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Search Results (5,071)

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Keywords = soybean

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13 pages, 6215 KiB  
Article
Reducing Washout of Proteins from Defatted Soybean Flakes by Alkaline Extraction: Fractioning and Characterization
by Giovana Wittmann, Lovaine Silva Duarte, Marco Antônio Záchia Ayub and Daniele Misturini Rossi
Sustainability 2024, 16(14), 6238; https://doi.org/10.3390/su16146238 (registering DOI) - 22 Jul 2024
Viewed by 179
Abstract
Human health, sustainable development, numerous environmental issues, and animal welfare are increasingly driving research and development of plant-based protein products that can serve as meat substitutes. This trend is expected to continue in the coming years due to growing consumer awareness, with people [...] Read more.
Human health, sustainable development, numerous environmental issues, and animal welfare are increasingly driving research and development of plant-based protein products that can serve as meat substitutes. This trend is expected to continue in the coming years due to growing consumer awareness, with people gradually shifting from animal-based foods to more sustainable plant-based options. Soy proteins are a valuable source of plant proteins and are widely used in human and animal diets due to their nutritional value and health benefits. In this study, soybean protein extraction by two methods was compared: water extraction (lower salt content) and Tris-HCl extraction (higher salt content), aiming to characterize the resulting protein fractions. These fractions were studied using differential precipitation based on the isoelectric point. Protein identification by SDS-PAGE, scanning electron microscopy (SEM) for cellular structure assessment, and Fourier-transform infrared spectroscopy (FTIR) were used to determine residual protein left in the solid fraction after extraction using the two methods. Electrophoresis assays revealed the presence of the four main protein fractions (2S, 7S, 11S, and soy whey proteins) in the defatted soybean flakes, establishing the protein profile of Brazilian soybeans and for the two main waste streams of the production process—spent flakes and whey. The separation of fractions was carried out by differential precipitation. FTIR analysis indicated higher residual protein levels in solid residues after the water extraction method compared to the Tris-HCl extraction method. SEM analysis revealed the removal of protein bodies in both extraction methods and the presence of residual oil-containing bodies. Both methodologies are viable alternatives for the industrial separation of soybean protein fractions. Differential precipitation could be implemented to produce isolated products and improve the nutritional profile, increase process yield thus generating less industrial waste and driving the process towards environmental sustainability. Full article
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<p>Scheme of the general process used to obtain soybean protein isolate.</p>
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<p>Scheme of the differential precipitation process for soybean protein fractions.</p>
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<p>SDS-PAGE gels with lanes: (MW) molecular weight, (IW) industrial whey, (+50_IW) industrial whey filtration retentate (+50 kDa), and (−50_IW) industrial whey filtration permeate (−50 kDa) in staining with (<b>a</b>) Coomassie Brilliant Blue and (<b>b</b>) silver nitrate.</p>
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<p>SDS-PAGE gel with lanes (DF_WE_11S): 11S fraction from water extraction of defatted flakes, (MW) molecular weight; (DF_THE_11S) 11S fraction from Tris-HCl extraction of defatted flakes, (SF_WE_11S) 11S fraction from water extraction of spent flake; (DF_WE_7S) 7S fraction from water extraction of defatted flakes; and (DF_THE_7S) 7S fraction from Tris-HCl extraction of defatted flakes.</p>
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<p>SDS-PAGE gel with lanes: (DF_WE_Int) intermediate fraction from water extraction of defatted flakes; (DF_THE_Int) intermediate fraction from Tris-HCl extraction of defatted flakes, (MW) molecular weight; (SF_WE_Int) intermediate fraction from water extraction of spent flakes; (DF_WE_LW) laboratory whey fraction from water extraction of defatted flakes; (DF_THE_LW) laboratory whey fraction from Tris-HCl extraction of defatted flakes; and (SF_WE_LW) laboratory whey fraction from water extraction of spent flakes.</p>
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<p>FTIR spectra of the solid residue of water extraction (red) and Tris-HCl extraction (blue) with defatted flakes as starting material.</p>
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<p>SEM images: (<b>a</b>) soybean defatted flakes at 500× magnification, (<b>b</b>) defatted flakes at 1000× magnification, (<b>c</b>) defatted flakes at 2500× magnification, (<b>d</b>) solid residue of water extraction defatted flakes at 500× magnification, (<b>e</b>) solid residue of water extraction defatted flakes at 1000× magnification, (<b>f</b>) solid residue of water extraction defatted flakes at 2500× magnification, (<b>g</b>) solid residue of Tris-HCl extraction defatted flakes at 500× magnification, (<b>h</b>) solid residue of Tris-HCl extraction defatted flakes at 1000× magnification, (<b>i</b>) solid residue of Tris-HCl extraction defatted flakes at 2500× magnification.</p>
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<p>SEM images: (<b>a</b>) solid residue of water extraction of defatted flakes, (<b>b</b>) solid residue of Tris-HCl extraction of defatted flakes, and (<b>c</b>) channel-like structures in the solid residue of Tris-HCl extraction of defatted flakes.</p>
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13 pages, 1469 KiB  
Article
The Biostimulant Potential of Clove Essential Oil for Treating Soybean Seeds
by Joao Paulo Costa, Vinícius Guimarães Nasser, Willian Rodrigues Macedo, Mario Ferreira Conceição Santos and Geraldo Humberto Silva
Agriculture 2024, 14(7), 1202; https://doi.org/10.3390/agriculture14071202 - 22 Jul 2024
Viewed by 177
Abstract
Increasing soybean productivity can be achieved by treating seeds with biostimulants. To this end, an investigation was conducted into the potential of a formulation prepared with clove es-sential oil (CEO) diluted in soybean oil for seed treatment. Soybean seeds were treated with CEO [...] Read more.
Increasing soybean productivity can be achieved by treating seeds with biostimulants. To this end, an investigation was conducted into the potential of a formulation prepared with clove es-sential oil (CEO) diluted in soybean oil for seed treatment. Soybean seeds were treated with CEO concentrations between 0.5 to 3.0 mL/L, and subjected to germination, vigor, and sanity analyses. The CEO at 1.6 mL/L exhibited favorable outcomes regarding germination, root length, and re-duced fungal infection. In this way, a two-crop field experiment evaluated soybean seeds treated with CEO at 1.6 mL/L. Soybean seeds treated with CEO in the field in 2021/2022 were not different from the controls. However, in 2019/2020, there was a higher percentage of emergence, nodulation, and production of 749 kg/ha more than in the industrial treatment. These results highlight the potential use of CEO as a biostimulant. Full article
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<p>Heatmap generated using Euclidean distance for metabolite clustering with significant differences between groups (<span class="html-italic">p</span> &lt; 0.05). The columns represent the samples from each treatment (green = industrial treatment; blue = soybean oil; red = CEO). Each line represents a metabolite. The colored squares (heat map) represent the abundance of metabolites, where dark red is the highest abundance and dark blue is the lowest.</p>
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<p>Multivariate principal component analysis (PCA) and PERMANOVA test of metabolic profiles found in soybean leaf extracts whose seeds were subjected to CEO, soybean oil, and industrial treatment.</p>
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17 pages, 3245 KiB  
Article
Evaluation of the Impact of Chemical Mutagens on the Phenological and Biochemical Characteristics of Two Varieties of Soybean (Glycine max L.)
by Anas Hamisu, Bhupendra Koul, Ananta Prasad Arukha, Saleh Al Nadhari and Muhammad Fazle Rabbee
Life 2024, 14(7), 909; https://doi.org/10.3390/life14070909 (registering DOI) - 22 Jul 2024
Viewed by 165
Abstract
Mutagenic effectiveness and efficiency are the most important factors determining the success of mutation breeding, a coherent tool for quickly enhancing diversity in crops. This study was carried out at Lovely Professional University’s agricultural research farm in Punjab, India, during the year 2023. [...] Read more.
Mutagenic effectiveness and efficiency are the most important factors determining the success of mutation breeding, a coherent tool for quickly enhancing diversity in crops. This study was carried out at Lovely Professional University’s agricultural research farm in Punjab, India, during the year 2023. The experimental design followed a randomized complete block design (RCBD) with three replications. The experiment aimed to assess the effect of three chemical mutagens, sodium azide (SA), ethyl methyl sulphonates (EMSs), and methyl methane sulfonate (MMS), at three different concentrations (0.2%, 0.4%, and 0.6%), in SL958 and SL744 soybean varieties to select the mutant exhibiting the highest yield. The data were collected and analysed using a two-way ANOVA test through SPSS software (version 22), and the means were separated using Duncan’s multiple range test (DMRT) at the 5% level of significance. Between the two varieties, the highest seed germination percentage (76.0% seedlings/plot) was recorded in SL958 (0.4% SA), while the lowest (30.33% seedlings/plot) was observed in 0.6% MMS as compared to the control (53% and 76% in SL744 and SL958 at 10 days after sowing, respectively). Several weeks after sowing, the average plant height was observed to be higher (37.84 ± 1.32 cm) in SL958 (0.4% SA) and lower (20.58 ± 0.30 cm) in SL744 (0.6% SA), as compared to the controls (SL958: 26.09 ± 0.62 cm and SL744: 27.48 ± 0.74 cm). The average leaf count was the highest (234.33 ± 3.09 tetrafoliate leaves/plant) in SL958 (0.4% SA) while it was the lowest (87 leaves/plant) in 0.6% MMS as compared to the control (SL744 180.00 ± 1.63 and SL958 160.73 ± 1.05). The highest total leaf areas recorded in the SL958 and SL744 M1plants were 3625.8 ± 1.43 cm2 and 2311.03 ± 3.65 cm2, respectively. Seeds of the SL958 variety treated with 0.4% SA resulted in the development of tetrafoliate leaves with a broad leaf base and the maximum yield (277.55 ± 1.37 pods/plant) compared to the narrow pentafoliate leaves obtained through the treatment with EMS. Meanwhile, in the SL744 variety, the same treatment led to tetrafoliate leaves with a comparatively lower yield of 206.54 ± 23.47 pods/plant as compared to the control (SL744 164.33 ± 8.58 and SL958 229.86 ± 0.96). The highest protein content (47.04 ± 0.87% TSP) was recorded in the SL958 (0.4% SA) M2 seeds followed by a content of 46.14 ± 0.64% TSP in the SL744 (0.4% SA) M2 seeds, whereas the lowest content (38.13 ± 0.81% TSP) was found in SL958 (0.6% MMS). Similar observations were recorded for the lipid and fibre content. The 0.4% SA treatment in SL958 proved to be efficient in generating the highest leaf area (tetrafoliate leaves) and a reasonable yield of M1 (the first generation after mutation) plants. Full article
(This article belongs to the Special Issue Effects of Environmental Factors on Challenges of Plant Breeding)
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<p>Field layout (8 × 60 m) and experimental design using RBD. V1: variety 1 (SL744), V2: variety 2 (SL958), C: control. Chemical<sub>xx</sub> (xx = 0.2, 0.4, 0.6%), EMS: ethyl methane sulfonate, MMS: methyl methane sulfonate, SA: sodium azide.</p>
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<p>Effect of chemical mutagens on seed germination percentage (%). (<b>A</b>) Effect on SL744 soybean varieties. (<b>B</b>) Effect on SL958 soybean varieties. DAS = Days after sowing.</p>
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<p>(<b>A</b>) Effect of different concentrations of three mutagens on the morphology of soybean (<span class="html-italic">Glycine max</span> L.) variety SL958 at 12 WAS. Mutagen I: Ethyl methane sulfonate (<b>a</b>) 0.2%, (<b>b</b>) 0.4%, (<b>c</b>) 0.6%. Mutagen II: Methyl methane sulfonate (<b>d</b>) 0.2%, (<b>e</b>) 0.4%, (<b>f</b>) 0.6%. Mutagen III: Sodium azide (<b>g</b>) 0.2%, (<b>h</b>) 0.4%, (<b>i</b>) 0.6%. (<b>C1</b>) Control: SL958 (without mutagen treatment). (<b>B</b>) Effect of different concentrations of three mutagens on the morphology of SL744 soybean (<span class="html-italic">Glycine max</span> L.) variety at 12 WAS. Mutagen I: Ethyl methane sulfonate (<b>j</b>) 0.2%, (<b>k</b>) 0.4%, (<b>l</b>) 0.6%. Mutagen II: Methyl methane sulfonate (<b>m</b>) 0.2%, (<b>n</b>) 0.4%, (<b>o</b>) 0.6%. Mutagen III: Sodium azide (<b>p</b>) 0.2%, (<b>q</b>) 0.4%, (<b>r</b>) 0.6%. (<b>C2</b>) Control: SL744 (without mutagen treatment).</p>
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25 pages, 9463 KiB  
Article
Impact of Structural Parameters on the Collision Characteristics and Coefficient of Restitution of Soybean Particles on Harvester’s Cleaning Screens
by Xiaohu Guo, Shiguo Wang, Shuren Chen, Bin Li, Zhong Tang and Yifan Hu
Agriculture 2024, 14(7), 1201; https://doi.org/10.3390/agriculture14071201 - 21 Jul 2024
Viewed by 362
Abstract
Inadequate parameter design of the cleaning device in soybean combine harvesters leads to elevated levels of machine harvesting losses and impurity rates. To provide fundamental data for the optimization of structural parameters of soybean cleaning sieves, it is of great significance to study [...] Read more.
Inadequate parameter design of the cleaning device in soybean combine harvesters leads to elevated levels of machine harvesting losses and impurity rates. To provide fundamental data for the optimization of structural parameters of soybean cleaning sieves, it is of great significance to study the collision and bouncing characteristics of soybeans on the cleaning sieve surface and the impact of parameters on the coefficient of restitution (COR). The current study designed a collision platform, using soybeans at the harvest stage as the research subject. The experimental factors included drop height, wall inclination angle, wall movement speed, and wall material. Through single-factor experiments and orthogonal experiments, the effects of different collision parameters on the rebound trajectory and COR of soybeans were investigated. This study focuses on soybeans at the harvest stage as the test subjects. Experiments were conducted on a collision platform and recorded with a high-speed camera to capture the three-dimensional motion trajectories of the soybeans using the principle of specular reflection. Through single-factor experiments, the jumping characteristics of the soybeans on sieve surfaces with different motion characteristics were analyzed. The impact of drop height (400–650 mm), wall inclination angle (8–13°), wall movement speed (0.6–1.1 m/s), and wall material (stainless steel plates and polyurethane plates) on the coefficient of restitution (COR) was calculated and clarified. Multi-factor orthogonal experiments were conducted to determine the significance order of the different factors affecting the COR. Three-dimensional models of the soybeans and the collision platform were constructed using SolidWorks software, and the collision between the soybeans and the cleaning wall was simulated using EDEM software. The micro-forces and energy transfer during the soybean collision were analyzed. The results indicated that the COR of soybeans decreases as the drop height increases, but increases with wall inclination angle and wall movement speed. Additionally, the COR is higher when the soybeans collide with stainless steel plates compared to polyurethane plates. The order of influence of the four factors on the COR were: wall material > wall inclination angle > wall speed > drop height. This study provides important reference value for the efficient and low-loss design of cleaning devices. Full article
(This article belongs to the Section Agricultural Technology)
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<p>Basic Dimensions of Soybeans.</p>
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<p>Soybean–wall collision platform.</p>
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<p>Modeling process and physical model of soybeans.</p>
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<p>Simplified collision platform in EDEM.</p>
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<p>High-speed image processing flowchart.</p>
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<p>Images of the soybean colliding with the wall at different times: before (<b>a</b>), during (<b>b</b>), and after (<b>c</b>).</p>
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<p>Top view of the soybean collision platform.</p>
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<p>Soybean center of mass position.</p>
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<p>Schematic diagram of marking method for calculating angular velocity.</p>
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<p>Force Curve of Soybeans.</p>
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<p>Energy changes during soybean collision process.</p>
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<p>Torque and rotational energy of soybeans.</p>
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<p>Influence of wall movement speed on soybean trajectory.</p>
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<p>Influence of wall inclination angle on soybean trajectory.</p>
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<p>Influence of wall inclination angle on soybean angular velocity.</p>
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<p>Influence of wall speed on soybean angular velocity.</p>
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<p>Variation of COR with drop height.</p>
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<p>Variation of COR with wall inclination angle.</p>
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<p>Variation of COR with wall speed.</p>
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<p>Rebound height of soybean colliding with stainless steel plate and polyurethane plate.</p>
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<p>Multi-factor range analysis chart.</p>
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16 pages, 1265 KiB  
Article
The Asymmetric Tail Risk Spillover from the International Soybean Market to China’s Soybean Industry Chain
by Shaobin Zhang and Baofeng Shi
Agriculture 2024, 14(7), 1198; https://doi.org/10.3390/agriculture14071198 - 21 Jul 2024
Viewed by 275
Abstract
China is the largest soybean importer and consumer in the world. Soybean oil is the most-consumed vegetable oil in China, while soybean meal is the most important protein feed raw material in China, which affects the costs of animal husbandry. Volatility in the [...] Read more.
China is the largest soybean importer and consumer in the world. Soybean oil is the most-consumed vegetable oil in China, while soybean meal is the most important protein feed raw material in China, which affects the costs of animal husbandry. Volatility in the international soybean market would generate risk spillovers to China’s soybean industrial chain. This paper analyzed the channel of risk spillover from the international soybean market to China’s soybean industry chain and the asymmetry of the risk spillover. The degree of risk spillover from the international soybean market to the Chinese soybean industry chain was measured by the Copula–CoVaR model. The moderating role of inventory and demand in asymmetric risk spillovers was analyzed by quantile regression. We draw the following conclusions: First, the international soybean market impacts China’s soybean industry chain through soybeans rather than soybean meal and oil. The price fluctuation of China soybean market is obviously lower than that of the international soybean market. Second, there are apparent asymmetric risk spillovers from the international soybean market to China’s soybean industry chain, especially the soybean meal market. Third, increasing the Chinese soybean inventory and growing demand could effectively prevent the downside risk spillover from international markets to China’s soybean market. This also explains the asymmetry of risk spillovers. The research enriches the research perspective on food security, and the analysis of risk spillover mechanisms provides a scientific basis for relevant companies to develop risk-management strategies. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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<p>Price trend.</p>
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<p>The value of VaR. <b>Note:</b> <span class="html-italic">Soym</span> and <span class="html-italic">Soyo</span> represent China’s soybean meal and soybean oil markets, respectively. <span class="html-italic">Swinef</span>, <span class="html-italic">Eggf</span>, and <span class="html-italic">Meatbf</span> represent Chinese swine, eggfowl, and meat bird compound feeds, respectively. <span class="html-italic">Esoyo</span> represents Chinese edible soybean oil.</p>
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<p>Risk spillover from the Chinese soybean market to the international soybean market.</p>
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23 pages, 11618 KiB  
Article
Identification of Insect Pests on Soybean Leaves Based on SP-YOLO
by Kebei Qin, Jie Zhang and Yue Hu
Agronomy 2024, 14(7), 1586; https://doi.org/10.3390/agronomy14071586 - 20 Jul 2024
Viewed by 347
Abstract
Soybean insect pests can seriously affect soybean yield, so efficient and accurate detection of soybean insect pests is crucial for soybean production. However, pest detection in complex environments suffers from the problems of small pest targets, large inter-class feature similarity, and background interference [...] Read more.
Soybean insect pests can seriously affect soybean yield, so efficient and accurate detection of soybean insect pests is crucial for soybean production. However, pest detection in complex environments suffers from the problems of small pest targets, large inter-class feature similarity, and background interference with feature extraction. To address the above problems, this study proposes the detection algorithm SP-YOLO for soybean pests based on YOLOv8n. The model utilizes FasterNet to replace the backbone of YOLOv8n, which reduces redundant features and improves the model’s ability to extract effective features. Second, we propose the PConvGLU architecture, which enhances the capture and representation of image details while reducing computation and memory requirements. In addition, this study proposes a lightweight shared detection header, which enables the model parameter amount computation to be reduced and the model accuracy to be further improved by shared convolution and GroupNorm. The improved model achieves 80.8% precision, 66.4% recall, and 73% average precision, which is 6%, 5.4%, and 5.2%, respectively, compared to YOLOv8n. The FPS reaches 256.4, and the final model size is only 6.2 M, while the number of computational quantities of covariates is basically comparable to that of the original model. The detection capability of SP-YOLO is significantly enhanced compared to that of the existing methods, which provides a good solution for soybean pest detection. SP-YOLO provides an effective technical support for soybean pest detection. Full article
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<p>Example of labeling soybean pests using LabelImg.</p>
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<p>Example of labeling soybean pests using LabelImg.</p>
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<p>Distribution of the true bounding boxes of the targets in the INSECT_SOYBEAN dataset.</p>
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<p>General structure and module design of YOLOv8.</p>
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<p>General structure and module design of SP-YOLO.</p>
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<p>The structure of FasterNet and the structure of FasterBlock.</p>
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<p>The structure of PConvGLU.</p>
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<p>The structure of the LSD.</p>
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<p>Comparison of the evaluation indicator chart of YOLOv8 and SP-YOLO.</p>
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<p>Comparison of the YOLOv8 and SP-YOLO recognition effect. (<b>a</b>) Heat map using HiRes-CAM of YOLOv8n. (<b>b</b>) Chart of the predicted results of YOLOv8n. (<b>c</b>) Heat map using HiRes-CAM of SP-YOLO. (<b>d</b>) Chart of the predicted results of SP-YOLO. (<b>e</b>) Original images.</p>
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<p>Comparison of the YOLOv8 and SP-YOLO recognition effect. (<b>a</b>) Heat map using HiRes-CAM of YOLOv8n. (<b>b</b>) Chart of the predicted results of YOLOv8n. (<b>c</b>) Heat map using HiRes-CAM of SP-YOLO. (<b>d</b>) Chart of the predicted results of SP-YOLO. (<b>e</b>) Original images.</p>
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17 pages, 13436 KiB  
Article
The Influence of the Distribution Law and Uniformity of a Threshed Mixture with the Working Parameters of a Soybean Threshing Device
by Yifan Hu, Zhong Tang, Shiguo Wang, Bin Li, Xiaohu Guo and Shuren Chen
Agronomy 2024, 14(7), 1581; https://doi.org/10.3390/agronomy14071581 - 20 Jul 2024
Viewed by 179
Abstract
Soybean plants cultivated using mulched drip irrigation planting technology have the following characteristics during the harvest period: green stems and leaves, and a high straw/grain ratio. Moreover, the threshing device of a soybean combine harvester is difficult to adapt to, resulting in an [...] Read more.
Soybean plants cultivated using mulched drip irrigation planting technology have the following characteristics during the harvest period: green stems and leaves, and a high straw/grain ratio. Moreover, the threshing device of a soybean combine harvester is difficult to adapt to, resulting in an increase in the accumulation and unevenness of the threshed mixture. This leads to an increase in impurity content and the loss rate. We conducted a single-factor experiment on a self-developed longitudinal/axial-flow soybean threshing and separation test bench, employing drum speed, feeding rate, and threshing clearance as experimental factors. The influence of the soybean threshing and separation device’s working parameters on the distribution and uniformity of the threshed mixture in the axial and radial directions of the drum was explored through experiments. The results showed that the mass of the threshed mixture and soybean seeds showed a trend of first rapidly increasing and then slowly decreasing in the axial direction of the drum. Additionally, the mass showed a distribution feature of large values on both sides and small values in the middle in the radial direction. A lower drum speed, greater threshing clearance, and a smaller feeding rate make the radial distribution of a threshed mixture more uniform. Based on the combination of the crushing rate and unthreshed rate, the optimal working parameter combination was determined to be as follows: a drum speed of 500 r/min, a feeding rate of 6 kg/s, and a threshing clearance of 25 mm. The findings of this research offer valuable insights for the structural optimization and design enhancement of threshing and cleaning mechanisms within soybean combine harvesters. Full article
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
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<p>Soybean plants maintained based on the mulching drip irrigation planting mode.</p>
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<p>Characteristics of green stems of soybean at the harvest stage (<b>a</b>) and threshing loss (<b>b</b>).</p>
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<p>Structural diagram of the longitudinal/axial-flow soybean threshing device.</p>
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<p>Structural diagram of the distribution of axial and radial directions of the material box. (<b>a</b>) Axial direction of the drum. (<b>b</b>) Radial direction of the drum.</p>
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<p>Longitudinal/axial-flow soybean threshing test bench.</p>
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<p>The distribution of the threshed mixture in the material boxes.</p>
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<p>The constituents of the threshed mixture. (<b>a</b>) Soybean seeds, (<b>b</b>) heavy impurities, and (<b>c</b>) light impurities.</p>
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<p>The three-dimensional distribution of the material’s weight. (<b>a</b>) Mass distribution of threshed mixture. (<b>b</b>) Mass distribution of soybean seeds.</p>
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<p>The mass distribution of the threshed mixture for different drum speeds. (<b>a</b>) Axial distribution curves. (<b>b</b>) Radial distribution curves.</p>
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<p>The distribution of seed masses for different drum speeds. (<b>a</b>) Axial distribution curves. (<b>b</b>) Radial distribution curves.</p>
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<p>The mass distribution of the threshed mixture for different feeding rates. (<b>a</b>) Axial distribution curves. (<b>b</b>) Radial distribution curves.</p>
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<p>The distribution of seed masses for different feeding rates. (<b>a</b>) Axial distribution curves. (<b>b</b>) Radial distribution curves.</p>
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<p>The mass distribution of the threshed mixture for different threshing clearances. (<b>a</b>) Axial distribution curves. (<b>b</b>) Radial distribution curves.</p>
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<p>The distribution of seed masses for different threshing clearances. (<b>a</b>) Axial distribution curves. (<b>b</b>) Radial distribution curves.</p>
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<p>Stacked bar charts of the mass distribution of various components in the threshed mixture. (<b>a</b>) Stacked chart of axial distribution of material. (<b>b</b>) Stacked chart of radial distribution of material.</p>
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<p>The fitting curves of the threshed mixture’s distribution. (<b>a</b>) Axial distribution of threshed mixture, (<b>b</b>) radial distribution of threshed mixture, (<b>c</b>) axial distribution of soybean seeds, (<b>d</b>) radial distribution of soybean seeds, (<b>e</b>) axial distribution of impurities, and (<b>f</b>) radial distribution of impurities.</p>
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21 pages, 4007 KiB  
Article
Juvenile/Peripubertal Exposure to Omega-3 and Environmental Enrichment Differentially Affects CORT Secretion and Adulthood Stress Coping, Sociability, and CA3 Glucocorticoid Receptor Expression in Male and Female Rats
by Julie Raymond, Alexandre Morin, Meenakshie Bradley-Garcia and Hélène Plamondon
Nutrients 2024, 16(14), 2350; https://doi.org/10.3390/nu16142350 - 20 Jul 2024
Viewed by 368
Abstract
In adult rats, omega-3 supplementation through fish oil (FO) and environmental enrichment (EE) have shown beneficial effects on cognition and stress regulation. This study assessed sex-specific effects of FO and EE during adolescence, a period critical for brain maturation, on adulthood coping mechanisms, [...] Read more.
In adult rats, omega-3 supplementation through fish oil (FO) and environmental enrichment (EE) have shown beneficial effects on cognition and stress regulation. This study assessed sex-specific effects of FO and EE during adolescence, a period critical for brain maturation, on adulthood coping mechanisms, sociability, and glucocorticoid regulation. An amount of 64 Wistar rats [n = 32/sex; postnatal day (PND) 23] were assigned to supplementation of control soybean oil (CSO) or menhaden fish oil (FO; 0.3 mL/100 g) from PND28 to 47 and exposed to EE or regular cage (RC) housing from PND28 to 58, with their blood corticosterone (CORT) levels being assessed weekly. As adults, exposure to repeated forced swim tests (FSTs; PND90–91) enabled analysis of coping responses, while socioemotional and memory responses were evaluated using the OFT, EPM, SIT, and Y maze tests (PND92–94). Immunohistochemistry determined hippocampal CA1/CA3 glucocorticoid receptor (GR) expression (PND95). CORT secretion gradually increased as the supplementation period elapsed in female rats, while changes were minimal in males. Coping strategies in the FST differed between sexes, particularly in FO-fed rats, where females and males, respectively, favoured floating and tail support to minimise energy consumption and maintain immobility. In the SIT, FO/EE promoted sociability in females, while a CSO diet favoured social recognition in males. Reduced CA3 GR-ir expression was found in FO/RC and CSO/EE rat groups, supporting stress resilience and memory consolidation. Our findings support environment and dietary conditions to exert a sex-specific impact on biobehavioural responses. Full article
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<p>Timeline of the experiment. Wistar rats (male and female, <span class="html-italic">N</span> = 64) arrived at the facility at PND23. Dietary supplementation [FO or CSO] was provided daily from PND28 to 47, and rats were exposed to EE or RC from PND28 to 59. Four conditions were tested: CSO/RC, CSO/EE, FO/RC, and FO/EE. Following the FST (PND90–91), rats were exposed to the OFT, EPM, SIT and Y-Maze (PND92–94). Brain tissue was collected on PND95. <span class="html-italic">FO: menhaden fish oil; CSO: control soybean oil; EE: environmental enrichment; RC: regular cage; CORT: corticosterone; FST: forced swim test; OFT: open field test; EPM: elevated-plus maze; SIT: social interaction test; GR-ir: glucocorticoid receptors</span>.</p>
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<p>Effect of supplementation, sex, and environment in the forced swim test (FST) on time spent climbing (<b>A</b>), swimming (<b>B</b>), immobility by floating (<b>C</b>), and immobility by tail support (<b>D</b>). Increased climbing was observed for CSO/RC males compared to all groups (<span class="html-italic">p</span> &lt; 0.001; #). FO Females climbed more than CSO regardless of the environment (<span class="html-italic">p</span> &lt; 0.001; *; (<b>A</b>)). Swimming was enhanced in CSO-fed females compared to male counterparts in both RC and EE (<span class="html-italic">p</span> &lt; 0.001; &amp;). Male CSO/RC rats show reduced swim compared to all groups (<span class="html-italic">p</span> &lt; 0.01, #; (<b>B</b>)). Immobility was increased in FO/RC females compared to all groups (<span class="html-italic">p</span> &lt; 0.001; #; (<b>C</b>)). Male rats fed FO used tail support to maintain immobility (<span class="html-italic">p</span> = 0.001; &amp;), while female counterparts preferred floating (<span class="html-italic">p</span> &lt; 0.001; #; (<b>D</b>)). Data are presented as mean ± S.E.M. * and # indicate significant differences between groups at <span class="html-italic">p</span> &lt; 0.05. * indicates significant impact of supplementation only (<span class="html-italic">p</span> &lt; 0.05). <span class="html-italic">FO: menhaden fish oil; CSO: control soybean oil; EE: enriched environment; RC: regular cage</span>.</p>
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<p>Effect of supplementation, sex, and environment in the Open Field Test (OFT) for time spent in the centre (<b>A</b>), time spent in the periphery (<b>B</b>), frequency to centre (<b>C</b>), and frequency to periphery (<b>D</b>). Male rodents spent more time in the centre zone compared to females (<span class="html-italic">p</span> &lt; 0.05; #). CSO/EE males spent increased time in the centre zone (<b>A</b>), while females in the same condition spent increased time in the periphery ((<b>B</b>); <span class="html-italic">p</span> &lt; 0.05; *). Rats in the FO/RC and CSO/EE group also entered more frequently the centre (<b>C</b>) and peripheral zone (<b>D</b>) compared to the FO/EE condition (<span class="html-italic">p</span> &lt; 0.05; &amp;). Data are presented as mean ± S.E.M. * and # indicate a statistically significant difference between groups (<span class="html-italic">p</span> &lt; 0.05). * indicates significant impact of the condition (supplementation and housing only) with no effect of sex (<span class="html-italic">p</span> &lt; 0.05). <span class="html-italic">FO: menhaden fish oil; CSO: control soybean oil; EE: enriched environment; RC: regular cage</span>.</p>
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<p>Effect of supplementation, sex, and environment in the Elevated Plus Maze (EPM) for frequency in the open arm (<b>A</b>) and closed arm (<b>B</b>). FO-supplemented rats entered the open (<b>A</b>) and closed arms (<b>B</b>) less frequently than CSO-supplemented rats (<span class="html-italic">p</span> &lt; 0.001; &amp;). Data are presented as mean ± S.E.M. &amp; indicates a significant impact of the condition (supplementation only) without an influence of sex or housing at <span class="html-italic">p</span> &lt; 0.05. <span class="html-italic">FO: menhaden fish oil; CSO: control Soybean oil; EE: enriched environment; RC: regular cage</span>.</p>
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<p>Effect of supplementation, sex, and environment in the Social Interaction Test (SIT) for exploration in session 1 (<b>A</b>) and session 2 (<b>B</b>). FO/EE females spent more time interacting with S1 than the empty cup compared to CSO/EE counterparts (<span class="html-italic">p</span> &lt; 0.05; *), supporting increased sociability (<b>A</b>). FO supplementation in males reduced social recognition through reduced interaction time with S2 compared to CSO-fed counterparts (<span class="html-italic">p</span> &lt; 0.05; *), notwithstanding housing conditions (<b>B</b>). Data are presented as mean ± S.E.M. * indicates a statistically significant difference between groups at <span class="html-italic">p</span> &lt; 0.05. <span class="html-italic">FO: menhaden fish oil; CSO: control soybean oil; EE: enriched environment; RC: regular cage</span>.</p>
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<p>Effect of supplementation, sex, and environment for latency to arm re-entry (<b>A</b>) and Risk assessment behaviour (<b>B</b>) in the Y-maze passive avoidance test. In general, males CSO/RC and FO/EE took more time to re-enter the aversive arm compared to females in the same condition (<span class="html-italic">p</span> &lt; 0.05; *; (<b>A</b>)). In males, CSO/EE and FO/EE showed reduced assessments compared to the CSO/RC condition (<span class="html-italic">p</span> &lt; 0.05; *). Females underwent fewer risk assessments compared to males (<span class="html-italic">p</span> &lt; 0.05; #; (<b>B</b>)). Data are presented as mean ± S.E.M. * and # indicate a statistically significant difference between groups at <span class="html-italic">p</span> &lt; 0.05. <span class="html-italic">FO: menhaden fish oil; CSO: control soybean oil; EE: enriched environment; RC: regular cage</span>.</p>
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<p>Corticosterone levels (pg/mL) assessed on experimental DAY1, 7, 14, 21. Statistical increases in CORT were observed for all females compared to males on DAY21 (<span class="html-italic">p</span> &lt; 0.001) as well as between females from DAY1, 7, and 14 (<span class="html-italic">p</span> &lt; 0.001 for each day). Data are presented as mean ± S.E.M. * indicates a statistically significant difference between groups at <span class="html-italic">p</span> &lt; 0.05. <span class="html-italic">FO: menhaden fish oil; CSO: control soybean oil; EE: enriched environment; RC: regular cage</span>.</p>
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<p>GR-ir at the CA3 region of the hippocampus. Figure shows representative photomicrographs of GR-ir in the CA3 for each experimental condition (<b>A</b>) as well as specificity of GR antibody through superposition on Hoechst adenine–thymine-binding dye (<b>B</b>). Reduced GR-ir was observed in CSO/EE and FO/RC groups compared to CSO/RC rats (<span class="html-italic">p</span> = 0.019 and <span class="html-italic">p</span> = 0.005, respectively; (<b>C</b>)). Data are presented as mean ± S.E.M. &amp; indicates effects of supplementation and housing without effects of sex (<span class="html-italic">p</span> &lt; 0.05). <span class="html-italic">FO: menhaden fish oil; CSO: control soybean oil; EE: enriched environment; RC: regular cage; GR: glucocorticoid receptors</span>.</p>
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20 pages, 10619 KiB  
Article
Transcriptomic and Metabolomic Analyses of Soybean Protein Isolate on Monascus Pigments and Monacolin K Production
by Xueling Qin, Haolan Han, Jiayi Zhang, Bin Xie, Yufan Zhang, Jun Liu, Weiwei Dong, Yuanliang Hu, Xiang Yu and Yanli Feng
J. Fungi 2024, 10(7), 500; https://doi.org/10.3390/jof10070500 (registering DOI) - 19 Jul 2024
Viewed by 332
Abstract
Monascus pigments (MPs) and monacolin K (MK) are important secondary metabolites produced by Monascus spp. This study aimed to investigate the effect of soybean protein isolate (SPI) on the biosynthesis of MPs and MK based on the analysis of physiological indicators, transcriptomes, and [...] Read more.
Monascus pigments (MPs) and monacolin K (MK) are important secondary metabolites produced by Monascus spp. This study aimed to investigate the effect of soybean protein isolate (SPI) on the biosynthesis of MPs and MK based on the analysis of physiological indicators, transcriptomes, and metabolomes. The results indicated that the growth, yellow MPs, and MK production of Monascus pilosus MS-1 were significantly enhanced by SPI, which were 8.20, 8.01, and 1.91 times higher than that of the control, respectively. The utilization of a nitrogen source, protease activity, the production and utilization of soluble protein, polypeptides, and free amino acids were also promoted by SPI. The transcriptomic analysis revealed that the genes mokA, mokB, mokC, mokD, mokE, mokI, and mokH which are involved in MK biosynthesis were significantly up-regulated by SPI. Moreover, the glycolysis/gluconeogenesis, pyruvate metabolism, fatty acid degradation, tricarboxylic acid (TCA) cycle, and amino acid metabolism were effectively up-regulated by SPI. The metabolomic analysis indicated that metabolisms of amino acid, lipid, pyruvate, TCA cycle, glycolysis/gluconeogenesis, starch and sucrose, and pentose phosphate pathway were significantly disturbed by SPI. Thus, MPs and MK production promoted by SPI were mainly attributed to the increased biomass, up-regulated gene expression level, and more precursors and energies. Full article
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<p>Effect of SPI on the growth, MPs, and MK production of <span class="html-italic">M. pilosus.</span> (<b>A</b>) pH of the fermentation broth; (<b>B</b>) biomass; (<b>C</b>) color value; (<b>D</b>) MK content. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effect of SPI on the process of nitrogen utilization by <span class="html-italic">M. pilosus.</span> (<b>A</b>) Monosodium glutamate; (<b>B</b>) nitrogen content; (<b>C</b>) protease activity; (<b>D</b>) soluble protein and polypeptide. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Transcriptional analysis of <span class="html-italic">M. pilosus</span> MS-1 response to SPI. (<b>A</b>) The volcano plot of DEGs; (<b>B</b>) cluster heat map of DEGs; (<b>C</b>) COG annotation classification statistical chart of DEGs; (<b>D</b>) GO enrichment analysis of DEGs; (<b>E</b>) KEGG classification annotation map; (<b>F</b>) KEGG enrichment bubble chart. C and S represent the CK and SPI group respectively.</p>
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<p>Expression levels of genes related to MK synthesis. (<b>A</b>) Transcription level; (<b>B</b>) Log2FC; (<b>C</b>) expression heat map; (<b>D</b>) effects of SPI on <span class="html-italic">Monascus</span> gene expression. Genes 1–10 are gene-315043, gene-213838, gene-256816, gene-52089, gene-170694, gene-272292, gene-99680, gene-87025, gene-304829, and gene-194396, respectively. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Hierarchical cluster analysis and volcano plot analysis of significant differential metabolites in CK and SPI groups. (<b>A</b>) Positive mode; (<b>B</b>) negative mode; (<b>C</b>) CI vs. SI in positive mode; (<b>D</b>) CE vs. SE in positive mode; (<b>E</b>) CI vs. SI in negative mode; (<b>F</b>) CE vs. SE in negative mode. C and S represent the CK and SPI group, respectively; I and E represent intracellular and extracellular, respectively. The same below.</p>
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<p>KEGG enrichment map of significant differential metabolic pathway between CK and SPI group. (<b>A</b>) KEGG classification annotation map; (<b>B</b>) KEGG enrichment bubble chart of intracellular; (<b>C</b>) KEGG enrichment bubble chart of extracellular.</p>
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<p>Putative regulatory mechanism of SPI on biosynthesis of MPs and MK. EMP—Embden–Meyerhof pathway; PP—pentose phosphate pathway; PEP—pyruvate metabolism; FAD—fatty acid degradation; AAM—amino acid metabolism; TCA—tricarboxylic acid cycle. Different colors in the figure represent different metabolic pathways, and italics represent genes. Amino acids are represented by abbreviations. Asp: Aspartate, Phe: Phenylalanine, Ile: Isoleucine, Met: Methionine, Val: Valine, Glu: Glutamate, His: Histidine, Leu: leucine, Trp: Tryptophan.</p>
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11 pages, 1281 KiB  
Article
Growth and Yield Dynamics in Three Japanese Soybean Cultivars with Plant Growth-Promoting Pseudomonas spp. and Bradyrhizobium ottawaense Co-Inoculation
by Khin Thuzar Win, Fukuyo Tanaka, Kiwamu Minamisawa and Haruko Imaizumi-Anraku
Microorganisms 2024, 12(7), 1478; https://doi.org/10.3390/microorganisms12071478 - 19 Jul 2024
Viewed by 227
Abstract
Co-inoculation of soybeans with Bradyrhizobium and plant growth-promoting bacteria has displayed promise for enhancing plant growth, but concrete evidence of its impact on soybean yields is limited. Therefore, this study assessed the comparative efficacy of two 1-aminocyclopropane-1-carboxylate deaminase-producing Pseudomonas species (OFT2 and OFT5) [...] Read more.
Co-inoculation of soybeans with Bradyrhizobium and plant growth-promoting bacteria has displayed promise for enhancing plant growth, but concrete evidence of its impact on soybean yields is limited. Therefore, this study assessed the comparative efficacy of two 1-aminocyclopropane-1-carboxylate deaminase-producing Pseudomonas species (OFT2 and OFT5) co-inoculated with Bradyrhizobium ottawaense (SG09) on the growth, physiology, nodulation efficiency, and grain yield of three major Japanese soybean cultivars: Enrei, Fukuyutaka, and Satonohohoemi. The experiments were conducted in a warehouse under natural light conditions. The treatments included the inoculation of SG09, SG09 + OFT2, and SG09 + OFT5. Compared with Bradyrhizobium inoculation alone, co-inoculation led to significant improvements in nodulation efficiency, growth, and physiological performance in the Enrei and Fukuyutaka cultivars, but not in the Satonohohoemi cultivar. Furthermore, co-inoculation significantly boosted the total nitrogen content and ion uptake in the shoots, ultimately leading to a remarkable improvement in the grain yield in the Enrei and Fukuyutaka cultivars. These findings contribute to clarifying the interplay among Bradyrhizobium, Pseudomonas, and the plant host cultivar. Notably, BradyrhizobiumPseudomonas co-inoculation represents a potentially effective biofertilization strategy for soybean production, highlighting promising avenues for sustainable agricultural practices. Full article
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<p>Effects of co-inoculating PGPB with <span class="html-italic">B. ottawaense</span> SG09 on leaf area and total dry weight in three different soybean cultivars at 7 weeks after sowing. Different letters indicate classes that exhibit significant differences (<span class="html-italic">p</span> &lt; 0.05) using Duncan’s multiple range test. “ns” indicates not significant (<span class="html-italic">p</span> &gt; 0.05). The white, pink, and blue boxes represent the treatments SG09, SG09 + OFT2, and SG09 + OFT5, respectively.</p>
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<p>Effects of co-inoculating of plant growth-promoting bacteria with <span class="html-italic">B. ottawaense</span> SG09 on the leaf chlorophyll content (SPAD value) and photosynthesis rate (A<sub>sat</sub>) of three different soybean cultivars at 7 weeks after sowing. Different letters indicate classes that exhibit significant differences (<span class="html-italic">p</span> &lt; 0.05) using Duncan’s multiple range test. “ns” indicates not significant (<span class="html-italic">p</span> &gt; 0.05). The white, pink, and blue boxes represent the treatments SG09, SG09 + OFT2, and SG09 + OFT5, respectively.</p>
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<p>Effects of co-inoculating PGPB and <span class="html-italic">B. ottawaense</span> SG09 on nodule numbers, nodule dry weight, and N<sub>2</sub> fixation (ARA) in three different soybean cultivars at 7 weeks after sowing. Different letters indicate classes that display significant differences (<span class="html-italic">p</span> &lt; 0.05) using Duncan’s multiple range test. “ns” indicates not significant (<span class="html-italic">p</span> &gt; 0.05). The white, pink, and blue boxes represent the treatments SG09, SG09 + OFT2, and SG09 + OFT5, respectively.</p>
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<p>Effects of co-inoculating plant growth-promoting bacteria with <span class="html-italic">B. ottawaense</span> SG09 on seed yield and aboveground biomass in three different soybean cultivars at maturity. Different letters indicate classes that display significant differences (<span class="html-italic">p</span> &lt; 0.05) using Duncan’s multiple range test. “ns” indicates not significant (<span class="html-italic">p</span> &gt; 0.05). The white, pink, and blue boxes represent the treatments SG09, SG09 + OFT2, and SG09 + OFT5, respectively.</p>
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15 pages, 903 KiB  
Article
Dietary Methionine Requirements for Juvenile Florida Pompano (Trachinotus carolinus)
by Trenton L. Corby, Trinh Ngo, Marty Riche and D. Allen Davis
J. Mar. Sci. Eng. 2024, 12(7), 1206; https://doi.org/10.3390/jmse12071206 - 18 Jul 2024
Viewed by 287
Abstract
A 56-day feeding trial was conducted to evaluate the quantitative methionine requirements in the diets of Florida pompano (Trachinotus carolinus). Eight practical diets using soybean meal, poultry meal, and red lentil meal as the primary protein sources were formulated using graded [...] Read more.
A 56-day feeding trial was conducted to evaluate the quantitative methionine requirements in the diets of Florida pompano (Trachinotus carolinus). Eight practical diets using soybean meal, poultry meal, and red lentil meal as the primary protein sources were formulated using graded levels of methionine supplement (0 to 0.70 g/100 g diet). Groups of 15 juvenile Florida pompano (4.04 ± 0.05 g) were size-sorted and placed into one of 40 glass aquaria (132 L) with five replicates per diet. Significant differences (p ≤ 0.05) were observed in overall biomass, mean weight, weight gain, thermal growth coefficient (TGC), and feed conversion ratio (FCR). To estimate the dietary methionine requirement, a series of statistical models, including the one-slope broken line model (BLM1), two-slope broken line model (BLM2), broken quadratic model (BQM), and four-parameter saturation kinetic model (SKM-4) were used to assess mean weight, weight gain, TGC, apparent net protein retention (ANPR), and methionine retention (MR). The model selection showed that BLM1 fit the data best for MW and TGC, SKM-4 for PWG and ANPR, and BQM for MR. Based on these results, a minimum dietary methionine requirement of 0.68% of the diet or 1.70 g/100 g protein is recommended. Full article
(This article belongs to the Section Marine Aquaculture)
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<p>Thermal growth coefficient fitted with a one-slope broken line model.</p>
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<p>Apparent net protein retention fitted with a four-parameter saturation kinetic model.</p>
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<p>Methionine retention fitted with a broken quadratic model.</p>
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15 pages, 3967 KiB  
Article
Effects of Different Soybean and Coconut Oil Additions on the Physicochemical and Sensory Properties of Soy Protein–Wheat Protein Mixture Subjected to High-Moisture Extrusion
by Wentao Zhang, Bowen Hui, Xuejie Li, Zengwang Guo, Jian Ma and Jian Li
Foods 2024, 13(14), 2263; https://doi.org/10.3390/foods13142263 - 18 Jul 2024
Viewed by 282
Abstract
A protein mixture was prepared using a blend of soybean protein isolate, soybean protein concentrate, and wheat protein through high-moisture extrusion. This study investigated the effects of soybean oil/coconut oil additions (2%, 5%, and 8%) on the physiochemical properties of a soy protein–wheat [...] Read more.
A protein mixture was prepared using a blend of soybean protein isolate, soybean protein concentrate, and wheat protein through high-moisture extrusion. This study investigated the effects of soybean oil/coconut oil additions (2%, 5%, and 8%) on the physiochemical properties of a soy protein–wheat protein mixture subjected to high-moisture extrusion. The protein extrudates underwent assessment for textural properties, fiber degree, sensory evaluation, microstructure, protein solubility, and protein secondary structure. The findings indicated that plant oils significantly reduced the hardness, springiness, and chewiness of the extrudates, and 5% plant oil significantly increased the fiber degree of the extrudates. In addition, the highest fiber degree and sensory evaluation score were achieved with 5% coconut oil. Observation of the macro- and microstructure indicated that the presence of unsaturated fatty acids in soybean oil did not benefit the improvement of the fibrous structure of protein extrudates during high-moisture extrusion processing. SDS-PAGE and FTIR results revealed that coconut oil, rich in saturated fatty acids, caused the clustering of medium- and low-molecular-weight subunits in texturized protein. Additionally, coconut oil elevated the ratio of 11S protein subunits containing sulfur-based amino acids and facilitated a shift from β-turn to β-sheet. The inclusion of plant oils increased the development of hydrogen and disulfide bonds, resulting in a denser, fibrous structure. DSC demonstrated that plant oils reduced the thermal stability of the texturized proteins but enhanced the order of protein structure. Full article
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<p>Effect of plant oil on textural properties and fiber degree of the texturized protein.</p>
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<p>Effect of plant oil on color of the texturized protein.</p>
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<p>Effect of plant oil on the sensory evaluation of the texturized protein.</p>
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<p>Effect of plant oil on the sensory weighted score of the texturized protein.</p>
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<p>Microstructure of the texturized protein with different plant oils, obtained by SEM. (<b>a</b>,<b>c</b>,<b>e</b>): Transversal sections of soybean protein extrudates at 30× and 1500× magnification. (<b>b</b>,<b>d</b>,<b>f</b>): Longitudinal cross-sections of soybean protein extrusions at 30× and 1500× magnification. The black frames in each picture represent the areas where the fibrous structure is most evident.</p>
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<p>SDS-PAGE patterns of soybean oil (<b>a</b>) and coconut oil of protein extrudates (<b>b</b>).</p>
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<p>Effect of plant oil on the secondary structure of the texturized protein.</p>
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<p>Effect of plant oil on the solubility of the texturized protein in different solvents.</p>
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<p>Effect of plant oil on the thermal properties of the texturized protein.</p>
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14 pages, 3092 KiB  
Article
Glyphosate Hormesis Improves Agronomic Characteristics and Yield of Glyphosate-Resistant Soybean Under Field Conditions
by Fábio Henrique Krenchinski, Vinicius Gabriel Canepelle Pereira, Bruno Flaibam Giovanelli, Victor José Salomão Cesco, Ricardo Alcántara-de la Cruz, Edivaldo D. Velini and Caio A. Carbonari
Agronomy 2024, 14(7), 1559; https://doi.org/10.3390/agronomy14071559 - 18 Jul 2024
Viewed by 318
Abstract
Brazil, the world’s largest soybean producer, owes its success to the cultivation of glyphosate-resistant (GR) cultivars. However, the soybean yields lag behind those obtained in areas managed for high productivity. Glyphosate-induced hormesis holds promise for increasing crop yields, but the potential evolution of [...] Read more.
Brazil, the world’s largest soybean producer, owes its success to the cultivation of glyphosate-resistant (GR) cultivars. However, the soybean yields lag behind those obtained in areas managed for high productivity. Glyphosate-induced hormesis holds promise for increasing crop yields, but the potential evolution of resistance in certain weed species poses a challenge to foliar applications under field conditions. This study assessed the effects of a hormesis-inducing glyphosate dose [90 g acid equivalent (ae) ha−1] on the agronomic characteristics and yield of four GR soybean cultivars. The evaluation was conducted in field settings across various Brazilian locations, considering foliar, seed, and seed + foliar treatments. The results showed variations in dry mass, root nodules, nutrient composition, plant height, pods, and yield, primarily influenced by environmental conditions, soil quality, and, ultimately, the interaction between GR cultivars and treatments. Total dry mass consistently increased with glyphosate, with seed and seed + foliar treatments showing the most substantial increases (7–21%). All three treatments increased nodulation by up to 36% across locations and cultivars, with seed + foliar treatment causing notable increases in nodule dry mass (up to 56%), followed by seed treatment (41%). Nutrient composition, especially for N, P, Br, and Fe, displayed location-dependent variations. Plant height varied among locations and cultivars, with minimal differences between treatments. Glyphosate treatments increased pod numbers (10 to 35%) and yields (11 to 42%) of soybean in seed and seed + foliar treatments. The findings highlight the potential of glyphosate hormesis as a viable tool for improving yields of GR soybean cultivars at the field level. However, the extent of benefits depends on the agronomic conditions of location, choice of cultivars, and herbicide application method. Full article
(This article belongs to the Special Issue Soybean Yield and Quality Improvement)
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<p>Total dry mass per plant of soybean RR2 (M5917-IPRO and M5838-IPRO) and RR (BMX-Tornado and N5909) cultivars treated with glyphosate via foliar (90 g ae ha<sup>−1</sup>), seed (90 g ae ha<sup>−1</sup>), and seed + foliar (180 g ae ha<sup>−1</sup>) in Assis Chateaubriand, Marechal Cândido Rondon, and Palotina, Brazil. Mean ± confidence interval (5% probability). Same capital letters between locations, italic capital letters between cultivars, and lowercase letters between treatments within a cultivar did not differ from each other using the Tukey test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">ns</span>—not significant.</p>
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<p>Number and dry mass of nodules in soybean RR2 (M5917-IPRO and M5838-IPRO) and RR (BMX-Tornado and N5909) cultivars treated with glyphosate via foliar (90 g ae ha<sup>−1</sup>), seed (90 g ae ha<sup>−1</sup>), and seed + foliar (180 g ae ha<sup>−1</sup>) in Assis Chateaubriand, Marechal Cândido Rondon, and Palotina, Brazil. Mean ± confidence interval (5% probability). Same capital letters between locations, italic capital letters between cultivars, and lowercase letters between treatments within a cultivar did not differ from each other using the Tukey test (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Plant height of soybean RR2 (M5917-IPRO and M5838-IPRO) and RR (BMX-Tornado and N5909) cultivars treated with glyphosate via foliar (90 g ae ha<sup>−1</sup>), seed (90 g ae ha<sup>−1</sup>), and seed + foliar (180 g ae ha<sup>−1</sup>) in Assis Chateaubriand, Botucatu, Marechal Cândido Rondon, and Palotina, Brazil. Mean ± confidence interval (5% probability). Same capital letters between locations, italic capital letters between cultivars, and lowercase letters between treatments within a cultivar did not differ from each other using the Tukey test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">ns</span>—not significant.</p>
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<p>Pods per plant of soybean RR2 (M5917-IPRO and M5838-IPRO) and RR (BMX-Tornado and N5909) cultivars treated with glyphosate via foliar (90 g ae ha<sup>−1</sup>), seed (90 g ae ha<sup>−1</sup>), and seed + foliar (180 g ae ha<sup>−1</sup>) in Assis Chateaubriand, Botucatu, Marechal Cândido Rondon, and Palotina, Brazil. Mean ± confidence interval (5% probability). Same capital letters between locations, italic capital letters between cultivars, and lowercase letters between treatments within a cultivar did not differ from each other using the Tukey test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">ns</span>—not significant.</p>
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<p>Crop yield of soybean RR2 (M5917-IPRO and M5838-IPRO) and RR (BMX-Tornado and N5909) cultivars treated with glyphosate via foliar (90 g ae ha<sup>−1</sup>), seed (90 g ae ha<sup>−1</sup>), and seed + foliar (180 g ae ha<sup>−1</sup>) in Assis Chateaubriand, Botucatu, Marechal Cândido Rondon, and Palotina, Brazil. Mean ± confidence interval (5% probability). Same capital letters between locations, italic capital letters between cultivars, and lowercase letters between treatments within a cultivar did not differ from each other using the Tukey test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">ns</span>—not significant.</p>
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13 pages, 479 KiB  
Article
Effects of Replacing Soybean Meal with Cottonseed Meal, Peanut Meal, Rapeseed Meal, or Distillers’ Dried Grains with Solubles on the Growth Performance, Nutrient Digestibility, Serum Parameters, and Rumen Fermentation in Growing Lambs
by Xuejiao Yin, Meijing Chen, Caihong Yang, Chunhui Duan, Shoukun Ji, Hui Yan, Yueqin Liu and Yingjie Zhang
Vet. Sci. 2024, 11(7), 322; https://doi.org/10.3390/vetsci11070322 - 17 Jul 2024
Viewed by 455
Abstract
Considering the frequently large price fluctuations for soybean meal, an alternative is the increased use of locally produced high-protein ingredients. The objective of this study was to evaluate the effects of the total replacement of soybean meal with different sources of protein on [...] Read more.
Considering the frequently large price fluctuations for soybean meal, an alternative is the increased use of locally produced high-protein ingredients. The objective of this study was to evaluate the effects of the total replacement of soybean meal with different sources of protein on the growth performance, nutrient digestibility, serum parameters, rumen fermentation parameters, and bacterial communities in growing lambs. Sixty sheep with similar body weights (38.46 ± 0.71 kg) were distributed to one of five treatments: soybean meal (SBM); cottonseed meal (COM); peanut meal (PEM); rapeseed meal (RAM); and distillers’ dried grains with solubles (DDGS). The experiment lasted 62 days with a 10-day adaptation period and a 52-day growing period. The results indicated that the body weight and average daily gain were not affected by different protein sources (p > 0.05), but the dry matter intake of the SBM group was lower than that of the other groups (p < 0.05); otherwise, the feed efficiency was higher (p < 0.05). The digestion of dry matter was higher in the SBM, COM, and RAM groups than in the DDGS and PEM groups (p < 0.05). Meanwhile, compared to the other groups, the SBM group had the highest digestion of gross energy and crude protein (p < 0.05). In addition, the concentration of glutathione peroxidase was highest in the SBM group (p < 0.05). Regarding the rumen fermentation, the SBM group had the highest concentration of NH3-N (p < 0.05). The rumen bacterial community was not affected by treatments (p > 0.05). In conclusion, the total replacement of soybean meal with cottonseed, peanut, rapeseed, or DDGS reduced digestibility but did not impact the body weight or average daily gain of growing lambs and had no effect on the immune function and rumen bacterial community; thus, they can be used to substitute the soybean meal. Full article
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Figure 1
<p>Effects of different protein sourced diets on rumen bacterial diversity: (<b>A</b>) Chao 1 index; (<b>B</b>) Shannon index; and (<b>C</b>) principal coordinate analysis (PCoA) of Bray–Curtis distance.</p>
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12 pages, 258 KiB  
Article
Assessment of Non-Phytate Phosphorus Requirements of Chinese Jing Tint 6 Layer Chicks from Hatch to Day 42
by Cheng-Yan Gong, Guang Liu, Hong-Peng Shi, Shuan Liu, Xin-Yi Gao, Shou-Jun Zhang, Hao Liu, Rui Li and Dan Wan
Animals 2024, 14(14), 2093; https://doi.org/10.3390/ani14142093 - 17 Jul 2024
Viewed by 234
Abstract
We aimed to estimate the non-phytate phosphorus (NPP) requirements of Chinese Jing Tint 6 layer chicks. We randomly allocated 720 birds to five treatments with six cages of 24 birds each, feeding them a corn–soybean diet containing 0.36%, 0.41%, 0.46%, 0.51%, and 0.56% [...] Read more.
We aimed to estimate the non-phytate phosphorus (NPP) requirements of Chinese Jing Tint 6 layer chicks. We randomly allocated 720 birds to five treatments with six cages of 24 birds each, feeding them a corn–soybean diet containing 0.36%, 0.41%, 0.46%, 0.51%, and 0.56% NNP. The results showed that the body weight gain (BWG), tibial length, and apparent total tract digestibility coefficients (ATTDC) of P were affected (p < 0.05) by dietary NPP level. A quadratic broken-line analysis (p < 0.05) of BWG indicated that the optimal NPP for birds aged 1–14 d was 0.411%. Similarly, 0.409% of NPP met tibial growth needs. However, 0.394% of NPP was optimal for P utilization according to the ATTDC criterion. For 15–42 d birds, 0.466% NPP, as estimated by the BWG criterion, was sufficient for optimal growth without decreasing P utilization. Using the factorial method, NPP requirements were calculated as 0.367% and 0.439%, based on the maintenance factors and BWG for 1–14 and 15–42 d birds, respectively, to maintain normal growth. Combining the non-linear model with the factorial method, this study recommends dietary NPP levels of 0.367% and 0.439% for 1–14 and 15–42 d birds, respectively, to optimize P utilization without affecting performance. Full article
(This article belongs to the Section Animal Nutrition)
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