Estimation of plant leaf water content based on spectroscopy.

Introduction: Leaf water content is a key physiological indicator of plant growth and health status. Constructing leaf water content estimation models based on spectroscopy is an effective method for monitoring plant physiological conditions.

Methods: To improve the accuracy of leaf water content estimation and develop models applicable to different plants, this study collected 1,680 groups of hyperspectral and water content data from peach tree leaves.

Synergistic adsorption mechanism of heavy metals on zinc oxide/phosphate modified gel-biochar composites.

In this study, waste catering oil was processed into a gel (NJ), sesame straw was processed into biochar (ZM), and the two were modified with zinc oxide nanoparticles and phosphoric acid to form NJZ and ZMP, respectively. Both materials were then coupled to obtain a polymer gel-biochar composite (N-Z). The materials were characterised by infrared spectroscopy and scanning electron microscopy, and the adsorption kinetics and isothermal adsorption characteristics of copper(II) ions (Cu) in water were analysed.

The Application of an Intelligent -Harvesting Device Based on FES-YOLOv5s.

To address several challenges, including low efficiency, significant damage, and high costs, associated with the manual harvesting of , in this study, a machine vision-based intelligent harvesting device was designed according to its agronomic characteristics and morphological features. This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate .

Lameness Recognition of Dairy Cows Based on Compensation Behaviour Analysis by Swing and Posture Features from Top View Depth Image.

Top-view systems for lameness detection have advantages such as easy installation and minimal impact on farm work. However, the unclear lameness motion characteristics of the back result in lower recognition accuracy for these systems. Therefore, we analysed the compensatory behaviour of cows based on top-view walking videos, extracted compensatory motion features (CMFs), and constructed a model for recognising lameness in cows.

Hg removal characteristics of a strain of mercury-tolerant bacteria screened from heavy metal-contaminated soil in a molybdenum-lead mining area.

In this study, the mercury-tolerant strain LTC105 was isolated from a contaminated soil sample collected from a molybdenum-lead mine in Luanchuan County, Henan Province, China. The strain was shown to be highly resistant to mercury, with a minimum inhibitory concentration (MIC) of 32 mg·L. After a 24-h incubation in LB medium with 10 mg·L Hg, the removal, adsorption, and volatilization rates of Hg were 97.

Improved YOLO-FastestV2 wheat spike detection model based on a multi-stage attention mechanism with a LightFPN detection head.

The number of wheat spikes has an important influence on wheat yield, and the rapid and accurate detection of wheat spike numbers is of great significance for wheat yield estimation and food security. Computer vision and machine learning have been widely studied as potential alternatives to human detection. However, models with high accuracy are computationally intensive and time consuming, and lightweight models tend to have lower precision.

Research on SPAD Estimation Model for Spring Wheat Booting Stage Based on Hyperspectral Analysis.

With the rapid progression of agricultural informatization technology, the methodologies of crop monitoring based on spectral technology are constantly upgraded. In order to carry out the efficient, precise and nondestructive detection of relative chlorophyll (SPAD) during the booting stage, we acquired hyperspectral reflectance data about spring wheat vertical distribution and adopted the fractional-order differential to transform the raw spectral data. After that, based on correlation analysis, fractional differential spectra and fractional differential spectral indices with strong correlation with SPAD were screened and fused.

Hydrothermal synthesis and electrochemical properties of Sn-based peanut shell biochar electrode materials.

Using activated-carbon-based electrodes derived from waste biomass in super-capacitor energy technologies is an essential future strategy to achieve sustainable energy and environmental protection. Biomass feed-stocks such as bamboo and straw have been used to prepare activated carbon-based electrodes. This experiment used peanut shells (waste biomass) as carbon precursors.

Performance Evaluation of a Cicada-Inspired Subsoiling Tool Using DEM Simulations.

Subsoiling practice is an essential tillage practice in modern agriculture. Tillage forces and energy consumption during subsoiling are extremely high, which reduces the economic benefits of subsoiling technology. In this paper, a cicada-inspired biomimetic subsoiling tool (CIST) was designed to reduce the draught force during subsoiling.

Design and test of potato seeding apparatus based on double-layer seed picking scoop structure.

At present, potato seeders in China generally have poor uniformity of seed rows and high coefficients of variation in plant spacing during seed rows, causing difficulties for subsequent mechanized plant protection and harvesting. Based on the effect of seed discharge to analyze the sowing process, a potato seed discharger with a double-layer seed picking spoon structure was designed. By analyzing the seed discharging mechanism and its operation process, the shape and size structural parameters of the seed picking spoon were determined.

Hydroponic lettuce defective leaves identification based on improved YOLOv5s.

Achieving intelligent detection of defective leaves of hydroponic lettuce after harvesting is of great significance for ensuring the quality and value of hydroponic lettuce. In order to improve the detection accuracy and efficiency of hydroponic lettuce defective leaves, firstly, an image acquisition system is designed and used to complete image acquisition for defective leaves of hydroponic lettuce. Secondly, this study proposed EBG_YOLOv5 model which optimized the YOLOv5 model by integrating the attention mechanism ECA in the backbone and introducing bidirectional feature pyramid and GSConv modules in the neck.

Quality Information Detection of Based on a Portable Spectrum Acquisition Device.

As one of the most popular edible fungi in the market, the quality of will determine its sales volume. Therefore, to achieve rapid and nondestructive testing of the quality of , this study first built a portable spectrum acquisition device for . The Ocean Spectromeper was used to calibrate the spectral data of the device, and the linear regression analysis method was combined to analyze the two.

Parameter calibration of the discrete element simulation model for soaking paddy loam soil based on the slump test.

The discrete element computer simulation method is an effective tool that enables the study of the interaction mechanism between the pulping components and the paddy soil during the paddy field pulping process. The findings are valuable in optimizing the parameters of the paddy beating device to improve its working quality and efficiency. However, the lack of accurate soil models for paddy soil has limited the application and development of the discrete element method in paddy pulping research.

Isolation and Identification of Mercury-Tolerant Bacteria LBA119 from Molybdenum-Lead Mining Soils and Their Removal of Hg.

Aims: To screen heavy metal-tolerant strains from heavy metal-contaminated soil in mining areas and determine the tolerance of the strains to different heavy metals and their removal rates through experiments.

Methods: Mercury-resistant strain LBA119 was isolated from mercury-contaminated soil samples in Luanchuan County, Henan Province, China. The strain was identified by Gram staining, physiological and biochemical tests, and 16S rDNA sequences.

Modelling and analysis of penetration resistance of probes in cultivated soils.

At present, the measurement of tillage depth is mainly based on manual measurement, but the manual raking method results in low measurement accuracy and high labor intensity. Due to the complexity of soil, theoretical research on tillage depth is relatively scarce. In order to provide a new research direction and research idea for soil stratification, topsoil was taken as the research object of this paper.

Improving effect of disaccharides and maltodextrin on preparation of egg yolk powder by microwave-assisted freeze-drying: Functional properties, structural properties, and retention rate of active IgY.

The preparation of egg yolk powder (EYP) with excellent solubility and high retention of active IgY is of great significance for increasing the added value and promoting the application of EYP. A new method of preparing EYP by microwave-assisted freeze-drying (MFD) was researched. Confocal laser scanning microscopy results demonstrated that the supplementation of excipients (sucrose, trehalose, and maltodextrin) could inhibit lipoproteins aggregation in egg yolk induced by freezing.

Selective transplantation method of leafy vegetable seedlings based on ResNet 18 network.

To solve the problem of low survival rate caused by unscreened transplanting of seedlings. This study proposed a selective transplanting method of leafy vegetable seedlings based on the ResNet 18 network. Lettuce seedlings were selected as the research object, and a total of 3,388 images were obtained in the dataset.

Calibration and analysis of discrete element simulation parameters of Chinese cabbage seeds.

Objective: To improve the accuracy of parameters used in discrete element simulation test of Chinese cabbage seeds harvesting process.

Methods: Firstly, the key physical parameters of Chinese cabbage seeds were measured. According to the results, the discrete element simulation model was established and the value range of simulation test parameters was determined.

A Cascaded Model Based on EfficientDet and YOLACT++ for Instance Segmentation of Cow Collar ID Tag in an Image.

In recent years, many imaging systems have been developed to monitor the physiological and behavioral status of dairy cows. However, most of these systems do not have the ability to identify individual cows because the systems need to cooperate with radio frequency identification (RFID) to collect information about individual animals. The distance at which RFID can identify a target is limited, and matching the identified targets in a scenario of multitarget images is difficult.

A Framework for Identification of Healthy Potted Seedlings in Automatic Transplanting System Using Computer Vision.

Automatic transplanting of seedlings is of great significance to vegetable cultivation factories. Accurate and efficient identification of healthy seedlings is the fundamental process of automatic transplanting. This study proposed a computer vision-based identification framework of healthy seedlings.

Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.

Objective: To realize the regulation of the position of corn seed planting in precision farming, an intelligent monitoring system is designed for corn seeding based on machine vision and the Genetic Algorithm-optimized Back Propagation (GABP) algorithm.

Methods: Based on the research on precision positioning seeding technology, comprehensive application of sensors, Proportional Integral Derivative (PID) controllers, and other technologies, combined with modern optimization algorithms, the online dynamic calibration controls of line spacing and plant spacing are implemented. Based on the machine vision and GABP algorithm, a test platform for the seeding effect detection system is designed to provide a reference for further precision seeding operations.