A method for measuring banana pseudo-stem phenotypic parameters based on handheld mobile LiDAR and IMU fusion.

Diameter and height are crucial morphological parameters of banana pseudo-stems, serving as indicators of the plant's growth status. Currently, in densely cultivated banana plantations, there is a lack of applicable research methods for the scalable measurement of phenotypic parameters such as diameter and height of banana pseudo-stems. This paper introduces a handheld mobile LiDAR and Inertial Measurement Unit (IMU)-fused laser scanning system designed for measuring phenotypic parameters of banana pseudo-stems within banana orchards. To address the challenges posed by dense canopy cover in banana orchards, a distance-weighted feature extraction method is proposed. This method, coupled with Lidar-IMU integration, constructs a three-dimensional point cloud map of the banana plantation area. To overcome difficulties in segmenting individual banana plants in complex environments, a combined segmentation approach is proposed, involving Euclidean clustering, Kmeans clustering, and threshold segmentation. A sliding window recognition method is presented to determine the connection points between pseudo-stems and leaves, mitigating issues caused by crown closure and heavy leaf overlap. Experimental results in banana orchards demonstrate that, compared with manual measurements, the mean absolute errors and relative errors for banana pseudo-stem diameter and height are 0.2127 cm (4.06%) and 3.52 cm (1.91%), respectively. These findings indicate that the proposed method is suitable for scalable measurements of banana pseudo-stem diameter and height in complex, obscured environments, providing a rapid and accurate inter-orchard measurement approach for banana plantation managers.

A double methylene blue labeled single-stranded DNA and hairpin DNA coupling biosensor for the detection of Fusarium oxysporum f. sp. cubense race 4.

The DCL gene in Fusarium oxysporum f. sp. cubense Race 4 (Foc4) is a pivotal pathogenic factor causing banana fusarium wilt. Precise DCL detection is crucial for Foc4 containment. Here, we present a novel ssDNA-hDNA coupling electrochemical biosensor for highly specific DCL detection. The sensing interface was formed via electrodeposition of a composite containing reduced graphene oxide (rGO) and gold nanoparticles (AuNPs) onto a carbon screen-printed electrode (SPE), followed by thiol-modified ssDNA functionalization. Additionally, the incorporation of hDNA, with methylene blue (MB) at both ends, binds to ssDNA through base complementarity, forming an ssDNA-hDNA coupling probe with bismethylene blue. This sensing strategy relies on DCL recognition by the hDNA probe, leading to DNA hairpin unfolding and detachment of hDNA bearing two MBs from ssDNA, generating a robust "on-off" signal. Empirical results demonstrate the sensor's amplified electrical signals, reduced background currents, and an extended detection range (6.02 × 106-3.01 × 1010 copies/µL) with a limit of detection (3.01 × 106 copies/µL) for DCL identification. We applied this sensor to analyze soil, banana leaves, and fruit samples, confirming its high specificity and stability. Moreover, post-sample detection, the sensor exhibits reusability, offering a cost-effective and rapid approach for banana wilt detection.

Performance matching of common pesticides in banana plantations on the surface of banana leaves at different growth stages.

BACKGROUND: The effective deposition of pesticide droplets on a target leaf surface is critical for decreasing pesticide application rates. The wettability between the target leaf surface and the pesticide spray liquid should be investigated in depth, with the aim of enhancing the adhesion of pesticide solutions. The wetting and deposition behavior of pesticides on target leaves depends on the properties of the liquid and the physical and chemical properties of the leaves. The physical and chemical properties of leaves vary with growth stage. This study aims to investigate the wetting behavior of banana leaf surfaces at different stages. RESULTS: The microstructures and chemical compositions of banana leaf surfaces at different stages were studied using modern methods. The surface structure of banana leaves exhibited a wide variety of characteristics at different growth stages, and the chemical composition changed marginally. The surface free energy (SFE) and polar and non-polar components of banana leaves at different growth stages were measured by examining the contact angles (CA) of different test solutions on the surface of banana leaves. Previous research has suggested that changes in the CA and SFE correlate with changes in leaf surface wettability. In general, the new upper leaves of banana trees are composed of polar components and exhibit hydrophobicity. Non-polar components become dominant as the leaf grows. The back surface of banana leaves was non-polar at all growth stages, with a trend that was opposite to that of the front surface. The critical surface tension of the banana leaf surface at different growth stages ranged from 7.83 to 24.22 mN m-1 , thus falling into the category of a low-energy surface. CONCLUSION: The surface roughness and chemical characteristics of banana leaves affected the wettability of the leaf surface. Differences in the free energy and the polar and non-polar components of the leaf surface at were seen at different growth stages. This study provides a favorable reference for the rational control of pesticide spraying parameters and the enhancement of wetting and adhesion of the solution on banana leaf surfaces. © 2023 Society of Chemical Industry.

Wetting and deposition characteristics of air-assisted spray droplet on large broad-leaved crop canopy.

Precision and efficient pesticide spraying is an important part of precision agriculture, banana is a large broad-leaved plant, with pests and diseases, has a high demand for spraying and pest control. The purpose of this study was to clarify the wettability of different pesticides on the banana leaf surface, and the effects of nozzle type and working parameters on the deposition distribution performance under air-assisted spray conditions. The wettability test results of different pesticides on banana leaf surfaces showed that the wettability of the adaxial side was always stronger than that of the abaxial side, the smaller the surface tension of the droplets, the better the wettability on the surface. The spray experiment was carried out on the previously developed air-assisted sprayer with the latest developed intelligent variable spray control system. Three types of nozzles were used to spray with different combinations of working parameters. The deposition distribution performance on the banana leaf surface was obtained by image processing using a self-compiled program. The experimental results show that the nozzle type, wind speed, and spray pressure have significant effects on the deposition distribution performance. Through the study of the interaction and coupling effect of nozzle type and working parameters on the spray droplet deposition distribution on both sides of banana leaves, the results show that under the conditions of hollow cone nozzle, 0.5Mpa spray pressure and 3-5 m/s wind speed, the spray coverage and droplet density are in the optimal state. This is mainly due to the low spray pressure and/or wind speed is not enough to make the banana leaves vibrate and improve the performance of pesticide deposition. excessive spray pressure and/or wind speed will cause large deformation of banana leaves and make them airfoil stable, which reduces the surface deposition performance. It is of great significance for promoting sustainable and intelligent phytoprotection.

Study on the nonfatigue and fatigue states of orchard workers based on electrocardiogram signal analysis.

In recent years, fatigue has become an important issue in modern life that cannot be ignored, especially in some special occupations. Agricultural workers are high-risk occupations that, under fatigue conditions over a long period, will cause health problems. In China, since very few studies have focused on the fatigue state of agricultural workers, we were interested in using electrocardiogram (ECG) signals to analyze the fatigue state of agricultural workers. Healthy agricultural workers were randomly recruited from hilly orchards in South China. Through the field experiment, 130 groups of 5-min interval ECG signals were collected, and we analyzed the ECG signal by HRV. The time domain (meanHR, meanRR, SDNN, RMSSD, SDSD, PNN20, PNN50 and CV), frequency domain (VLF percent, LF percent, HF percent, LF norm, HF norm and LF/HF) and nonlinear parameters (SD1, SD2, SD1/SD2 and sample entropy) were calculated and Spearman correlation coefficient analysis and Mann-Whitney U tests were performed on each parameter for further analysis. For all subjects, nine parameters were slightly correlated in nonfatigue and fatigue state. Six parameters were significantly increased and ten HRV parameters were significantly decreased compared the nonfatigue state. As for males, fifteen parameters were significantly different, and for females, eighteen parameters were significantly different. In addition, the probability density functions of SDNN, SDSD, VLF%, HFnorm and LF/HF were significantly different in nonfatigue and fatigue state for different genders, and the nonlinear parameters become more discrete compared the nonfatigue state. Finally, we obtained the most suitable parameters, which reflect the fatigue characteristics of orchard workers under different genders. The results have instructional significance for identifying fatigue in orchard workers and provide a convincing and valid reference for clinical diagnosis.

Banana Leaf Surface's Janus Wettability Transition from the Wenzel State to Cassie-Baxter State and the Underlying Mechanism.

Janus wettability plays an important role in certain special occasions. In this study, field emission scanning electron microscopy (FESEM) was used to observe the surface microstructure of banana leaves, the static wettability of the banana leaf surface was tested, and the dynamic response of water droplets falling at different heights and hitting on the adaxial and abaxial sides was studied. The study found that the nanopillars on the adaxial and abaxial sides of the banana leaf were different in shape. The nanopillars on the adaxial side were cone-shaped with large gaps, showing hydrophilicity (Wenzel state), and the heads of the nanopillars on the abaxial side were smooth and spherical with small gaps, showing weak hydrophobicity (Cassie-Baxter state). Banana leaves show Janus wettability, and the banana leaf surface has high adhesion properties. During the dynamic impact test, the adaxial and abaxial sides of the banana leaves showed different dynamic responses, and the wettability of the adaxial side of the banana leaves was always stronger than the abaxial side. Based on the structural parameters of nanopillars on the surface of the banana leaf and the classical wetting theory model, an ideal geometric model around a single nanopillar on both sides of the banana leaf was established. The results show that the established model has high accuracy and can reflect the experimental results effectively. When the apparent contact angle was 76.17°, and the intrinsic contact angle was 81.17° on the adaxial side of the banana leaf, steady hydrophilicity was shown. The abaxial side was similar. The underlying mechanism of Janus wettability on the banana leaf surface was elucidated. This study provides an important reference for the preparation of Janus wettability bionic surfaces and the efficient and high-quality management of banana orchards.

Multi-Target Recognition of Bananas and Automatic Positioning for the Inflorescence Axis Cutting Point.

Multi-target recognition and positioning using robots in orchards is a challenging task in modern precision agriculture owing to the presence of complex noise disturbance, including wind disturbance, changing illumination, and branch and leaf shading. To obtain the target information for a bud-cutting robotic operation, we employed a modified deep learning algorithm for the fast and precise recognition of banana fruits, inflorescence axes, and flower buds. Thus, the cutting point on the inflorescence axis was identified using an edge detection algorithm and geometric calculation. We proposed a modified YOLOv3 model based on clustering optimization and clarified the influence of front-lighting and backlighting on the model. Image segmentation and denoising were performed to obtain the edge images of the flower buds and inflorescence axes. The spatial geometry model was constructed on this basis. The center of symmetry and centroid were calculated for the edges of the flower buds. The equation for the position of the inflorescence axis was established, and the cutting point was determined. Experimental results showed that the modified YOLOv3 model based on clustering optimization showed excellent performance with good balance between speed and precision both under front-lighting and backlighting conditions. The total pixel positioning error between the calculated and manually determined optimal cutting point in the flower bud was 4 and 5 pixels under the front-lighting and backlighting conditions, respectively. The percentage of images that met the positioning requirements was 93 and 90%, respectively. The results indicate that the new method can satisfy the real-time operating requirements for the banana bud-cutting robot.

Microscale mechanism of microstructure, micromorphology and Janus wettability of the banana leaf surface.

As a result of natural selection, the adaxial and abaxial sides of banana leaves show different wetting states and anisotropy. Janus wettability between the adaxial and abaxial sides of the banana leaf surface is revealed for the first time in this work. This has relevance for the preparation of bionic materials and an important role in the efficient and high-quality production management of pesticide spraying in banana orchards. The main purpose of this research is to analyze and study the microscale mechanism and coupling relationship between the Janus wettability of banana leaf surface and the microstructure and micromorphology. We adopt advanced modern instrument analysis technology, such as contact angle (CA) measurements, field emission scanning electron microscopy (FESEM), X-ray spectrometric analysis (EDS), and Fourier transform infrared spectroscopy (FTIR), and performed tests on the adaxial and abaxial sides of banana leaves to investigate the cause of Janus wettability. The results show that banana leaves exhibit different degrees of anisotropy, mainly due to the surface micromorphology. Banana leaves exhibit a hydrophilic Wenzel state on the adaxial side and a weakly hydrophobic Cassie-Baxter state on the abaxial side. We focused on studying the coupling effect and found that the main coupling element impacting the Janus wettability of the banana leaf surface is the nanopillars microstructure, and the secondary coupling element is the content of hydrophilic functional groups on the surface. This work may lead to the design and fabrication of Janus wetting surfaces by mimicking the nanopillar structure on banana leaf surfaces and help explore the potential application of efficient and high-quality pesticide spraying in banana orchards.

Immobilized Ag3PO4/GO on 3D nickel foam and its photocatalytic degradation of norfloxacin antibiotic under visible light.

In this study, a series of Ag3PO4/graphene oxide (GO) films were dip-coated on a metal nickel foam. The immobilized catalysts were characterized by X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, ultraviolet-visible spectroscopy, Raman spectroscopy, high-resolution transmission electron microscopy and photoluminescence spectroscopy. The results show that Ag3PO4/GO was successfully supported on a nickel foam. The photocatalytic activity of the film catalyst under visible light was investigated by the degradation of norfloxacin, an antibiotic. Photocatalytic stability of this catalyst was also investigated. An optimized film exhibited superior activity and stability, the degradation rate of norfloxacin was about 83.68% in 100 min and the reaction rate constant k was 1.9 times that of pristine Ag3PO4. Further investigation found that photo-generated holes (h+) and superoxide anion radicals (·O2 -) are the main active species in the photodegradation process. The result indicates that the addition of GO inhibits the recombination of photogenerated electron-hole pairs, and thus has improved the photocatalytic activity and cyclic stability under visible light. The photocatalytic mechanism of the film catalyst was proposed. The prepared Ag3PO4/GO film catalyst is a promising candidate for treatment of wastewater containing antibiotics.