Agriculture

19 pages, 6483 KiB

Open AccessArticle

Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging

by Xiaoyu Xue, Haiqing Tian, Kai Zhao, Yang Yu, Ziqing Xiao, Chunxiang Zhuo and Jianying Sun

Agriculture 2024, 14(9), 1653; https://doi.org/10.3390/agriculture14091653 (registering DOI) - 22 Sep 2024

Abstract

Lactic acid content is a crucial indicator for evaluating maize silage quality, and its accurate detection is essential for ensuring product quality. In this study, a quantitative prediction model for the change of lactic acid content during the secondary fermentation of maize silage [...] Read more.

Lactic acid content is a crucial indicator for evaluating maize silage quality, and its accurate detection is essential for ensuring product quality. In this study, a quantitative prediction model for the change of lactic acid content during the secondary fermentation of maize silage was constructed based on a colorimetric sensor array (CSA) combined with hyperspectral imaging. Volatile odor information from maize silage samples with different days of aerobic exposure was obtained using CSA and recorded by a hyperspectral imaging (HSI) system. Subsequently, the acquired spectral data were subjected to preprocessing through five distinct methods before being modeled using partial least squares regression (PLSR). The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to screen three color-sensitive dyes that are more sensitive to changes in lactic acid content of maize silage. To minimize model redundancy, three algorithms, such as competitive adaptive reweighted sampling (CARS), were used to extract the characteristic wavelengths of the three dyes, and the combination of the characteristic wavelengths obtained by each algorithm was used as an input variable to build an analytical model for quantitative prediction of the lactic acid content by support vector regression (SVR). Moreover, two optimization algorithms, namely grid search (GS) and crested porcupine optimizer (CPO), were compared to determine their effectiveness in optimizing the parameters of the SVR model. The results showed that the prediction accuracy of the model can be significantly improved by choosing appropriate pretreatment methods for different color-sensitive dyes. The CARS-CPO-SVR model had better prediction, with a prediction set determination coefficient (

R_{P}^{2}

), root mean square error of prediction (RMSEP), and a ratio of performance to deviation (RPD) of 0.9617, 2.0057, and 5.1997, respectively. These comprehensive findings confirm the viability of integrating CSA with hyperspectral imaging to accurately quantify the lactic acid content in silage, providing a scientific and novel method for maize silage quality testing. Full article

(This article belongs to the Section Digital Agriculture)

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16 pages, 4313 KiB

Open AccessArticle

Combined Genome-Wide Association Studies (GWAS) and Linkage Mapping Identifies Genomic Regions Associated with Seedling Root System Architecture (RSA) under Different Nitrogen Conditions in Wheat (Triticum aestivum L.)

by Yulin Jia, Ninglu Xu, Jun Zhang, Kaiming Ren, Jinzhi Wu, Chunping Wang, Ming Huang and Youjun Li

Agriculture 2024, 14(9), 1652; https://doi.org/10.3390/agriculture14091652 (registering DOI) - 21 Sep 2024

Abstract

The nitrogen (N) use efficiency (NUE) in the roots of seedlings is beneficial for increasing crop yield. Creating marker-assisted selection for wheat root traits can assist wheat breeders in choosing robust roots to maximize nutrient uptake. Exploring and identifying the effect of different [...] Read more.

The nitrogen (N) use efficiency (NUE) in the roots of seedlings is beneficial for increasing crop yield. Creating marker-assisted selection for wheat root traits can assist wheat breeders in choosing robust roots to maximize nutrient uptake. Exploring and identifying the effect of different N supply conditions on root system architecture (RSA) is of great significance for breeding N efficient wheat varieties. In this study, a total of 243 wheat varieties native to the Yellow and Huai Valley regions of China were utilized for genome-wide association studies (GWAS). Furthermore, a recombinant inbred line (RIL) population of 123 lines derived from the cross between Avocet and Chilero was utilized for linkage examination. A hydroponic seedling experiment using a 96-well tray was conducted in the lab with two treatments: normal N (NN) and low N (LN). Five RSA traits, including the relative number of root tips (RNRT), relative total root length (RTRL), relative total root surface area (RTRS), relative total root volume (RTRV), and relative average root diameter (RARD), were investigated. GWAS and linkage analysis were performed by integrating data from the wheat 660 k single nucleotide polymorphism (SNP) chip and diversity arrays technology (DArT) to identify genetic loci associated with RSA. The results showed that, based on the ratio of RSA-related traits under two N supply conditions, a total of 497 SNP markers, which are significantly associated with RSA-related traits, were detected at 148 genetic loci by GWAS. A total of 10 QTL loci related to RSA were discovered and identified by linkage mapping. Combining two gene localization methods, three colocalized intervals were found: AX-95160997/QRtrl.haust-3D, AX-109592379/QRnrt.haust-5A, and AX-110924288/QRtrl.haust-7D/QRtrs.haust-7D. According to the physical location of the colocalization of these two sites, between 39.61 and 43.74 Mb, 649.97 and 661.55 Mb, and 592.44 and 605.36 Mb are called qRtrl-3D, qRnrt-5A, and qRtrl-7D. This study has the potential to enhance the effectiveness of selecting root traits in wheat breeding programs, offering valuable insights into the genetic underpinnings of NUE in wheat. These results could help in breeding wheat varieties with higher NUE by implementing focused breeding strategies. Full article

(This article belongs to the Section Crop Genetics, Genomics and Breeding)

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17 pages, 7845 KiB

Open AccessArticle

Bud-YOLO: A Real-Time Accurate Detection Method of Cotton Top Buds in Cotton Fields

by Xuening Zhang and Liping Chen

Agriculture 2024, 14(9), 1651; https://doi.org/10.3390/agriculture14091651 (registering DOI) - 21 Sep 2024

Abstract

Cotton topping plays a crucial and indispensable role in controlling excessive growth and enhancing cotton production. This study aims to improve the operational efficiency and accuracy of cotton topping robots through a real-time and accurate cotton top bud detection algorithm tailored for field [...] Read more.

Cotton topping plays a crucial and indispensable role in controlling excessive growth and enhancing cotton production. This study aims to improve the operational efficiency and accuracy of cotton topping robots through a real-time and accurate cotton top bud detection algorithm tailored for field operation scenarios. We propose a lightweight structure based on YOLOv8n, replacing the C2f module with the Cross-Stage Partial Networks and Partial Convolution (CSPPC) module to minimize redundant computations and memory access. The network’s neck employs an Efficient Reparameterized Generalized-FPN (Efficient RepGFPN) to achieve high-precision detection without substantially increasing computational cost. Additionally, the loss calculation of the optimized prediction frame was addressed with the Inner CIoU loss function, thereby enhancing the precision of the model’s prediction box. Comparison experiments indicate that the Bud-YOLO model is highly effective for detecting cotton top buds, with an AP50 of 99.2%. This performance surpasses that of other YOLO variants, such as YOLOv5s and YOLOv10n, as well as the conventional Faster R-CNN model. Moreover, the Bud-YOLO model exhibits robust performance across various angles, occlusion conditions, and bud morphologies. This study offers technical insights to support the migration and deployment of the model on cotton topping machinery. Full article

(This article belongs to the Section Digital Agriculture)

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20 pages, 1212 KiB

Open AccessArticle

Farmers’ Adoption of Agricultural Nature-Based Solutions in Northeast China: An Extended Theory of Planned Behavior Approach

by Minglong Zhang, Yanfang Huang, Yunzheng Zhang, Fengying Nie and Xiangping Jia

Agriculture 2024, 14(9), 1650; https://doi.org/10.3390/agriculture14091650 (registering DOI) - 20 Sep 2024

Abstract

The academic field has limited studies on implementing nature-based solutions (NbSs) in Chinese agriculture, especially regarding households’ and farmers’ attitudes toward the acceptance of agricultural NbS technologies. Based on this, this study aims to fill this knowledge gap by examining the factors behind [...] Read more.

The academic field has limited studies on implementing nature-based solutions (NbSs) in Chinese agriculture, especially regarding households’ and farmers’ attitudes toward the acceptance of agricultural NbS technologies. Based on this, this study aims to fill this knowledge gap by examining the factors behind farmers’ agricultural practices of NbS adoption in Northeast China. Accordingly, this paper constructs an extended theoretical framework of planned behavior (TPB) and empirically tests it using partial least squares structural equation modeling (PLS-SEM) on data from 298 farmers in Inner Mongolia. It was found that incorporating institutional trust (IT) into TPB improves the prediction of Chinese farmers’ intention to de-farm behavior. Unlike previous studies, this study identified two indirect pathways influencing farmers’ intention to adopt agricultural NbS technologies: from institutional trust through attitude to intention, and from institutional trust through perceived behavioral control to intention. The findings broaden the research perspective in this area, provide empirical evidence for the application of NbSs in agricultural practices in China and other developing countries, and demonstrate in practice that NbS has been promoted as an essential tool to maximize nature’s ability to provide ecosystem services and create direct economic benefits for farmers through increased yields and reduced costs. Full article

(This article belongs to the Special Issue Feature Papers in the Fields of Agricultural Economics, Policies and/or Rural Management)

19 pages, 6791 KiB

Open AccessArticle

Vegetation Phenology Changes and Recovery after an Extreme Rainfall Event: A Case Study in Henan Province, China

by Yinghao Lin, Xiaoyu Guo, Yang Liu, Liming Zhou, Yadi Wang, Qiang Ge and Yuye Wang

Agriculture 2024, 14(9), 1649; https://doi.org/10.3390/agriculture14091649 (registering DOI) - 20 Sep 2024

Abstract

Extreme rainfall can severely affect all vegetation types, significantly impacting crop yield and quality. This study aimed to assess the response and recovery of vegetation phenology to an extreme rainfall event (with total weekly rainfall exceeding 500 mm in several cities) in Henan [...] Read more.

Extreme rainfall can severely affect all vegetation types, significantly impacting crop yield and quality. This study aimed to assess the response and recovery of vegetation phenology to an extreme rainfall event (with total weekly rainfall exceeding 500 mm in several cities) in Henan Province, China, in 2021. The analysis utilized multi-sourced data, including remote sensing reflectance, meteorological, and crop yield data. First, the Normalized Difference Vegetation Index (NDVI) time series was calculated from reflectance data on the Google Earth Engine (GEE) platform. Next, the ‘phenofit’ R language package was used to extract the phenology parameters—the start of the growing season (SOS) and the end of the growing season (EOS). Finally, the Statistical Package for the Social Sciences (SPSS, v.26.0.0.0) software was used for Duncan’s analysis, and Matrix Laboratory (MATLAB, v.R2022b) software was used to analyze the effects of rainfall on land surface phenology (LSP) and crop yield. The results showed the following. (1) The extreme rainfall event’s impact on phenology manifested directly as a delay in EOS in the year of the event. In 2021, the EOS of the second growing season was delayed by 4.97 days for cropland, 15.54 days for forest, 13.06 days for grassland, and 12.49 days for shrubland. (2) Resistance was weak in 2021, but recovery reached in most areas by 2022 and slowed in 2023. (3) In each year, SOS was predominantly negatively correlated with total rainfall in July (64% of cropland area in the first growing season, 53% of grassland area, and 71% of shrubland area). In contrast, the EOS was predominantly positively correlated with rainfall (51% and 54% area of cropland in the first and second growing season, respectively, and 76% of shrubland area); however, crop yields were mainly negatively correlated with rainfall (71% for corn, 60% for beans) and decreased during the year of the event, with negative correlation coefficients between rainfall and yield (−0.02 for corn, −0.25 for beans). This work highlights the sensitivity of crops to extreme rainfall and underscores the need for further research on their long-term recovery. Full article

(This article belongs to the Special Issue Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring—2nd Edition)

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14 pages, 2043 KiB

Open AccessArticle

Reducing Grain Damage in Moist Corn Threshing via Corncob Division

by Gang Wang, Chengqian Jin, Min Zhang, Chongyou Wu, Qing Tang and Yao Yang

Agriculture 2024, 14(9), 1648; https://doi.org/10.3390/agriculture14091648 (registering DOI) - 20 Sep 2024

Abstract

For the prompt planting of subsequent crops, most of China’s corn harvest must occur before full maturity, with a grain moisture content above 25%. Harvesting moist corn presents challenges due to significant grain damage during threshing. We conducted a high-speed photography observation test [...] Read more.

For the prompt planting of subsequent crops, most of China’s corn harvest must occur before full maturity, with a grain moisture content above 25%. Harvesting moist corn presents challenges due to significant grain damage during threshing. We conducted a high-speed photography observation test of moist corn threshing. It demonstrated that corn ears, when passing through the threshing cylinder, often break into pieces. Grains on divided corncobs can be threshed more easily and earlier than those on undivided ones, suggesting that pre-dividing corn ears reduces grain damage. An experiment using the Lianchuang 825 variety examined the effect of moisture content and the divided rate of corncobs (DRC) on grain damage. The results showed that as moisture content increased from 25% to 37%, grain damage to undivided ears increased from 3.75% to 37.71%. Dividing corn ears before threshing significantly reduced damage, with an eight-piece division reducing damage by approximately 70% across all moisture levels. Verification with the Jinyu 1233 variety confirmed that a higher DRC consistently reduced damage. This study provides a new approach to reducing damage in moist corn threshing and aids in the development of low-damage threshing devices. Full article

(This article belongs to the Special Issue Innovative Design and Application of Modern Agricultural Machinery Systems in Cropping Systems)

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24 pages, 12131 KiB

Open AccessArticle

Reproductive Structures of Female Phytoseiulus persimilis (Acari: Phytoseiidae) and the Development of Egg and Embryo in the Body

by Binting Huang, Mingxia Li, Xiaohuan Jiang, Bo Zhang, Yong Huang and Xuenong Xu

Agriculture 2024, 14(9), 1647; https://doi.org/10.3390/agriculture14091647 (registering DOI) - 20 Sep 2024

Abstract

The Phytoseiulus persimilis specialized in preying on Tetranychus species, with particularly strong predation capability against Tetranychus urticae. To investigate the morphology of female reproductive structures and effects of different gravid times on structures of oocytes and embryos in Phytoseiulus persimilis, we [...] Read more.

The Phytoseiulus persimilis specialized in preying on Tetranychus species, with particularly strong predation capability against Tetranychus urticae. To investigate the morphology of female reproductive structures and effects of different gravid times on structures of oocytes and embryos in Phytoseiulus persimilis, we employed paraffin sectioning, transmission electron microscopy (TEM), and scanning electron microscopy (SEM) on the model species of predatory mite Phytoseiulus persimilis. The female adult possessed several reproductive organs, including paired solenostomes, major ducts, embolus, calyces, and vesicles within the sperm-access system, as well as lyrate organ and the ovary. Furthermore, the reproductive system also encompassed the uterus, vagina, and genital pore, which were involved in egg development and expulsion. The solenostomes were situated between the third and fourth legs, and they were scarcely discernible in virgin, but they became apparent during mating. The occurrence of mating significantly influenced the nucleus of lyrate organ. In virgin, the nucleus exhibited underdeveloped morphology, whereas in mated individuals, it was well-formed. However, the duration of mating did not impact its development. The cellular structure of the ovary was solely associated with the stage of the surrounding oocyte and was not directly linked to mating occurrences. The uterus was barely visible outside of mating periods but became observable 12 h after mating when eggs were present within the body. At this point, it opened in preparation for egg laying when both the vagina and reproductive opening were open. Positioned in front of the vesicle but behind the ovary was the lyrate organ, with its lower part housing the uterus. The vagina was connected to the genital pore. No significant difference was observed in oocyte morphology between the virgin ovaries and the mated. Oocyte development occurred through four stages: during stage I (4–9 h after mating), yolk accumulation took place; stage II (10 h after mating) involved egg relocation; stage III (12–13 h after mating) was marked by eggshell formation; finally, at stage IV (14–16 h after mating), embryonic development commenced, leading to egg deposition. The fusion of sperm and egg occurred approximately 9–10 h after mating. These findings established a solid foundation for investigating the Phytoseiid reproductive mechanisms. Full article

(This article belongs to the Special Issue Comprehensive Application and Prospects of New Technologies for Plant Protection)

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25 pages, 9183 KiB

Open AccessArticle

A High-Accuracy Contour Segmentation and Reconstruction of a Dense Cluster of Mushrooms Based on Improved SOLOv2

by Shuzhen Yang, Jingmin Zhang and Jin Yuan

Agriculture 2024, 14(9), 1646; https://doi.org/10.3390/agriculture14091646 (registering DOI) - 20 Sep 2024

Abstract

This study addresses challenges related to imprecise edge segmentation and low center point accuracy, particularly when mushrooms are heavily occluded or deformed within dense clusters. A high-precision mushroom contour segmentation algorithm is proposed that builds upon the improved SOLOv2, along with a contour [...] Read more.

This study addresses challenges related to imprecise edge segmentation and low center point accuracy, particularly when mushrooms are heavily occluded or deformed within dense clusters. A high-precision mushroom contour segmentation algorithm is proposed that builds upon the improved SOLOv2, along with a contour reconstruction method using instance segmentation masks. The enhanced segmentation algorithm, PR-SOLOv2, incorporates the PointRend module during the up-sampling stage, introducing fine features and enhancing segmentation details. This addresses the difficulty of accurately segmenting densely overlapping mushrooms. Furthermore, a contour reconstruction method based on the PR-SOLOv2 instance segmentation mask is presented. This approach accurately segments mushrooms, extracts individual mushroom masks and their contour data, and classifies reconstruction contours based on average curvature and length. Regular contours are fitted using least-squares ellipses, while irregular ones are reconstructed by extracting the longest sub-contour from the original irregular contour based on its corners. Experimental results demonstrate strong generalization and superior performance in contour segmentation and reconstruction, particularly for densely clustered mushrooms in complex environments. The proposed approach achieves a 93.04% segmentation accuracy and a 98.13% successful segmentation rate, surpassing Mask RCNN and YOLACT by approximately 10%. The center point positioning accuracy of mushrooms is 0.3%. This method better meets the high positioning requirements for efficient and non-destructive picking of densely clustered mushrooms. Full article

(This article belongs to the Special Issue Intelligent Agricultural Machinery and Robots: Embracing Technological Advancements for a Sustainable and Highly Efficient Agricultural Future)

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22 pages, 6605 KiB

Open AccessArticle

Design and Experimentation of Targeted Deep Fertilization Device for Corn Cultivation

by Zhongying Qi, Cunliang Liu, Yao Wang, Zhiwei Zhang and Xiaobo Sun

Agriculture 2024, 14(9), 1645; https://doi.org/10.3390/agriculture14091645 - 20 Sep 2024

Abstract

In response to the challenges of low fertilizer utilization rates, excessive application amounts, and difficulties in precise targeted fertilization during the middle tillage and top-dressing period for corn, a targeted deep fertilization device is designed, integrating mechanical structure design and automatic control technology. [...] Read more.

In response to the challenges of low fertilizer utilization rates, excessive application amounts, and difficulties in precise targeted fertilization during the middle tillage and top-dressing period for corn, a targeted deep fertilization device is designed, integrating mechanical structure design and automatic control technology. The device mainly includes a strong discharge fertilization device and a targeted fertilization control system. The fertilization device has been designed, and the main factors affecting the performance of the fertilization wheel have been identified. Based on the structure, a strong discharge fertilization plate mechanism has been added, and a mechanical model for the fertilization wheel during the refilling and discharging processes has been constructed. A targeted fertilization control system for corn has been developed that utilizes a photoelectric sensor to detect the position of the corn plants. A microcontroller combines the plant position information and the device moving speed to adjust the intermittent rotation of the stepper motor in real time, achieving targeted deep fertilization for corn. Coupled simulation analysis was conducted using discrete element software EDEM and dynamic software Adams. Through single-factor and multi-factor experiments, the main factors affecting fertilization performance were analyzed, and the optimal structural parameters for the fertilization wheel were determined. Bench validation tests were conducted, and the results demonstrated that under forward speeds of 0.4 to 1.2 m/s, the coefficient of variation of the fertilizer application rate per hole of the discharge device ranged from 2.02% to 4.46%, the error in fertilizer application rate per hole ranged from 7.12% to 12.18%, the average length of fertilizer application holes ranged from 72.5 mm to 130.2 mm, and the coefficient of variation of hole length stability ranged from 1.94% to 3.54%. These parameters were consistent with the results from the simulation tests, and the operational performance met the requirements. Finally, field tests validated the overall operational performance of the device. When the device’s speed ranged from 0.4 m/s to 1.2 m/s, the coefficient of variation of the fertilizer application rate per hole, the error in fertilizer application rate per hole, the average length of fertilizer application holes, the coefficient of variation of hole length stability, and the qualification rate of fertilization position were 3.63%, 10.46%, 108.8 mm, 2.96%, and 87.16%, respectively. The overall performance of the device is stable and meets the requirements for targeted deep fertilization in corn cultivation. Full article

(This article belongs to the Section Agricultural Technology)

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15 pages, 5302 KiB

Open AccessArticle

Study on the Contact Parameter Calibration of the Maize Kernel Polyhedral Discrete Element Model

by Huhu Chen, Haipeng Lin, Xuefeng Song, Fengwei Zhang, Fei Dai, Ting Yang and Baicheng Li

Agriculture 2024, 14(9), 1644; https://doi.org/10.3390/agriculture14091644 - 19 Sep 2024

Abstract

During maize production and transportation, maize kernels frequently interact with mechanical components. To accurately simulate the interaction process between maize and mechanical components, it is essential to establish a reliable maize kernel model and input precise contact parameters. This study established polyhedral discrete [...] Read more.

During maize production and transportation, maize kernels frequently interact with mechanical components. To accurately simulate the interaction process between maize and mechanical components, it is essential to establish a reliable maize kernel model and input precise contact parameters. This study established polyhedral discrete element models of different maize kernels and calibrated the contact parameters between maize kernels and steel plates using the inclined plane method. The coefficients of restitution, static friction, and dynamic friction between maize and steel sheets were measured to be 0.5, 0.545, and 0.213, respectively. Subsequently, the contact parameters between maize kernels were determined through steepest climb tests and central composite design response surface tests. Then, the above parameters were optimized using Design-Expert software. The coefficients of restitution, static friction, and dynamic friction between maize kernels were measured to be 0.318, 0.182, and 0.232, respectively. Finally, the optimized parameters were validated using the angle of repose experiment, which found that the relative error between the experiment and the simulation was only 1.24%. The results indicated that the obtained contact parameters were accurate and reliable. Full article

(This article belongs to the Section Agricultural Technology)

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14 pages, 7196 KiB

Open AccessArticle

Identification of Ascorbate Oxidase Genes and Their Response to Cold Stress in Citrus sinensis

by Xiaoyong Xu, Xingchen Miao, Naiyi Deng, Mengge Liang, Lun Wang, Lijuan Jiang and Shaohua Zeng

Agriculture 2024, 14(9), 1643; https://doi.org/10.3390/agriculture14091643 (registering DOI) - 19 Sep 2024

Abstract

Ascorbate oxidase (AAO) plays an important role in maintaining cellular redox homeostasis, thereby influencing plant growth, development, and responses to both biotic and abiotic stresses. However, there has been no systematic characterization of AAO genes in Citrus, especially their roles in response [...] Read more.

Ascorbate oxidase (AAO) plays an important role in maintaining cellular redox homeostasis, thereby influencing plant growth, development, and responses to both biotic and abiotic stresses. However, there has been no systematic characterization of AAO genes in Citrus, especially their roles in response to cold stress. In the present study, nine AAO genes were identified in C. sinensis through bioinformatics analyses, exhibiting uneven distribution across four chromosomes. All CsAAOs possessed three conserved domains and were predicted to localize in the apoplast. The CsAAO gene family displayed varied intron–exon patterns. Phylogenetic analysis categorized the CsAAO family into three main clades (Clade A–C), suggesting distinct biological functions. Collinearity and Ka/Ks analysis revealed three duplicate gene pairs within the CsAAO gene family, with all duplicated CsAAOs primarily evolving under purifying selection. Analysis of cis-acting elements showed the presence of multiple hormone response elements and stress response elements within the CsAAO promoters. The computational analysis of microRNA target transcripts suggested that CsAAO9 may be a target of csi-miR156. RNA-Seq data demonstrated high expression levels of CsAAOs in roots and young fruits, while qRT-PCR analysis showed significant upregulation of six CsAAOs in response to cold treatment. Furthermore, the activities of CsAAOs exhibited a pattern of initial decrease followed by an increase after exposure to low temperatures. These findings offer important insights into the role of CsAAOs in response to cold stress. Furthermore, AAOs could be target genes for breeding crops with better cold resistance. Full article

(This article belongs to the Special Issue Abiotic Stress Responses in Horticultural Crops)

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17 pages, 5564 KiB

Open AccessArticle

Modeling for Apple-Slice Drying in Carbon Dioxide Gas

by Tien Cong Do, Quoc Tuan Le and Thi Thu Hang Tran

Agriculture 2024, 14(9), 1642; https://doi.org/10.3390/agriculture14091642 - 19 Sep 2024

Abstract

In this study, a numerical model of a modified air-drying process of apple slices that considers the conjugate heat and mass transfer in the drying chamber is developed. Inside the apple slice sample, the continuum model is incorporated to describe the non-isothermal two-phase [...] Read more.

In this study, a numerical model of a modified air-drying process of apple slices that considers the conjugate heat and mass transfer in the drying chamber is developed. Inside the apple slice sample, the continuum model is incorporated to describe the non-isothermal two-phase transport. The intra- and extra-sample heat, mass, and momentum transfer are coupled to simulate the transportation phenomena inside the drying chamber using the finite volume method implemented in computational fluid dynamic software (COMSOL Multiphysics 6.0). In this manner, temperature, velocity, moisture content of the drying agent inside the chamber, sample temperature, and moisture content distributions can be predicted. The validity of the proposed model is confirmed by a good agreement between the numerical and experimental data in terms of the overall evaporation rate and temperature. The simulation results indicate that the maldistribution of the convective heat and mass transfer resistance on the sample surface is significant. This can be explained by the nonuniform velocity distribution inside the drying chamber. Additionally, both experimental and numerical observations show that the drying process can be divided into two periods: the quasi-constant drying rate and falling drying rate periods. The impact of dryer operational conditions on the drying process is numerically investigated. Full article

(This article belongs to the Section Agricultural Product Quality and Safety)

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16 pages, 6522 KiB

Open AccessArticle

Experiment and Analysis of Physical Properties of Sweet Potato Varieties at Different Harvesting Periods

by Jiwen Peng, Haiyang Shen, Gongpu Wang, Zhilong Zhang, Baoliang Peng, Guangyu Xue, Sen Huang, Wenhao Zheng and Lianglong Hu

Agriculture 2024, 14(9), 1641; https://doi.org/10.3390/agriculture14091641 - 19 Sep 2024

Abstract

To fill the research gap in the mechanical and physical properties of different varieties of sweet potatoes at different points in the harvest period and to provide a theoretical basis for the design of key components of the sweet potato harvester, the physical [...] Read more.

To fill the research gap in the mechanical and physical properties of different varieties of sweet potatoes at different points in the harvest period and to provide a theoretical basis for the design of key components of the sweet potato harvester, the physical properties of Su-Shu 16, Su-Shu 36, and Ning-Zi 4 during the harvest period were studied at three time points: 15 October, 25 October, and 4 November 2023. The moisture content of sweet potatoes was determined using the DGF30/7-IA electric hot air-drying oven. The results showed that the moisture content of sweet potatoes decreased with increasing growth time at three different time points during the harvest period. The moisture content of Su-Shu 16 was, on average, 12.74% higher than that of Su-Shu 36, while the moisture content of Ning-Zi 4 was, on average, 8.07% higher than that of Su-Shu 36. The density of Su-Shu 36 measured by the drainage method is greater than that of Su-Shu 16 and Ning-Zi 4, but the difference is relatively small, and the density tends to decrease slowly with the increase of growth time. Using an electronic universal testing machine, compression tests were conducted on Su-Shu 16, Su-Shu 36, and Ning-Zi 4 at loading speeds of 5 mm/min and 10 mm/min, respectively. The results showed that the compressive strength limit range of Su-Shu 36 was slightly higher than that of Su-Shu 16 and significantly higher than that of Ning-Zi 4. The Poisson’s ratio, elastic modulus, and shear modulus values of Su-Shu 16 and Su-Shu 36 were similar and much higher than those of Ning-Zi 4. Studying sweet potatoes’ growth and physical characteristics for different purposes can provide data references for the design of digging depth, working width, and conveyor chain gap of sweet potato harvesters, as well as data references for sweet potato simulation experiments. Full article

(This article belongs to the Special Issue From Planting to Harvesting: The Role of Agricultural Machinery in Crop Cultivation)

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19 pages, 13127 KiB

Open AccessArticle

Optimization of the Camellia oleifera Fruit Harvester Engine Compartment Heat Dissipation Based on Temperature Experiments and Airflow Field Simulation

by Wenfu Tong, Kai Liao, Lijun Li, Zicheng Gao, Fei Chen and Hong Luo

Agriculture 2024, 14(9), 1640; https://doi.org/10.3390/agriculture14091640 - 19 Sep 2024

Abstract

The Camellia oleifera fruit harvester, a specialized agricultural device, is engineered for efficient operation within the densely planted C. oleifera groves of China’s undulating terrains. Its design features a notably small footprint to navigate the constrained spaces between trees. With the enhancement of [...] Read more.

The Camellia oleifera fruit harvester, a specialized agricultural device, is engineered for efficient operation within the densely planted C. oleifera groves of China’s undulating terrains. Its design features a notably small footprint to navigate the constrained spaces between trees. With the enhancement of the functionality and power of the harvester, the engine compartment becomes even more congested. This, while beneficial for performance, complicates heat dissipation and reduces harvesting efficiency. In this study, experiments were initially conducted to collect temperature data from the main heat-generating components and parts susceptible to high temperatures within the harvester’s engine compartment. Subsequently, a 3D model was developed for numerical simulations, leading to the proposal of optimization schemes for the engine compartment’s structure and the validation of these schemes’ feasibility. A comparison of the experimental data, both before and after optimization, revealed a significant reduction in the surface temperatures of components within the engine compartment following optimization. As a result, the heat dissipation of the engine compartment has been greatly optimized. The harvester has demonstrated prolonged normal operation, enhancing the reliability and economy of the harvester. Full article

(This article belongs to the Special Issue Agricultural Machinery and Technology for Fruit Tree Management)

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18 pages, 20690 KiB

Open AccessArticle

Halving Environmental Impacts of Diverse Crop Production in Fujian, China through Optimized Nitrogen Management

by Jun Li, Minglei Wang, Wenjiao Shi and Xiaoli Shi

Agriculture 2024, 14(9), 1639; https://doi.org/10.3390/agriculture14091639 - 19 Sep 2024

Abstract

Nitrogen (N) fertilizer is essential for agricultural production as it is the main nutrient driving crop growth. However, in China, only one-third of applied N fertilizer is effectively absorbed by crops, while the rest leads to significant environmental impacts. In this study, we [...] Read more.

Nitrogen (N) fertilizer is essential for agricultural production as it is the main nutrient driving crop growth. However, in China, only one-third of applied N fertilizer is effectively absorbed by crops, while the rest leads to significant environmental impacts. In this study, we introduced a nitrogen threshold boundary (NTB) approach to establish different thresholds for N use efficiency (NUE) and N surplus without affecting crop yield. We also developed an integrated assessment framework to systematically evaluate the potential for improving N utilization and reducing environmental impacts in the production of grain crops (rice, wheat, maize, and soybeans) and cash crops (tea, fruits, and vegetables) at the county level in Fujian Province. Three N management strategies were evaluated: a scenario with reduced N surplus (S1), a scenario with increased NUE (S2), and a combined scenario that simultaneously reduces N surplus and increases NUE (S3). The predictions indicate that, under the aforementioned scenarios, there will be a decrease of 66%, 58%, and 71% in N application without affecting crop yields, respectively. Correspondingly, N surplus will decrease by 65%, 56%, and 67%, while greenhouse gas (GHG) emissions will decrease by 54%, 48%, and 57%. In addition, NUE will increase by 23%, 17% and 25%, respectively. It is notable that scenario S3 demonstrated the greatest potential for improvement. For cash crops, N application will decrease by 65–78%, NUE will increase by 13–21%, N surplus will decrease by 63–74%, and GHG emissions will reduce by 66–78%. In contrast, for grain crops, N application will decrease by 27–38%, NUE will increase by 9–13%, N surplus will decrease by 26–37%, and GHG emissions will reduce by 24–28%. Overall, the potential for improvement is greater for cash crops compared to grain crops. The application of the assessment framework in this study demonstrates its effectiveness as a valuable tool for promoting green and sustainable development in conventional agricultural regions. Full article

(This article belongs to the Section Crop Production)

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30 pages, 1464 KiB

Open AccessReview

Abiotic Stress in Cotton: Insights into Plant Responses and Biotechnological Solutions

by Akshay Milind Patil, Bhausaheb D. Pawar, Sopan Ganpatrao Wagh, Harshraj Shinde, Rahul Mahadev Shelake, Nanasaheb R. Markad, Nandu K. Bhute, Jan Červený and Rajendra. S. Wagh

Agriculture 2024, 14(9), 1638; https://doi.org/10.3390/agriculture14091638 - 19 Sep 2024

Abstract

Climate change has rapidly increased incidences of frequent extreme abiotic stresses, such as heat, drought, salinity, and waterlogging. Each of these stressors negatively affects the cotton crop (Gossypium spp.) and results in significant yield decreases. Every stressful event causes specific changes in [...] Read more.

Climate change has rapidly increased incidences of frequent extreme abiotic stresses, such as heat, drought, salinity, and waterlogging. Each of these stressors negatively affects the cotton crop (Gossypium spp.) and results in significant yield decreases. Every stressful event causes specific changes in the metabolism and physiology of plants, which are linked to complex molecular alterations. Understanding the molecular mechanisms that regulate a plant’s response to stress is essential to developing stress-resistant cotton varieties that can withstand various stress factors. Gene expressions in response to multiple stresses have been studied and mapped. These genes include ion transporters and heat shock proteins, which are vital to allowing adaptive responses. These approaches showed the ability to employ advanced genome sequencing and multi-omics techniques to identify dynamic gene expression patterns and elucidate intricate regulatory networks. Using genetic variation in combination with molecular techniques, it would be possible to generate stress-resilient cotton varieties that would enable sustainable cotton output in the face of abiotic stresses. Here, we reviewed the effects of major abiotic stressors on cotton plants, such as heat, salinity, drought, heavy metals, and waterlogging. We also examine the vast network of proteins, genes, and stress-sensitive signaling pathways that help cotton tolerate abiotic stress. Full article

(This article belongs to the Section Crop Production)

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19 pages, 4009 KiB

Open AccessArticle

Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C₃ and C₄ under Bis(2,4,6-tribromophenoxy) Ethane Exposure

by Yixuan Chen, Sen Wang, Yuru Li, Wanyu Liu and Zhenchuan Niu

Agriculture 2024, 14(9), 1637; https://doi.org/10.3390/agriculture14091637 - 18 Sep 2024

Abstract

This study investigated the response of a bacterial community’s structure and function in the rhizosphere soil of C₃ and C₄ plants under bis(2,4,6-tribromophenoxy) ethane (BTBPE) exposure. The bacterial community composition was determined using 16S rRNA sequencing, while FAPROTAX and PICRUSt 2 [...] Read more.

This study investigated the response of a bacterial community’s structure and function in the rhizosphere soil of C₃ and C₄ plants under bis(2,4,6-tribromophenoxy) ethane (BTBPE) exposure. The bacterial community composition was determined using 16S rRNA sequencing, while FAPROTAX and PICRUSt 2 were employed for functional predictions. Results showed significant differences between C₃ and C₄ plants in terms of bacterial community structure. C₃ plants exhibited higher abundances of Proteobacteria, Bacteroidetes at the phylum level and Sphingomicrobium at the genus level, compared to C₄ plants. Conversely, C₄ plants had higher abundances of Actinobacteria and Patescibacteria at the phylum level and Nocardioides at the genus level. LEfSe and function prediction analyses revealed that the rhizosphere soil bacteria in C₃ plants exhibited significantly higher enrichment in nitrogen fixation functions (p < 0.05), whereas C₄ plants showed a significantly higher relative abundance of bacteria and functions related to organic pollutant degradation (p < 0.05). These findings suggest that the rhizosphere soil bacteria of C₃ plants exhibit a stronger response to BTBPE exposure in nitrogen metabolism-related processes, while C₄ plants possess superior biodegradation ability compared to C₃ plants. Full article

(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)

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16 pages, 4675 KiB

Open AccessArticle

Coupling Coordination and Spatial–Temporal Evolution of the Water–Land–Ecology System in the North China Plain

by Liang Chen, Xiaogang Wang, Mouchao Lv, Jing Su and Bo Yang

Agriculture 2024, 14(9), 1636; https://doi.org/10.3390/agriculture14091636 - 18 Sep 2024

Abstract

Exploring the coordination of agricultural water resources (W), cultivated land (L), and the ecoenvironment (E) system is crucial for sustainable agriculture in the North China Plain (NCP). However, the synergistic effects of this composite system remain unclear. Coupling coordination degrees (CCDs) of 53 [...] Read more.

Exploring the coordination of agricultural water resources (W), cultivated land (L), and the ecoenvironment (E) system is crucial for sustainable agriculture in the North China Plain (NCP). However, the synergistic effects of this composite system remain unclear. Coupling coordination degrees (CCDs) of 53 cities in the NCP for the years 2011, 2015, and 2020 were evaluated using the TOPSIS model, and the coupling coordination model, combined with the analytic hierarchy process and entropy weight method. The evaluation results were further analyzed to identify obstacle factors. The findings reveal the following: (1) The comprehensive development level showed a fluctuating upward trend, with closeness values ranging from 0.418 to 0.574 in 2020, indicating an improvement of 14.6–52.3% compared to 2011. The coefficient of variation (CV) for each province rose from 12.65% in 2011 to 13.64% and subsequently declined to 9.12% by 2020. (2) Between 2011 and 2020, CCDs of the W–L–E composite system exhibited a consistent upward trend. In 2020, regions with intermediate or better coordination accounted for 34.0%, and were primarily located in Jiangsu Province, the southern part of Anhui Province, the northwestern part of Shandong Province, and the municipalities of Beijing and Tianjin. (3) In 2011 and 2015, significant obstacle factors included the water quality compliance rate and the per capita disposable income of rural residents, although these were not primary obstacles in 2020. The water supply modulus and multiple cropping index were major obstacle factors in 2011, 2015, and 2020. Developing water-appropriate cropping patterns based on regional water resource endowment is the essential path for the sustainable and coordinated development of water, land, and ecology in the NCP. Full article

(This article belongs to the Section Agricultural Water Management)

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24 pages, 9931 KiB

Open AccessArticle

Peanut Pickup Combine Harvester Seedling Vines Crushing Mechanism Performance Enhancement and Pilot Studies

by Jinbiao Zhang, Zhuang Zhao, Zenghui Gao, Yu Tian, Dongwei Wang and Nan Xu

Agriculture 2024, 14(9), 1635; https://doi.org/10.3390/agriculture14091635 - 18 Sep 2024

Abstract

Aiming at the current peanut pickup combine harvester seedling vines crushing mechanism operation qualified seedling length rate is low, the impurity rate is high, and the seedling vines crushing mechanism is optimized design. On the basis of the material characteristics of peanut seedling [...] Read more.

Aiming at the current peanut pickup combine harvester seedling vines crushing mechanism operation qualified seedling length rate is low, the impurity rate is high, and the seedling vines crushing mechanism is optimized design. On the basis of the material characteristics of peanut seedling vines, taking the crushing mechanism as the research carrier, the interaction mechanism of the seedling vine mechanism was analyzed. Establish the mechanical model and motion trajectory model in the crushing process, simulate the peanut seedling vines crushing process based on the discrete element method, analyze the influence of the cutter shaft rotational speed, movement speed, and bending angle on the crushing of peanut seedling vines, and establish the regression model, and the results of the research show that the influence factors in the main order of priority are: knife shaft speed > movement speed > bending angle The optimal parameter combination is knife shaft speed 2171.94 r/min, movement speed 0.79 m/s, and bending angle 45°. According to the field test conditions, it is determined that the knife shaft rotational speed of 2170 r/min, movement speed of 0.8 m/s, and bending angle of 45° can make the peanut seedling vines crushing mechanism of the work performance to achieve a qualified seedling length rate of 97.292%, the rate of impurity content of 2.746%, and the error with the predicted value is less than 2%, which indicates that this study can provide a reference for the optimal design of the seedling vines crushing mechanism of the peanut pickup combine harvester. Full article

(This article belongs to the Section Agricultural Technology)

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