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ObjectiveFarmland consolidation for agricultural mechanization in hilly and mountainous areas can alter the landscape pattern, elevation, slope and microgeomorphology of cultivated land. It is of great significance to assess the ecological risk of cultivated land to provide data reference for the subsequent farmland consolidation for agricultural mechanization. This study aims to assess the ecological risk of cultivated land before and after farmland consolidation for agricultural mechanization in hilly and mountainous areas, and to explore the relationship between cultivated land ecological risk and cultivated land slope.MethodsTwenty counties in Tongnan district of Chongqing city was selected as the assessment units. Based on the land use data in 2010 and 2020 as two periods, ArcGIS 10.8 and Excel software were used to calculate landscape pattern indices. The weights for each index were determined by entropy weight method, and an ecological risk assessment model was constructed, which was used to reveal the temporal and spatial change characteristics of ecological risk. Based on the principle of mathematical statistics, the correlation analysis between cultivated land ecological risk and cultivated land slope was carried out, which aimed to explore the relationship between cultivated land ecological risk and cultivated land slope.Results and DiscussionsComparing to 2010, patch density (PD), division (D), fractal dimension (FD), and edge density (ED) of cultivated land all decreased in 2020, while meant Patch Size (MPS) increased, indicating an increase in the contiguity of cultivated land. The mean shape index (MSI) of cultivated land increased, indicating that the shape of cultivated land tended to be complicated. The landscape disturbance index (U) decreased from 0.97 to 0.94, indicating that the overall resistance to disturbances in cultivated land has increased. The landscape vulnerability index (V) increased from 2.96 to 3.20, indicating that the structure of cultivated land become more fragile. The ecological risk value of cultivated land decreased from 3.10 to 3.01, indicating the farmland consolidation for agricultural mechanization effectively improved the landscape pattern of cultivated land and enhanced the safety of the agricultural ecosystem. During the two periods, the ecological risk areas were primarily composed of low-risk and relatively low-risk zones. The area of low-risk zones increased by 6.44%, mainly expanding towards the northern part, while the area of relatively low-risk zones increased by 6.17%, primarily spreading towards the central-eastern and southeastern part. The area of moderate-risk zones increased by 24.4%, mainly extending towards the western and northwestern part, while the area of relatively high-risk zones decreased by 60.70%, with some new additions spreading towards the northeastern part. The area of high-risk zones increased by 16.30%, with some new additions extending towards the northwest part. Overall, the ecological safety zones of cultivated relatively increased. The cultivated land slope was primarily concentrated in the range of 2° to 25°. On the one hand, when the cultivated land slope was less than 15°, the proportion of the slope area was negatively correlated with the ecological risk value. On the other hand, when the slope was above 15°, the proportion of the slope area was positively correlated with the ecological risk value. In 2010, there was a highly significant correlation between the proportion of slope area and ecological risk value for cultivated land slope within the ranges of 5° to 8°, 15° to 25°, and above 25°, with corresponding correlation coefficients of 0.592, 0.609, and 0.849, respectively. In 2020, there was a highly significant correlation between the proportion of slope area and ecological risk value for cultivated land slope within the ranges of 2° to 5°, 5° to 8°, 15° to 25°, and above 25°, with corresponding correlation coefficients of 0.534, 0.667, 0.729, and 0.839, respectively.ConclusionsThe assessment of cultivated land ecological risk in Tongnan district of Chongqing city before and after the farmland consolidation for agricultural mechanization, as well as the analysis of the correlation between ecological risk and cultivated land slope, demonstrate that the farmland consolidation for agricultural mechanization can reduce cultivated land ecological risk, and the proportion of cultivated land slope can be an important basis for precision guidance in the farmland consolidation for agricultural mechanization. Considering the occurrence of moderate sheet erosion from a slope of 5° and intense erosion from a slope of 10° to 15°, and taking into account the reduction of ecological risk value and the actual topographic conditions, the subsequent farmland consolidation for agricultural mechanization in Tongnan district should focus on areas with cultivated land slope ranging from 5° to 8° and 15° to 25°.

ObjectiveThe interaction between bisphenol E（BPE） and serum albumin was analyzed to provide a useful referrence for the rapid evaluation of the toxicological effect of bisphenols.MethodsElectropherograms of serum albumin with BPE under physiological conditions in vitro were determined using external calibration Hummel-Dreyer （HD） method by capillary electrophoresis. To obtain the interaction parameters， the experimental data were analyzed by three functional forms： Nonlinear equation， Scatchard equation and Klotz equation.ResultsThree form functions were fitted with the interaction parameters. The binding ratio of BPE and serum albumin was about 2. The interaction parameters showed that two kinds of serum albumin had the same number of binding sites， and the binding between different albumin and BPE were both non-covalent interactions.ConclusionAs a simple and effective method， external calibration HD method could be used to analyze the protein pollutant interaction in the food safety field. BPE showed similar moderate interaction with different serum albumin， which suggested that bisphenol compounds had similar pollution distribution regularity in human body and cattle.

To address the problem that the low-density canopy of greenhouse crops affects the robustness and accuracy of simultaneous localization and mapping (SLAM) algorithms, a greenhouse map construction method for agricultural robots based on multiline LiDAR was investigated. Based on the Cartographer framework, this paper proposes a map construction and localization method based on spatial downsampling. Taking suspended tomato plants planted in greenhouses as the research object, an adaptive filtering point cloud projection (AF-PCP) SLAM algorithm was designed. Using a wheel odometer, 16-line LiDAR point cloud data based on adaptive vertical projections were linearly interpolated to construct a map and perform high-precision pose estimation in a greenhouse with a low-density canopy environment. Experiments were carried out in canopy environments with leaf area densities (LADs) of 2.945-5.301 m 2 /m 3 . The results showed that the AF-PCP SLAM algorithm increased the average mapping area of the crop rows by 155.7% compared with that of the Cartographer algorithm. The mean error and coefficient of variation of the crop row length were 0.019 m and 0.217%, respectively, which were 77.9% and 87.5% lower than those of the Cartographer algorithm. The average maximum void length was 0.124 m, which was 72.8% lower than that of the Cartographer algorithm. The localization experiments were carried out at speeds of 0.2 m/s, 0.4 m/s, and 0.6 m/s. The average relative localization errors at these speeds were respectively 0.026 m, 0.029 m, and 0.046 m, and the standard deviation was less than 0.06 m. Compared with that of the track deduction algorithm, the average localization error was reduced by 79.9% with the proposed algorithm. The results show that our proposed framework can map and localize robots with precision even in low-density canopy environments in greenhouses, demonstrating the satisfactory capability of the proposed approach and highlighting its promising applications in the autonomous navigation of agricultural robots., Competing Interests: Author XZ was employed by company Beijing PAIDE Science and Technology Development Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Tan, Zhao, Zhai, Fu, Chen and Yang.)

Food quality and safety are issues of concern to the government, food industry, and consumers; hence, it is imperative to detect harmful substances in foodstuff. Traditional techniques for this purpose include biochemical methods and instrumental analysis methods such as chromatography and chromatography-mass spectrometry. These methods, however, are time-consuming and unable to obtain the spatial distribution of the analytes. Therefore, the development of rapid, non-destructive, real-time, and visual detection technologies has emerged as a hotspot in the field of food research. In recent years, hyperspectral imaging, which combines imaging and spectral technology, is rapidly gaining ground. This technique allows one to determine the geometrical characteristics and chemical composition of samples. Compared with traditional spectral technologies, hyperspectral imaging has the advantages of wide detection ranges, in addition to being real-time and non-destructive. At present, hyperspectral imaging is widely used in meat quality evaluation, detection of adulteration, and meat classification. In addition, Raman imaging is mainly used for the detection of illegal additives in food and for adulteration detection. This technology is fast, non-destructive, and low cost; furthermore, spectral and spatial information of the targets can be simultaneously obtained. Mass spectrometry imaging allows for the visualization and high-throughput analysis of sample tissues, without the need for complex sample preparation steps such as labeling and staining. Compared with other imaging technologies, mass spectrum information of substances can be obtained by mass spectrometry imaging. As a molecular visualized technology, it helps obtain the spatial distribution of nutrients and harmful substances in food. Mass spectrometry imaging has unique advantages in food research, e. g., it is used for molecular-level detection and accurate positioning of substances, and hence, it has excellent application prospects in this field. In this paper, recent literature data about imaging technologies in the field of food research, including 72 reports published in professional local and overseas magazines, are collated. The principles of hyperspectral imaging, Raman imaging, and mass spectrometry imaging are introduced, along with the detailed applications of these methods in the quality detection, source identification, and microbial pollution of food. In addition, it also includes food physical damage, food adulteration and food chemical residues. Besides, the advantages and disadvantages of these imaging technologies are discussed. Finally, prospects for the development of imaging technologies in food research are presented. Future work related to hyperspectral imaging should focus on the development of high-sensitivity cameras and high-resolution systems. Improving the data processing efficiency and adding prediction models are also key points for the future. Future studies on Raman imaging can focus on the application of different chemometrics algorithms that would improve the evaluation of food quality and safety parameters. Expanding the scope of application of these methods in food research will also be the focus of future research. Regarding mass spectrometry imaging, attempts should be made to improve the ionization methods, detection sensitivity, spatial resolution, and data processing effectiveness. Additionally, the combination of spectral imaging and mass spectrometry imaging gives full play to their advantages, so that spectral and mass spectrometry information of the targets can be obtained. In short, the application of imaging technologies in food research is expected to be more promising.

Objective: To examine the effects of continuous and intermittent exercises on obesity and fatty liver in rats fed with high-fat diet., Methods: Wistar rats were randomly assigned into routine diet (R) and high-fat diet (H) groups, and each group were subdivided into sedentary group (S), continuous exercise (CE) group, and intermittent exercise (IE) group (n=8). In the CE group, the rats were forced to swim continuously for 90 min once daily, and those in the IE group swam for 30 min for 3 times (at a 4-h interval) daily. Both the CE and IE groups exercised for 5 days a week for 8 consecutive weeks. After the experiment, the retroperitoneal, epididymal, and visceral white and brown adipose tissues, the liver, and the gastrocnemius muscle of the rats were weighed. The lipogenesis rate was determined by incorporation of (3)H(2)0 into saponified lipids, and the blood lipid profiles were analyzed. The body weight and food intake of the rats were recorded daily., Results: IE appeared to be more efficient than CE in reducing the adverse effects of high-fat diet and sedentarism. Compared with CE, IE resulted in an improved lipid profile with reduced food intake, body weight gain, visceral and central adiposity, and fatty liver. The effect of high-fat diet and different exercises on weight gain, adiposity, fatty liver, and lipid profile in rats was associated to the manner of exercise, time of each session, age, gender, and length of observation period., Conclusion: Intermittent exercise is an important nonpharmacological strategy to control obesity and the related complications.

A new analytical method using ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was developed for screening and confirmation of 10 unapproved sedative drugs in feeds. The samples were extracted using the solution of methanol-0.1 mol/L HCl (9:1, v/v), and the extracts were centrifuged and then directly purified through MCX cartridges. The identification and detection were achieved in positive electrospray ionization (ESI) mode using Q-TOF-MS. The potential of UPLC-Q-TOF MS for confirmatory analysis was shown by determining the accurate mass of all the compounds and fragment ions upon collision-induced-dissociation (CID) at different energies. The extra mass measurement errors for all the sedative drugs were found to be within 5 ppm. The calibration graphs were linear in the concentration range of 5-100 microg/L with the correlation coefficients more than 0.99 for the 10 drugs. The limits of quantification (LOQ, S/N = 10) were 8 microg/kg for nitrazepam, zolpidem and thioridazine; 10 microg/kg for thriazolam, estazolam, diazepam, promethazine, chlorpromazine and midazolam; 20 microg/kg for clozapine. The recoveries for all the compounds in feeds were 60.6%-108.5% with the relative standard deviations less than 10% at the spiked levels of LOQ, 2LOQ and 4LOQ.

A screening method for 29 forbidden or limited synthetic pigments in cheese samples was established by liquid chromatography/quadrupole time-of-flight mass spectrometry (LC/Q-TOF MS). The pigments were extracted by n-hexane/water (3:1, v/v). After extraction, the n-hexane extract, water extract and residue, were obtained. The n-hexane extract was then cleaned-up by gel permeation chromatography (GPC). The water extract was extracted by acetonitrile, and the residue by ammonia water/methanol (1:99, v/v). The results showed that the 29 synthetic pigments with a wide range of polarities were extracted effectively with the recoveries between 70% and 95%, and matched well by Q-TOF MS precision mass searching to the mass spectral library with matching scores between 59. 66 and 99. 47. The quantitative analysis of the 29 pigments was carried out by Target MS/MS. The limits of detection (LODs) for 8 Sudan dyes were 0.4-2.5 micro/kg while for 21 water-soluble synthetic pigments were 20-80 microg/kg. The screening method is suitable for a wide range of synthetic pigments, and can be applied to food samples with proteins and fat in matrix.