Leaf blast is recognized as one of the most devastating diseases affecting rice production in world, seriously threatening yield. Therefore, early detection leaf extremely important to limit spread and propagation disease. In this study, a blast-specific spectral vegetation index RBVI = 9.78R816−R724 − 2.08(ρ736/R724) was designed qualitatively detect level disease canopy field improve accuracy by remote sensing unmanned aerial vehicle. Stacking integrated learning, AdaBoost, SVM were used...

The 3D point cloud data are used to analyze plant morphological structure. Organ segmentation of a single can be directly determine the accuracy and reliability organ-level phenotypic estimation in point-cloud study. However, it is difficult achieve high-precision, automatic, fast segmentation. Besides, few methods easily integrate global structural features local clouds relatively at reduced cost. In this paper, distance field-based pipeline (DFSP) which could code spatial structure...

High-resolution (HR) optical remote sensing images are typically small in swath and, due to cloud cover, their revisit period, mosaic error, and other problems, it is often infeasible obtain a large range of for study area. Meanwhile, low-resolution (LR) satellite suffer from insufficient spatial texture information ground objects. Therefore, classifying area with high resolution, area, no occlusion using imagery very difficult. In recent years, the rapid development super-resolution...

Leaf blast is a disease of rice leaves caused by the Pyricularia oryzae. It considered significant affecting yield and quality causing economic losses to food worldwide. Early detection leaf essential for early intervention limiting spread disease. To quickly non-destructively classify levels accurate timely control. This study used hyperspectral imaging technology obtain image data leaves. The descending dimension methods got characteristics different classes, obtained screening were as...

Abstract The radiative transfer model of vegetation leaves simulates the transmission mechanism light inside and reflectivity blades according to change law different components in process plant growth. Based on PIOSL model, this paper combines with structure rice construct a radiation for leaves. parameters each layer RPIOSL are determined by Non-dominated Sorting Genetic Algorithm-III. (NSGA-III.) algorithm. reflectance spectra 218 leaf samples periods were simulated using model. results...

Abstract BACKGROUND Rice diseases that are not detected in a timely manner may trigger large‐scale yield reduction and bring significant economic losses to farmers. AIMS In order solve the problems of insufficient rice disease detection accuracy model is lightweight, this study proposes lightweight method based on improved YOLOv8. The incorporates full‐dimensional dynamic convolution (ODConv) module enhance feature extraction capability improve robustness model, while non‐monotonic focusing...

Introduction The rapid and non-destructive estimation of rice aboveground biomass (AGB) is vital for accurate growth assessment yield prediction. However, vegetation indices (VIs) often suffer from saturation due to high canopy coverage vertical organs, limiting their accuracy across multiple stages. Therefore, this study utilizes UAV-acquired RGB multi-spectral (MS) images during several critical stages explore the potential multi-source data fusion accurately cost-effectively estimating...

To achieve rapid, accurate, and non-destructive diagnoses of nitrogen deficiency in cold land japonica rice, hyperspectral data were collected from field experiments to investigate the relationship between (N) content difference spectral reflectance establish inversion model differences N rice. In this study, was used invert rice provide a method for implementation precision fertilization without reducing yield chemical fertilizer. For purpose constructing standard principle minimum...

Chlorophyll content is an important indicator of the growth status japonica rice. The objective this paper to develop inversion model that can predict rice chlorophyll by using hyperspectral image canopy collected with unmanned aerial vehicle (UAV). UAV-based remote sensing provide timely and cost-effective monitoring over a large region. study was based on data at Shenyang Agricultural College Academician Japonica Rice Experimental Base in 2018 2019. In order extract salient information...

This article addresses a new adaptive fuzzy fast finite-time state-constraint protocol for leader-follower formation control. Each agent in uncertain nonlinear dynamic multiagent systems is represented by second-order integrator, which synchronously governs its position and velocity. The logic are employed to compensate approximate functions. On the premise of maintaining structure coupling communication topology, time-varying transformation equations containing exponential signals...

Rice is the world's most important food crop and of great importance to ensure world security. In rice cultivation process, weeds are a key factor that affects production. Weeds in field compete with for sunlight, water, nutrients, other resources, thus affecting quality yield rice. The chemical treatment fields using herbicides suffers from problem sloppy herbicide application methods. cases, farmers do not consider distribution paddy fields, but use uniform doses spraying whole field....

A precision agriculture approach that uses drones for crop protection and variable rate application has become the main method of rice weed control, but it suffers from excessive spraying issues, which can pollute soil water environments harm ecosystems. This study proposes a to generate spray prescription maps based on actual distribution weeds in fields utilize DJI plant UAVs perform automatic operations according maps, achieving precise pesticide application. We first construct YOLOv8n DT...

The nondestructive and rapid acquisition of rice field phenotyping information is very important for the precision management growth process. In this research, LAI (leaf area index), leaf chlorophyll content (Cab), canopy water (Cw), dry matter (Cdm) was inversed based on hyperspectral remote sensing technology an unmanned aerial vehicle (UAV). improved Sobol global sensitivity analysis (GSA) method used to analyze input parameters PROSAIL model in spectral band range 400-1100 nm, which...

Rice leaf blast, which is seriously affecting the yield and quality of rice around world, a fungal disease that easily develops under high temperature humidity conditions. Therefore, use accurate non-destructive diagnostic methods important for production management. Hyperspectral imaging technology type crop identification method with great potential. However, large amount redundant information mixed in hyperspectral data makes it more difficult to establish an efficient classification...

Leaf spot (LS) caused by Cercosporidium personatum is one of the most harmful peanut diseases in late growth stage and severely affects yield peanuts. Hyperspectral disease detection technology efficient, objective, accurate suitable for large-scale crop management practices. To establish a multi-scale spectral index (SI) with high accuracy stability LS disease, reflectance different severity levels at leaf, plant, field scales was collected, difference wavelength analyzed using mean,...

Abstract In this paper, we present a novel controller design method for stochastic nonlinear systems with unmodeled dynamics, uncertain parameters, and unknown covariance noise. order to deal these uncertainties, new event‐based small gain is designed. The event‐triggered scheme can reduce the computational burden caused by disturbance By combining technique of changing supply rate condition, input‐to‐state practically stability Lyapunov function obtained subsystem. Simultaneously, used...