortification on ROI using cross-sectional data from a survey of farmers in China. An endogenous switching regression model that accounts for selection bias was used in the research. The empirical results revealed that the adoption of biofortification has a positive and statistically significant impact on ROI. A heterogeneity analysis also revealed that comparatively high annual income adopters and female adopters tend to benefit more from the adoption of biofortification than middle- and low-income adopters and male adopters.
DS-DETR: A Model for Tomato Leaf Disease Segmentation and Damage Evaluation
Authors: Wu Jianshuang , Wen Changji , Chen Hongrui , Ma Zhenyu , Zhang Tian , Su Hengqiang , Yang Ce
Published: August 2022

Early blight and late blight are important factors restricting tomato yield. However, it is still a challenge to accurately and objectively detect and segment crop diseases in order to evaluate disease damage. In this paper, the Disease Segmentation Detection Transformer (DS-DETR) is proposed to segment leaf disease spots efficiently based on several improvements to DETR. Additionally, a damage assessment is carried out by the area ratio of the segmented leaves to the disease spots. First, an unsupervised pre-training method was introduced into DETR with the Plant Disease Classification Dataset (PDCD) to solve the problem of the long training epochs and slow convergence speed of DETR. This method can train the Transformer structures in advance to obtain leaf disease features. Loading the pre-training model weight in DS-DETR can speed up the convergence speed of the model. Then, Spatially Modulated Co-Attention (SMCA) was used to assign Gaussian-like spatial weights to the query box of DS-DETR. The different positions in the image are trained using the query boxes with different weights to improve the accuracy of the model. Finally, an improved relative position code was added to the Transformer structure of DS-DETR. Relative position coding promotes the capture of the sequence order of input tokens by the Transformer. The spatial location feature is strengthened by establishing the location relationship between different instances. Based on these improvements, the DS-DETR model was tested on the Tomato leaf Disease Segmentation Dataset (TDSD) constructed by us. The experimental results show that the DS-DETR proposed by us achieved 0.6823 for APmask, which improved by 12.87%, 8.25%, 3.67%, 1.95%, 10.27%, and 9.52% compared with the state-of-the-art: Mask RCNN, BlendMask, CondInst, SOLOv2, ISTR, and DETR, respectively. In addition, the disease grading accuracy reached 0.9640 according to the segmentation results given by our proposed model.
Adaptation of Quinoa (Chenopodium quinoa Willd.) to Australian Environments
Authors: Snowball Richard , Dhammu Harmohinder S. , D’Antuono Mario Francesco , Troldahl David , Biggs Ian , Thompson Callen , Warmington Mark , Pearce Amanda , Sharma Darshan L.
Published: August 2022

Quinoa is being evaluated in cropping systems in many countries outside of its natural range of South America. Very few attempts have been made by farmers or researchers to grow or evaluate quinoa under Australian environments. Given the growing popularity of quinoa with consumers, new commercial opportunities for farmers and international interest in the crop, it was timely to undertake a comprehensive evaluation of the potential of quinoa in Australia. Two advanced selections and nine germplasm lines (six of Chilean and three of Bolivian origin) identified in an earlier project were tested in 23 field trials at 14 locations on mainland Australia. Targets included irrigated sites in tropical, Mediterranean, semi-arid and desert climates, and rain-fed sites of south-western Australia with a Mediterranean climate. The field experiments were either a randomised complete block design (RBCD) or a split plot/factorial design with 2–4 replicates, and a linear mixed model was used to compare the treatment lines. Seed yield of quinoa was highest when grown in winter and spring under rain-fed conditions in Geraldton, in spring and summer under irrigation at Bool Lagoon, and summer, autumn and winter under irrigation at Leeton. The highest seed yield achieved was 3 t/ha for a germplasm line from Chile, while the highest yield for a germplasm line from Bolivia was 2.6 t/ha. Advanced selections from Australia yielded well in comparison at most trial sites. Declining seed yield was associated with mean daily temperatures during seed development increasing above 17 °C, mean daily temperatures during flowering declining below 15 °C, and rainfall during seed development under rain-fed conditions falling below 50 mm. Seed produced at Bool Lagoon was the closest in colour to white quinoa imported from Peru; however, it was more than noticeably different. Seed produced at Geraldton and Leeton was significantly larger than from other field sites; however, none were larger than 2 mm in diameter as found in Royal white quinoa from Bolivia. Superior seed colour and seed size were associated with dry conditions at maturity and cool conditions during seed development, respectively. We conclude that quinoa can become a potential crop option for Australian agriculture by exploiting genetic diversity and supplementing with suitable management practices matched to agro-climatic environments. There are reasonable prospects to raise the seed yield potential in areas in all states, especially in the regions where quinoa grew well in our experiments.
Effect of Nitrogen on the Viscosity of the Erosive Sediment-Laden Flows
Authors: Zhang Yuanyuan , Gao Jianen , Gao Zhe , Wang Zhaorun , Wang Lu , Kang Youcai , Ahmad Rafiq
Published: August 2022

Viscosity is a fundamental hydrodynamic property of erosive flow, but except for the effect of sediment on viscosity, the effect of other erosive substances such as agricultural nitrogen on the characteristics of erosive flow has rarely been studied. This in turn is likely to be an important factor affecting the erosive transport mechanism. In this study, the effect of nitrogen on the viscosity of sediment-laden flow with different levels was investigated by using a self-made dual vertical tube rheometer. It was found that: (i) the viscosity coefficient (μ) of nitrogen-bearing erosive flow is affected by the nitrogen concentration, sediment content, and the physical and chemical properties of the sediment; (ii) the calculation model of the relative viscosity coefficient with the effects of nitrogen, concentration, sediment gradation, and temperature, was constructed, and the validation showed that the model not only has a clear physical meaning but also has a simple calculation method and good calculation accuracy. The results of the study are of great significance for the in-depth understanding of the erosion transport mechanism of erosive flow.
Detection of Candidate Loci and Genes Related to Phosphorus Efficiency at Maturity through a Genome-Wide Association Study in Soybean
Authors: Wang Qing , Ning Lihua , Yu Wenqing , Zhao Wei , Huang Fang , Yu Deyue , Wang Hui , Cheng Hao
Published: August 2022

Phosphorus (P) deficiency is one of the major factors limiting soybean production, and approximately 90% of P absorbed by plants occurs during the reproductive stage. Thus, it is important to understand the genetic mechanism underlying soybean low-P tolerance, especially in the mature period. Here, we evaluated six P-efficiency-related traits at maturity of 219 soybean accessions, namely, plant height (PH), node number of the main shoot (NN), branch number of the main shoot (BN), pod number per plant (PN), 100-seed weight (100SW), and seed yield per plant (SY), under normal-phosphorus (NP) and low-phosphorus (LP) conditions across two environments. Then, a genome-wide association study (GWAS) in conjunction with a high-density NJAU 355 K SoySNP array was performed. As a result, 27 P-efficiency-related single nucleotide polymorphisms (SNPs) were identified. Furthermore, two repeated SNPs, AX-93897192 and AX-93897200, located on chromosome 19 that were associated with both PH and NN were considered as stable SNPs associated with P deficiency, and the candidate gene GmABCG39 was identified. This work will be helpful in breeding high-P-efficiency soybean varieties.
Planting Date and Hybrid Affect Sugarcane Aphid Infestation, Yield, and Water Use Efficiency in Dryland Grain Sorghum
Authors: Jenkins Zane , Thapa Sushil , M. Bell Jourdan , E. Jessup Kirk , C. Blaser Brock , Stewart Bob A. , Xue Qingwu
Published: August 2022

Grain sorghum (Sorghum bicolor L.) is a major dryland crop in the Texas High Plains. Currently, drought and infestation by the sugarcane aphid (SCA, Melanaphis sacchari) are the two major challenges to grain sorghum production in the area. A 2-year field study was conducted to investigate the effect of planting date (PD) and hybrid selection on yield, evapotranspiration (ET), water use efficiency (WUE), and SCA infestation. Five sorghum hybrids (86P20, SP-31A15, AG1201, AG1203, and DKS37-07) were grown on two planting dates (PD1—early May; PD2—late June) under dryland conditions. Insecticides were not used. There were significant differences in grain yield, WUE, evapotranspiration (ET), and SCA population between two PDs and among hybrids. For PD1, SCA infestation occurred after sorghum reached physiological maturity in 2017. Although SCA infestation was observed during late grain filling in 2018, SCA populations were low and did not affect yield. For PD2, SCA was present before anthesis in both years and significantly affected grain yield. Even with heavy SCA infestation in PD2, the grain yield was higher in PD2 than in PD1 due to timely precipitation. Among hybrids, AG1203, 86P20 and DK37-07 performed better with higher yield and less SCA infestation in PD2. Grain yield was more related to seeds per plant than to kernel weight and harvest index.
Research into Meteorological Drought in Poland during the Growing Season from 1951 to 2020 Using the Standardized Precipitation Index
Authors: Kalbarczyk Robert , Kalbarczyk Eliza
Published: August 2022

Meteorological drought (MDr) causes considerable economic losses in many countries, including in relation to agriculture. To examine the diversity of seasonal meteorological drought in Poland, the study uses monthly precipitation sums in the period from March to November, collected from 74 ground-based meteorological stations in 1951–2020. The paper defines meteorological drought on the basis of the standardized precipitation index in three seasons (SPI-3) and differentiates three degrees of drought intensity: extreme, severe and moderate. The study also calculates the size of Poland’s area affected by meteorological drought (AAMDr) and determines the relationship between AAMDr and SPI-3. MDr in Poland occurred more frequently in spring and autumn (every 4–5 years) than in summer (every 7 years). In the areas affected by extreme drought, precipitation was below the average, mainly ≤50% of the climatic norm, and air temperature values were below or above the average of the climatic norm, mainly ranging from −1.0 to 1.0 °C. A significant negative correlation between AAMDr and SPI-3 indices was found. The obtained results could be useful for managing climatic risk and developing regional and local agriculture adaptation plans aimed at mitigating the effects of climate change.
Residual Effect of Finely-Ground Biochar Inoculated with Bio-Fertilization Impact on Productivity in a Lentil–Maize Cropping System
Authors: Ali Amjad , Ahmad Wiqar , Munsif Fazal , Khan Aziz , Nepal Jaya , Wójcik-Gront Elżbieta , Ahmad Ijaz , Khan Muhammad Shahid , Ullah Ikram , Akbar Sultan , Zaheer Sajjad , Jin Gang
Published: August 2022

Biochar fertilization improves soil fertility and carbon sequestration, implying agricultural and environmental advantages. The effect of different sized previously applied biochar and biofertilizer agents on succeeding crops remains poorly known for legume–cereal cropping cycles. This study compared different particle-sized biochar and biofertilizer strains applied to lentils for their residual impact on subsequent maize growth, nutrition, and soil fertility without further polluting the environment. Three particle sizes (<2, 2–5, 5–10 mm) of Babul tree (Acacia arabica) wood biochar was obtained through grinding and sieving and applied prior to the lentil (first) crop at a rate of 500 g m−2. The commercial Rhizobium leguminosarum products Biozote-N and Rhizogold were inoculated to lentil seeds before sowing. The effect of biochar and biofertilizer agents on the succeeding maize (second) crops was evaluated for soil and crop performance. Findings revealed that particle sizes of <2 mm biochar and Biozote-N inoculation enhanced plant height, leaf area and leaf area index, biological yield, and thousand grain weight of the subsequent maize crop. Maize grain yield was enhanced by 2.5%, tissue N uptake by 15%, nitrogen uptake efficiency by 17%, grain protein content by 15%, extractable P by 17%, and soil bulk density by 3% with a residual biochar particle size of <2 mm and Biozote-N inoculation. It was concluded that the finely grounded (<2 mm) biochar particle combined with inoculation of Biozote-N was superior to larger particle sizes for enhancing crop growth and improving soil fertility status at the residual level, benefiting the subsequent crop in a legume–cereal rotation system.
Comparative Analysis of Two Pear Pests, Cacopsylla jukyungi and Cacopsylla burckhardti (Hemiptera: Psyllidae), Based on Complete Mitochondrial Genomes and Comparison to Confamilial Species
Authors: Kang Ah Rang , Kim Min Jee , Park Jeong Sun , Seo Ho-Jin , Song Jang-Hoon , Won Kyung-Ho , Choi Eu Ddeum , Kim Iksoo
Published: August 2022

Mitochondrial genome sequences have been used in diverse fields of biology. In this study, we sequenced the complete mitochondrial genomes (mitogenome) of two pear pests: Cacopsylla jukyungi, the most damaging insect pest to commercial pears in South Korea, and Cacopsylla burckhardti (Hemiptera: Psyllidae). The two mitogenomes were compared to confamilial species to accumulate genetic information and understand evolutionary characteristics of the family Psyllidae. The 15,438 bp-and 14,799 bp-long complete mitogenomes of C. jukyungi and C. burckhardti, respectively, had many features typical of insect mitogenomes; however, at 1283 bp, the C. jukyungi mitogenome had an unusually long A+T-rich region, which was composed of two identical 540-bp repeat sequences. Among the intergenic spacer regions, the one located at the ND1 and trnS2 junction was relatively well conserved in length (mostly within 23–36 bp). This region had a high sequence identity in all Psyllidae, possessing a 5-bp consensus sequence (CGGTA), which is speculated to have a functional role. Though the A+T-rich region in available Psyllidae mitogenomes varied substantially in length (662–1430 bp) and sequence divergence, all species had a conserved sequence stretch at the 3′-end of srRNA, which is also speculated to have a functional role. Genetic divergence among genes indicated the lowest variability in srRNA, lrRNA, and COI, whereas ATP8 and ND6 showed the highest variability at both family and genus (Cacopsylla) levels. Our data provide evidence that the family Psyllidae, including current C. jukyungi and C. burckhardti, have evolutionary unique features that were previously undetected, along with the unique A+T-rich region structure in C. jukyungi.