bluuebunny/crossref_metadata_2025 huggingface dataset:
Resistance to white spot syndrome virus in the European shore crab is associated with suppressed virion trafficking and heightened immune responses
Authors: Millard Rebecca S. , Bickley Lisa K. , Bateman Kelly S. , Verbruggen Bas , Farbos Audrey , Lange Anke , Moore Karen A. , Stentiford Grant D. , Tyler Charles R. , van Aerle Ronny , Santos Eduarda M.
Published: December 2022

Introduction

All decapod crustaceans are considered potentially susceptible to White Spot Syndrome Virus (WSSV) infection, but the degree of White Spot Disease (WSD) susceptibility varies widely between species. The European shore crab Carcinus maenas can be infected with the virus for long periods of time without signs of disease. Given the high mortality rate of susceptible species, the differential susceptibility of these resistant hosts offers an opportunity to investigate mechanisms of disease resistance.

Methods

Here, the temporal transcriptional responses (mRNA and miRNA) of C. maenas following WSSV injection were analysed and compared to a previously published dataset for the highly WSSV susceptible Penaeus vannamei to identify key genes, processes and pathways contributing to increased WSD resistance.

Results

We show that, in contrast to P. vannamei, the transcriptional response during the first 2 days following WSSV injection in C. maenas is limited. During the later time points (7 days onwards), two groups of crabs were identified, a recalcitrant group where no replication of the virus occurred, and a group where significant viral replication occurred, with the transcriptional profiles of the latter group resembling those of WSSV-susceptible species. We identify key differences in the molecular responses of these groups to WSSV injection.

Discussion

We propose that increased WSD resistance in C. maenas may result from impaired WSSV endocytosis due to the inhibition of internal vesicle budding by dynamin-1, and a delay in movement to the nucleus caused by the downregulation of cytoskeletal transcripts required for WSSV cytoskeleton docking, during early stages of the infection. This response allows resistant hosts greater time to fine-tune immune responses associated with miRNA expression, apoptosis and the melanisation cascade to defend against, and clear, invading WSSV. These findings suggest that the initial stages of infection are key to resistance to WSSV in the crab and highlight possible pathways that could be targeted in farmed crustacean to enhance resistance to WSD.
Highly sensitive liquid biopsy Duplex sequencing complements tissue biopsy to enhance detection of clinically relevant genetic variants
Authors: Hallermayr Ariane , Neuhann Teresa M. , Steinke-Lange Verena , Scharf Florentine , Laner Andreas , Ewald Roland , Liesfeld Ben , Holinski-Feder Elke , Pickl Julia M. A.
Published: December 2022

Background

Liquid biopsy (LB) is a promising complement to tissue biopsy for detection of clinically relevant genetic variants in cancer and mosaic diseases. A combined workflow to enable parallel tissue and LB analysis is required to maximize diagnostic yield for patients.

Methods

We developed and validated a cost-efficient combined next-generation sequencing (NGS) workflow for both tissue and LB samples, and applied Duplex sequencing technology for highly accurate detection of low frequency variants in plasma. Clinically relevant cutoffs for variant reporting and quantification were established.

Results

We investigated assay performance characteristics for very low amounts of clinically relevant variants. In plasma, the assay achieved 100% sensitivity and 92.3% positive predictive value (PPV) for single nucleotide variants (SNVs) and 91.7% sensitivity and 100% PPV for insertions and deletions (InDel) in clinically relevant hotspots with 0.5-5% variant allele frequencies (VAFs). We further established a cutoff for reporting variants (i.e. Limit of Blank, LOB) at 0.25% VAF and a cutoff for quantification (i.e. Limit of Quantification, LOQ) at 5% VAF in plasma for accurate clinical interpretation of analysis results. With our LB approach, we were able to identify the molecular cause of a clinically confirmed asymmetric overgrowth syndrome in a 10-year old child that would have remained undetected with tissue analysis as well as other molecular diagnostic approaches.

Conclusion

Our flexible and cost-efficient workflow allows analysis of both tissue and LB samples and provides clinically relevant cutoffs for variant reporting and precise quantification. Complementing tissue analysis by LB is likely to increase diagnostic yield for patients with molecular diseases.
Optimized Approach for Localization of Sensor Nodes in 2D Wireless Sensor Networks Using Modified Learning Enthusiasm-Based Teaching–Learning-Based Optimization Algorithm
Authors: Kaur Goldendeep , Jyoti Kiran , Mittal Nitin , Mittal Vikas , Salgotra Rohit
Published: December 2022

Wireless Sensor Networks (WSNs) have a wonderful potential to interconnect with the physical world and collect data. Data estimation, long lifespan, deployment, routing, task scheduling, safety, and localization are the primary performance difficulties for WSNs. WSNs are made up of sensor nodes set up with minimal battery power to monitor and reveal the occurrences in the sensor field. Detecting the location is a difficult task, but it is a crucial characteristic in many WSN applications. Locating all of the sensor nodes efficiently to obtain the precise location of an occurrence is a critical challenge. Surveillance, animal monitoring, tracking of moving objects, and forest fire detection are just a few of the applications that demand precise location determination. To cope with localization challenges in WSNs, there is a variety of localization algorithms accessible in the literature. The goal of this research is to use various optimization strategies to solve the localization problem. In this work, a modified learning enthusiasm-based teaching–learning-based optimization (mLebTLBO) algorithm is used to cope with a 2D localization problem applying the notion of an exclusive anchor node and movable target nodes. A modified LebTLBO algorithm seeks to increase overall efficiency by assessing the exploration and exploitation abilities. The computational results reveal that this technique outperforms others with respect to localization errors in a 2D environment of WSN.
Review of On-Orbit Robotic Arm Active Debris Capture Removal Methods
Authors: Zhang Wei , Li Feng , Li Junlin , Cheng Qinkun
Published: December 2022

Space is the driving force of the world’s sustainable development, and ensuring the sustainability of human activity in space is also necessary. Robotic arm active debris capture removal (RA-ADCR) is a noteworthy technology for containing the dramatic increase in space debris and maintaining orbital safety. This review divides the RA-ADCR technology progress history into three periods and presents the status of related research. Two major development trends are summarized and subdivided through the analysis and collation of research achievements over the past three years. Taking the treatment of parameter uncertainties as the entry point, researchers would like to improve the discrimination accuracy and scope to reduce uncertainties. On the other hand, researchers accept such uncertainties and would like to offset and avoid the impact of uncertainties by extending the error margins. Subsequently, the challenges of RA-ADCR are analyzed in line with the task execution flow, which mainly focuses on the conflict between on-satellite computing power and the performance of task execution. In addition, feasible solutions for the current phase are discussed. Finally, future outlooks are evaluated and discussed.
Numerical Simulation and PIV Experimental Investigation on Underwater Autorotating Rotor
Authors: Li Liang , Chen Ming , Wang Fang , Wu Zhichen , Xu Anan
Published: December 2022

In this work, the flow field of an autorotating rotor in a water tunnel with various pitches and shaft backward angles was investigated via particle image velocimetry (PIV). The experiments were carried out on a free-rotating two-bladed single rotor. Computational Fluid Dynamics (CFD) based on moving overset grids were developed to study the hydrodynamic characteristics of an underwater autorotating rotor. The simulation results are in good agreement with the test results. The thrust and thrust coefficient of the underwater autorotating rotor were calculated by CFD simulation under different situations. The research demonstrates that rotational speed and thrust have a significant positive correlation with water velocity, pitch, and shaft back angle. In particular, the thrust coefficient scarcely varies with the shaft backward angle. An underwater autorotation rotor with a thin airfoil, negative torque, and a suitable number of blades can increase the thrust and thrust coefficient. The investigation is of significance in enriching the autorotation theory of rotors and helping to develop underwater autorotating rotors.
Study on Burning Surface Regression Algorithm under Erosive Burning Based on CT Images of Solid Rocket Motor Grain
Authors: Liu Shun , Lu Hongyi , Zhang Bin , Yang Yucheng , Sang Doudou
Published: December 2022

The presence of the erosive burning effect during the operation of a solid rocket motor (SRM) is one of the most important factors affecting the proper operation of the motor. To solve the effects of the operating process of the motor under erosive burning, a synthesis algorithm based on the actual CT images is proposed to combine the Level-set (LS) method with the minimum distance function (MDF) method for the simulation of the burning surface regression of the grain under erosive burning. The Hamilton–Jacobi control equation can be solved exactly for the discrete form of LS. To improve the computational efficiency of the LS method, the minimum distance field is initialized and only the distortion grid is adjusted during the reinitialization. The third-order TVD Runge–Kutta method is used to solve the problem of numerical oscillation and improve the calculation accuracy. The experiments simulate the burning process of the NAWC No. 6 partial grain under erosive burning, which can provide the main basis for the performance design of solid propellant. The experimental results show that the method has good applicability to three-dimensional complex grains. It can realize the simulation of grains under erosive burning and its calculation accuracy is high.
Experimental Study on Ice Accretion of Aviation Jet Fuel Tube
Authors: Zhu Chengxiang , Wang Jingxin , Bian Qingyong , Liu Chunyang , Zhao Ning , Zhu Chunling
Published: December 2022

Ice accretion on the inner surface of a fuel tube can fall off and potentially block the filters and small orifices, which thereby restricts the fuel flow to the engines during the long flying of the aircraft in cold conditions. This might cause the engines to shut down and pose a catastrophic safety threat. In this pursuit, the present study evaluates the effects of fuel temperature, entrained water concentration, and duration on the accretion of ice in flowing super-saturated RP-3 aviation jet fuel. A methodology for the quantitative mixing of water mist with fuel for accurately controlling water concentration was proposed. The different kinds of accreted ice, ‘fluffy’ and ‘pebbly’, were observed. As the distance of flow increased, a non-uniform distribution of ice on the cross-sectional area was noted. The amount of ice accretion increased with a decrease in the temperature from −2 °C and −12 °C, and with an increase in entrained water concentration. Besides, the amount of ice accretion showed an increasing trend as time went on and became stable after 2 h. Our experimental results can assist to gain a better understanding of the ice accretion process in flowing super-saturated fuels and may serve as a basis for the design of the aircraft fuel system and airworthiness certification.
Implementation of Fuel Cells in Aviation from a Maintenance, Repair and Overhaul Perspective
Authors: Hoff Tim , Becker Florian , Dadashi Alireza , Wicke Kai , Wende Gerko
Published: December 2022

Hydrogen is one of the most promising power sources for meeting the aviation sector’s long-term decarbonization goals. Although on-board hydrogen systems, namely, fuel cells, are extensively researched, the maintenance, repair and overhaul (MRO) perspective remains mostly unaddressed. This paper analyzes fuel cells from an MRO standpoint, based on a literature review and comparison with the automotive sector. It also examines how well the business models and key resources of MRO providers are currently suited to provide future MRO services. It is shown that fuel cells require extensive MRO activities and that these are needed to meet the aviation sector’s requirements for price, safety and, especially, durability. To some extent, experience from the automotive sector can be built upon, particularly with respect to facility requirements and qualification of personnel. Yet, MRO providers’ existing resources only partially allow them to provide these services. MRO providers’ underlying business models must adapt to the implementation of fuel cells in the aviation sector. MRO providers and services should, therefore, be considered and act as enablers for the introduction of fuel cells in the aviation industry.
Development, Validation, and Evaluation of Partial PST Tractor Simulation Model for Different Engine Modes during Field Operations
Authors: Siddique Md. Abu Ayub , Baek Seung-Min , Baek Seung-Yun , Kim Yong-Joo , Lim Ryu-Gap
Published: December 2022

The objectives of this study are the development and verification of a simulation model of the partial PST (power-shift transmission) tractor based on actual field operations. The PST simulation model was verified for the asphalt driving condition, and performance was evaluated for asphalt driving, plow, and rotary tillage. In this study, the traditional, APS (Auto Power Shift) ECO, and APS power engine modes were used to analyze fuel consumption. The statistical analysis proved that the experimental and simulation results were in a linear relationship, with an accuracy of over 98%. Finally, the results suggested that users could utilize the 95-kW partial PST tractor in the APS ECO engine mode with higher fuel economy compared to the traditional and APS power modes.
Strigolactone (GR24) Application Positively Regulates Photosynthetic Attributes, Stress-Related Metabolites and Antioxidant Enzymatic Activities of Ornamental Sunflower (Helianthus annuus cv. Vincent’s Choice) under Salinity Stress
Authors: Ahsan Muhammad , Zulfiqar Hira , Farooq Muhammad Ansar , Ali Sajjad , Tufail Aasma , Kanwal Shamsa , Shaheen Muhammad Rashid , Sajid Mateen , Gul Hera , Jamal Aftab , Saeed Muhammad Farhan , Mancinelli Roberto , Radicetti Emanuele
Published: December 2022

Strigolactones, a new group of phytohormones, are reported to improve plant tolerance to multiple abiotic stresses. A pot experiment was conducted to investigate the impact of synthetic strigolactone (GR24 at 0.001, 0.01 and 0.1 mg L−1) application on ornamental sunflowers (Helianthus annuus cv. Vincent’s Choice) grown under salt stress (150 mM NaCl). Salt stress was applied after 14 days, and SL was applied 25 days seed sowing. The results showed that amongst various GR24 concentrations, 0.01 mg L−1 proved to be superior, as it enhanced the photosynthetic rate (9.29%), transpiration rate (0.76%), stomatal conductance (77.5%), total soluble protein (0.55%) and K+ (14.63% in roots; 14.87% in shoots) and Ca2+ (12.63% in roots; 11.48% in shoots) contents under control conditions. Similarly, the leaf turgor potential (Ψp), osmotic potential (Ψs) and free proline, glycinebetaine (GB), superoxide dismutase (SOD), catalase (CAT) and peroxide (POD) contents increased by 58.17, 89.95, 159.04, 101.54, 74.42, 175.68 and 53.62%, respectively, under salt stress conditions. The leaf water potential (Ψw) decreased (−0.14%) and the malondialdehyde (MDA) content increased (16.65%) when treated with the 0.001 mg L−1 GR24 level. Meanwhile, hydrogen peroxide (H2O2) and Na+ concentrations in roots and shoots increased by 62.53%, 74.66% and 38.55% under saline conditions with a GR24 level of 0 mg L−1. Regarding the plant biomass, a GR24 level of 0.01 mg L−1 with salt stress greatly decreased the root (−47.27% and −50.45%) and shoot (−44.79% and −59.42%) fresh and dry weights, respectively, compared to control conditions. These results reveal that exogenously applied GR24 might be an effective way to mitigate the perilous impacts of salt stress in ornamental sunflower production. It is suggested that the use of molecular techniques to study different processes in which GR24 could play a vital part in various commercial floricultural crops is extremely imperative and can open novel horizons for future investigations in this exhilarating field of plant hormones.
Feature Extraction on the Difference of Plant Stem Structure Based on Ultrasound Energy
Authors: Lv Danju , Zi Jiali , Huang Xin , Gao Mingyuan , Xi Rui , Li Wei , Wang Ziqian
Published: December 2022

Plant growth is closely related to the structure of its stem. The ultrasonic echo signal of the plant stem carries much information on the stem structure, providing an effective means for analyzing stem structure characteristics. In this paper, we proposed to extract energy features of ultrasonic echo signals to study the structure of the plant stem. Firstly, it is found that there are obvious different ultrasonic energy changes in different kinds of plant stems whether in the time domain or the frequency domain. Then, we proposed a feature extraction method, density energy feature, to better depict the interspecific differences of the plant stems. In order to evaluate the extracted 24-dimensional features of the ultrasound, the information gain method and correlation evaluation method were adopted to compute their contributions. The results showed that the mean density, an improved feature, was the most significant contributing feature in the four living plant stems. Finally, the top three features in the feature contribution were selected, and each two of them composed as 2-D feature maps, which have significant differentiation of the stem species, especially for grass and wood stems. The above research shows that the ultrasonic energy features of plant stems can provide a new perspective for the study of distinguishing the structural differences among plant stem species.
Different Response of Soil Microbial Carbon Use Efficiency in Compound of Feldspathic Sandstone and Sand
Authors: Zhang Yao , Wang Junqi , Chen Lan , Zhou Sha , Zhang Lu , Zhao Fazhu
Published: December 2022

The stoichiometry of efficient soil microbial carbon use is a sensitive index for measuring changes in soil quality and plays a crucial role in research on ecological stoichiometry in the soil nutrient cycle. To further understand the effect of feldspathic sandstone and sand compound ratios on microbial carbon use efficiency (CUE), we simulated the field conditions of the feldspathic sandstone-sand compound layer in the Mu Us sandy land and analyzed the soil C:N:P ratio, microbial biomass, extracellular enzyme activity, and microbial carbon use efficiency in soils with different compound ratios. The results demonstrated that an increase in the feldspathic sandstone content had insignificant effects on the soil C:N:P ratio. The maximum values for microbial biomass nitrogen (MBN) and microbial biomass phosphorus (MBP) were observed at compound ratios of 1:5 and 1:2, respectively. Calculations of microbial carbon use efficiency and vector analysis revealed that the microbial carbon use efficiency increased as the feldspathic sandstone content increased, P limitation existed in all compound soils, and soil with a 1:1 compound ratio may be substantially less limited. In conclusion, our research indicated that adding feldspathic sandstone to sand improved soil quality, and the compound ratio affected soil microorganisms; nevertheless, it did not significantly change soil nutrient restriction. Our study provides a theoretical basis for the development and utilization of desert land resources.
Microbial and Protease Fermentation of Mao-Tai Lees Alters Nutritional Composition and Promotes In Vitro Intestinal Proteolysis
Authors: Yi Siyu , Azad Md. Abul Kalam , Ji Yujiao , Liu Yang , Dou Mengying , Kong Xiangfeng
Published: December 2022

Mao-tai lees (ML) is a by-product produced in the process of Mao-tai liquor production and contains high levels of crude protein, starch and fiber, and large yield. Thus, the ML has the potential to become feedstuffs alternatives in livestock production. The present study evaluated the nutritional values of ML and fermented ML (FML), including the first stage (FML I; microbial fermentation), the second stage (FMTL II; microbial fermentation), and the final stage (FFML; microbial fermentation with proteases), and explored their effects on in vitro intestinal fermentation. The results showed that the FFML had higher contents of acid detergent fiber, acid detergent lignin, crude fiber, crude protein, neutral detergent fiber, starch, Vitamin B2, B6, and B12, whereas the FML II presented higher contents of calcium, copper, iron, manganese, magnesium, and Vitamin B1 compared with the other groups. Compared with the ML, the total free amino acids (FAAs) and total bioamine contents were higher in the FML II and FFML and had lower total hydrolyzed amino acids and total other free organic acids contents, among which the FFML had higher total FAAs and total bioamine contents. The FMLs had lower n-6:n-3 PUFA ratio compared with the ML; however, the FFML had lower n-6:n-3 PUFA ratio than the other groups. Furthermore, the FFML had higher concentrations of 1,7-diaminoheptane, isobutyrate, isovalerate, putrescine, and spermidine in vitro fermentation, suggesting that the FFML had greater proteolysis than the other groups. Collectively, these findings suggest that microbial fermentation with proteases could alter the nutritional composition and promote in vitro intestinal proteolysis of ML, which may be an effective way for promoting the protein utilization of ML. The study provides an effective potential strategy to develop novel feedstuff alternatives.
PLSR-Based Assessment of Soil Respiration Rate Changes under Aerated Irrigation in Relation to Soil Environmental Factors
Authors: Cui Jiapeng , Tan Feng
Published: December 2022

To ameliorate soil oxygen deficiencies around subsurface drip irrigation (SDI) drippers, aerated irrigation (AI) was introduced to supply aerated water to the soil through venturi installed in the SDI pipeline. The objectives of this study were to investigate the effect of AI on the soil respiration rate and the mechanism of regulation. The Daejeon experiment included two treatments: AI and unaerated SDI as a control check (CK), and used the National Soil Quality Zhanjiang Observation and Experiment Station as a platform to carry out a 2-year (2020–2021) positioning experiment. The effects on the soil respiration rate, soil temperature, soil water content, oxygen content, soil bacterial biomass and root biomass of the two treatments were established. The oxygen content, soil bacterial biomass and root biomass regression equation, using the partial least squares regression analysis (PLSR) algorithm and structural equation modeling (SEM), screened out the influence of soil respiration under AI treatment as the main soil environmental factor and driving mechanism of rate change. The results showed that compared with the control CK, the soil respiration rate, soil oxygen content, root biomass and soil bacterial biomass were significantly enhanced under AI treatment, the soil water content had a decreasing trend, and there was no significant difference in the effect on soil temperature between the different treatments. The regression fitting results showed that the soil respiration rate under both treatments was negatively correlated with soil temperature using a quadratic polynomial correlation, linearly correlated with the soil oxygen content, positively correlated with root biomass and soil bacterial biomass using power function and positively correlated with the soil water content using a cubic polynomial correlation. The PLSR and SEM results demonstrated that aerated irrigation technology could drive the increase in the soil respiration rate by changing the soil oxygen content, root biomass and bacterial biomass.
Automatic Disease Detection of Basal Stem Rot Using Deep Learning and Hyperspectral Imaging
Authors: Yong Lai Zhi , Khairunniza-Bejo Siti , Jahari Mahirah , Muharam Farrah Melissa
Published: December 2022

Basal Stem Rot (BSR), a disease caused by Ganoderma boninense (G. boninense), has posed a significant concern for the oil palm industry, particularly in Southeast Asia, as it has the potential to cause substantial economic losses. The breeding programme is currently searching for G. boninense-resistant planting materials, which has necessitated intense manual screening in the nursery to track the progression of disease development in response to different treatments. The combination of hyperspectral image and machine learning approaches has a high detection potential for BSR. However, manual feature selection is still required to construct a detection model. Therefore, the objective of this study is to establish an automatic BSR detection at the seedling stage using a pre-trained deep learning model and hyperspectral images. The aerial view image of an oil palm seedling is divided into three regions in order to determine if there is any substantial spectral change across leaf positions. To investigate if the background images affect the performance of the detection, segmented images of the plant seedling have been automatically generated using a Mask Region-based Convolutional Neural Network (RCNN). Consequently, three models are utilised to detect BSR: a convolutional neural network that is 16 layers deep (VGG16) model trained on a segmented image; and VGG16 and Mask RCNN models both trained on the original images. The results indicate that the VGG16 model trained with the original images at 938 nm wavelength performed the best in terms of accuracy (91.93%), precision (94.32%), recall (89.26%), and F1 score (91.72%). This method revealed that users may detect BSR automatically without having to manually extract image attributes before detection.
Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture
Authors: Shin Jaemyung , Mahmud Md. Sultan , Rehman Tanzeel U. , Ravichandran Prabahar , Heung Brandon , Chang Young K.
Published: December 2022

Introducing machine vision-based automation to the agricultural sector is essential to meet the food demand of a rapidly growing population. Furthermore, extensive labor and time are required in agriculture; hence, agriculture automation is a major concern and an emerging subject. Machine vision-based automation can improve productivity and quality by reducing errors and adding flexibility to the work process. Primarily, machine vision technology has been used to develop crop production systems by detecting diseases more efficiently. This review provides a comprehensive overview of machine vision applications for stress/disease detection on crops, leaves, fruits, and vegetables with an exploration of new technology trends as well as the future expectation in precision agriculture. In conclusion, research on the advanced machine vision system is expected to develop the overall agricultural management system and provide rich recommendations and insights into decision-making for farmers.
Chemical and Morphologic Characterization of Sylvite (KCl) Mineral from Different Deposits Used in the Production of Fertilizers
Authors: Castro-Suarez John R. , Colpas-Castillo Fredy , Taron-Dunoyer Arnulfo
Published: December 2022

In the present work, four (4) samples of sylvite (KCl) from different deposits in Canada, Belarus and Germany were analyzed in order to determine the differences between them in terms of chemical composition, morphology and impurities present. Different non-instrumental and instrumental techniques were used. A scanning electron microscope analysis showed that the particles are completely amorphous. Bueno mineral has particles with the largest area (with 91.4% particles larger than 0.50 mm), and the BPC mineral samples have those with the smallest area (with 49.9% particles smaller than 0.50 mm). The Bueno mineral has the highest angle of repose. Bueno mineral has the highest surface area and pore volume when compared to the other KCl minerals. On the other hand, the BPC KCl mineral presented a lower surface area and pore volume. The problem mineral has the highest percentage composition of K. Blanco mineral did not present Al, and the element Mo was not detected in the Blanco and Bueno mineral. The IR bands of O-H, C-N, N-H and C=O bonds were observed. These results are useful for the fertilizer industry. These differences can produce adverse effects in a subsequent application in fertilizer production processes. Such differences can be attributed to the origin of this mineral, the way it is obtained and exploited, or to the transport and storage process through the use of anticompacting additives due to the high hygroscopicity of the mineral.
Transmissible Effects of a Biochar Amendment to an Upper Soil Zone Upon an Associated Lower Zone, Including Attenuation of Soybean Cyst Nematode (Heterodera glycines)
Authors: Sinh Nguyen Van , Linh Doan Thi Truc , Phuong Nguyen Thi Kim , Ritz Karl , Toyota Koki
Published: December 2022

Mung bean residues stimulate the hatching of soybean cyst nematode (SCN). In our previous study, combined incorporation of mung bean residues and biochar into soil can be effective in suppression of the soybean cyst nematode (SCN), Heterodera glycines, in the upper layer soil. However, there are no data available as to whether such effects are transmissible, and could for example be manifest in subsoil zones where such incorporation is confined to topsoils, via water-based pathways. We evaluated the effects of leachate passage from a biochar-amended soil in an upper soil zone to a lower zone in a microcosm-based system, upon a range of physicochemical properties and density of SCN. Disturbed soil was filled in a total of 9 cylindrical cores with two layers. The upper layer (0–15 cm) was amended with biochar at rates equivalent to 0, 0.3% or 1.8%, with bulk density set at of 1.1 g cm−3. The lower layer (15–25 cm) without biochar amendment was compacted to 1.2 g cm−3. Mung beans were grown for two weeks and incorporated into the upper layer. Water was surface-applied to the cores 4, 6, and 8 weeks after mung bean incorporation. After 16 weeks, the upper and lower layer soils were separately collected and assayed. The presence of biochar in the upper layer reduced the abundance of free-living nematodes, mainly bacterivorous, but increased that of a predator genus Ecumenicus in this zone. In the lower layer of soil under a biochar-amended upper layer, available P and soluble cations were increased as were abundances of total nematodes including Ecumenicus, resulting in greater maturity index, basal and structure indices. Notably, SCN density was decreased in lower zones by more than 90% compared to zero-biochar controls. This demonstrates that the effects of biochar upon soil properties, including impacts on biota and plant pathogens, are transmissible.
Sunflower Seed Suction Stability Regulation and Seeding Performance Experiments
Authors: Zhao Xuan , Zhang Tao , Liu Fei , Li Na , Li Junru
Published: December 2022

The poor adsorption stability of the current air-suction sunflower seed-metering devices under high-speed operation leads to unstable seed adsorption posture, as well as increases in the multiple and miss indices. In order to improve the stability of seed adsorption, an air-suction sunflower seed-metering device based on structure-assisted stable suction posture was designed, the movement mechanism of the seed absorption process and the seed-feeding process is analyzed, following which mathematical models of the processes are established, and the key factors affecting the seeding performance were determined. Furthermore, the shape parameter equation of sunflower seeds is fitted, depending on the dimensions and shape parameters, which provides the design basis for the key components of the seed-metering device. Moreover, in order to optimize the seed-metering devices structure, taking the depth, width, and length of the seed suction grooves as experimental factors, as well as the qualified, multiple, and miss indices as evaluation indices, an orthogonal regression experiment considering three factors and three levels is carried out using the Box–Behnken experimental design. Finally, multiple regression models are established and extreme value theory is used to optimize the parameters of the influencing factors and obtain optimal parameter combinations. The optimal parameter combination is as follows: width of the suction groove, 10.5 mm; depth, 3 mm; and length, 23 mm. Results from verification experiments revealed the corresponding experimental indicators, the qualified index is 91.63%, the multiple index is 5.63%, and the miss index is 2.74%, thus meeting the requirements of effective sunflower seed sowing.
Hyperspectral Estimation of Winter Wheat Leaf Water Content Based on Fractional Order Differentiation and Continuous Wavelet Transform
Authors: Li Changchun , Xiao Zhen , Liu Yanghua , Meng Xiaopeng , Li Xinyan , Wang Xin , Li Yafeng , Zhao Chenyi , Ren Lipeng , Yang Chen , Jiao Yinghua
Published: December 2022

Leaf water content (LWC) is one of the important indicators of crop health. It plays an important role in the physiological process of leaves, participates in almost all physiological processes of crops, and is of great significance to the survival and growth of crops. Based on the hyperspectral (350–1350 nm) and LWC data (jointing, booting, flowering, and filling periods) of winter wheat in 2020 and 2021, this work proposed to transform and process the hyperspectral data by adopting fractional order differential and continuous wavelet transform, and took a differential spectrum, wavelet coefficients, and mixed variables (differential spectrum and wavelet coefficients) as input variables of the model and adopted Gaussian process regression (GPR), classification and regression decision tree (CART), and artificial neural network (ANN) methods to estimate the LWC of wheat in different growth periods. The results indicated that fractional differential and continuous wavelet transform could highlight the spectral characteristics of winter wheat canopy and improve its correlation with LWC. The three model variables had the best estimation effect on LWC in the flowering period, and the average values of R2 were 0.86 and 0.87 in modeling and verification, which indicated that the flowering period could be used as the best estimation period for LWC. Compared with the differential spectrum and wavelet coefficients, LWC estimation based on mixed variables performed best. The average values of R2 in modeling and verification were 0.78 and 0.79. Among them, the ANN model had the highest estimation accuracy, and the R2 in modeling and verification could reach 0.92 and 0.91. This showed that fractional differential and continuous wavelet transform could effectively promote the sensitivity of spectral information to LWC and enhance the prediction ability and stability of wheat LWC. The outcomes of the present study have the potential to provide new ideas for the water monitoring of crops.
Seasonal Changes Modulate the Rhizosphere of Desert Plant Species
Authors: Ahmad Maqshoof , Iqbal Zafar , Bushra  , Hussain Azhar , Abdullah Muhammad , Alataway Abed , Dewidar Ahmed Z. , Mattar Mohamed A.
Published: December 2022

Arid and semi-arid ecosystems are categorized as having degraded soils due to the limited availability of water and nutrients. The perennial shrubs in these regions have developed different ecological and physiological adaptations to cope with harsh conditions. The plant species vary in the chemical profile of their root exudates, which can induce variability in the microbial community in the rhizosphere. The present research has been conducted (i) to investigate the variation in composition, diversity, and structure of rhizosphere’s bacterial community of desert plants; (ii) to identify plant-specific effects on the rhizosphere microbial community structure; and (iii) to determine the influence of soil moisture on the rhizosphere’s microbial community and soil biological properties under stressful conditions. Ten desert plant species from the Cholistan desert were selected as test specimens. Bacterial communities from the rhizosphere of 10 plants of each species were explored. Soil samples were collected during monsoon (June–August) and dry months (March–May). Microbial community structure analyses were carried out through 16S rRNA sequencing by targeting V3 and V4 regions. Among tested plant species, the rhizosphere of Leptadenia pyrotechnica (S6 vs. S16), Aerva javanica (Burm. f.) Juss. ex Schult (S9 vs. S19), and Vachellia jacquemontii (Benth.) (S10 vs. S20) had greater microbial diversity in both seasons. Higher levels of microbial communities were found during monsoon season. Furthermore, Gammaproteobacteria were abundant in the rhizospheres of all studied plants during the monsoon season. In contrast, the rhizosphere was abundant with unidentified_Actinobacteria during the dry season. The rhizospheric soil was further analyzed for biological properties. The maximum microbial biomass carbon (165 mg kg–1) and microbial biomass nitrogen (6.7 mg kg–1) were found in the rhizosphere of Vachellia jacquemontii (Benth.) Benth during monsoon season. However, a minimum of microbial biomass carbon (119 mg kg–1) and microbial biomass nitrogen (4.2 mg kg–1) were found in the rhizosphere of Cleome pallida Kotschy during dry seasons. The diversified microbial community structure and biological properties enable desert plants to cope with adverse climate conditions.
Effects of Different Exogenous Organic Materials on Improving Soil Fertility in Coastal Saline-Alkali Soil
Authors: Zuo Wengang , Xu Lu , Qiu Meihua , Yi Siqiang , Wang Yimin , Shen Chao , Zhao Yilin , Li Yunlong , Gu Chuanhui , Shan Yuhua , Bai Yanchao
Published: December 2022

The coastal saline-alkali soil in eastern China is an important reserve arable land resource. Adding exogenous organic material is an effective way to improve soil fertility and promote the conversion of saline-alkali soil to agricultural soil. In this study, a field plot experiment was used to investigate the influences of different organic materials (vinegar residue, VR; sewage sludge, SS; vermicompost, VC) on the reduction in salinity-alkalinity barrier factors, the accumulation of soil organic carbon (SOC), and the improvement in soil fertility in saline-alkali soil. The results indicated that applying different types of exogenous organic materials reduced soil electrical conductivity (EC) and pH, promoted SOC accumulation, and increased the barley yield. With the same application rate, VR application was more beneficial in reducing soil EC and pH, accumulating SOC, and increasing barley yield compared to SS and VC applications. In particular, the barley yield with VR application was higher than that with SS and VC applications by 18.4% and 26.6% on average, respectively, during the two-year experiment. Correlation and path analysis revealed that the barley yield was significantly negatively correlated with soil barrier factors (EC and pH), but EC in SS and VC-treated soils had an indirect negative effect on barley yield, while EC in VR-treated soil had a direct negative effect (−2.24). In addition, the direct (−4.46) and indirect (5.39) contributions of SOC to barley yield were higher with VR than those with SS and VC, while the direct contribution of soil aggregate to barley yield was lower with VR than that with SS and VC. Therefore, compared with SS and VC applications, VR application led to a fast reduction in soil barrier factors and the rapid accumulation of SOC, which were more beneficial for increasing barley yields in saline-alkali soil.
Development of Loop-Mediated Isothermal Amplification Assay for the Rapid Detection of Pyrenophora graminea in Barley Seeds
Authors: Hu Zhangwei , Chen Liyifan , Du Chunmei , Liu Yaoxia , Yan Jiahui , Guo Qingyun , Yao Qiang
Published: December 2022

Barley leaf stripe, caused by Pyrenophora graminea, is an essential systemic seed-borne disease in barley worldwide. Barley is a major cereal crop in the Qinghai–Tibet Plateau, and barley production has been threatened by leaf stripe in this region, particularly in organic farming regions. Detecting the pathogen in infected barley seeds is crucial for managing barley leaf stripe. In this study, a loop-mediated isothermal amplification (LAMP) assay was developed to detect the pathogen based on primers designed based on the sequence of the pig 14 gene (GenBank: AJ277800) of P. graminea. The optimal concentrations of MgSO4, dNTPs, and enzymes in the LAMP reaction system were established as 10.0 mM, 1.0 mM, and 8 U in a 25 μL reaction volume, respectively. The established LAMP methods for detecting P. graminea were optimally performed at 63 °C for 70 min with high reliability. The minimum detection limit was 1 × 10−2 ng·μL−1 in the 25 μL reaction system. The specificity of LAMP for P. graminea was validated with eight fungal species. All DNA extracts from P. graminea-infected barley seeds with incubation, intact, and smashed treatments were applied in LAMP and confirmed to enable the detection of the pathogen. The LAMP assay in this study could facilitate the detection of P. graminea in barley seeds onsite, provide information for seed health certificates, and help decide on seed treatment in leaf stripe management.
Deficiencies of Secondary Nutrients in Crop Plants—A Real Challenge to Improve Nitrogen Management
Authors: Grzebisz Witold , Zielewicz Waldemar , Przygocka-Cyna Katarzyna
Published: December 2022

Secondary nutrient (e.g., calcium, magnesium, sulfur) deficiencies in crop plants disturb the nitrogen balance in the plants, thus reducing the overall yield. This hypothesis was analyzed based on the physiological functions of these nutrients, in relation to the uptake and utilization of N, in crop plants. Nitrogen uptake by plants requires a well-developed root system, the size of which depends on the supply of calcium. This process is largely controlled by the content of toxic aluminum in the soil, which can be mitigated through the application of lime and/or gypsum. In humid climates, the excessive uptake of calcium by plants occurs during water shortages; this process significantly interferes with N uptake. Magnesium, which affects plant growth throughout the growing season, can effectively control excessive calcium uptake. Magnesium deficiency can be ameliorated with soil- or foliar-applied fertilizers. These stages define the timing of plant sampling and determination of the N:S ratio, as an indicator of plant nutritional status. The application of Mg, S, or MgS facilitates higher productivity of fertilizer N by narrowing the N:Mg and N:S ratios in plants. The use of secondary nutrients can allow farmers to obtain high yields while reducing both production costs and environmental risks.
Effect of Low-Temperature Tolerant Rootstocks on the Growth and Fruit Quality of Watermelon in Semi-Forcing and Retarding Culture
Authors: Jang Yoonah , Moon Ji-Hye , Kim Sang-Gyu , Kim Taebok , Lee Oak-Jin , Lee Hee-Ju , Wi Seung-Hwan
Published: December 2022

Watermelon grafting is practiced in order to improve tolerance to poor environments such as low temperature. This study was conducted to investigate the effect of low-temperature tolerant bottle gourd (Lagenaria siceraria) rootstocks on the growth and fruit quality of watermelon in semi-forcing and retarding culture where plants were exposed to low or high temperature. Five bottle gourd accessions (FR79, IT207112, BG702, BG703, and FRD22) with low temperature tolerance were evaluated as rootstock for the watermelon scion ‘Sambokkul’. Non-grafted watermelon and watermelon grafted onto commercial rootstock ‘Shintozwa’ (Cucurbita maxima D. × C. moschata D.) or ‘Bullojangsaeng’ (L. siceraria) were used as controls. Watermelons were cultivated in spring (April to June, semi-forcing culture) and autumn (August to October, retarding culture). The responses to low-temperature, growth, yield, and fruit quality differed depending on the rootstocks and growing season. In semi-forcing culture, the monthly averages of daily and minimum temperature in April were, respectively, 13.4 and 1.5 °C. Although the low temperature of the early growth stage suppressed the initial growth of watermelons, grafting mitigated the low-temperature stress. The fruit quality of non-grafted watermelons was greater, but the fruit mass was the lowest (4.8 kg). Grafting onto ‘Shintozwa’ increased the fruit weight (7.0 kg) but reduced the fruit quality. Grafting onto bottle gourd rootstocks had high affinity, good root growth, tolerance to low temperature, and little effect on fruit quality. In retarding culture, the temperature conditions in early and late growth were very high and low, respectively. The growth and fruit quality of grafted watermelons were not superior to those of non-grafted watermelons. Accordingly, these results suggest that watermelon grafting onto the bottle gourd rootstocks may increase the low-temperature tolerance, especially in the early growth stage, and the marketable yield without a reduction in fruit quality. The most promising accession for this purpose was found to be ‘FR79’.
RicePedigree: Rice Pedigree Database for Documentation and Assistance in Rice Breeding
Authors: Woo Dong-U , Lee Yejin , Jeon Ho-Hwi , Park Halim , Park Jin-Hwa , Choi Sung-Hoon , Lee Chang-Min , Mo Youngjun , Kang Yang-Jae
Published: December 2022

For the purpose of breeding documentation, researchers and breeders kept handwritten records of the breeding history, including parental information and breeding methods. The cultivars were used again as parents for further breeding, and modern cultivars of rice have a wide range of alleles from many generations of parents and ancestors. To understand such a breeding history, it is necessary to ask around for relevant information, which is then usually documented in Excel or Word by multiple breeders or breeding institutes. Here, we constructed RicePedigree, which contains the breeding history of rice based on the documents provided by the Rural Development Administration (RDA) in Korea. We devised a simple method for collecting a breeding history and storing it in a database. RicePedigree is a web-based application on the database that facilitates researchers’ and breeders’ utilization of the breeding history of rice. Based on the query cultivar name, it will return a hierarchical tree of breeding histories and a list of cultivars and breeding lines that contain query cultivars in their breeding histories. This app would be a good way to review and keep track of information about current and future cultivars.