Soil organic carbon (SOC) is important in the global cycle. Accurate estimation of SOC content cultivated land a prerequisite for evaluating sequestration potential and quality soils. However, existing prediction studies based on hyperspectral remote sensing neglect spectral response physical properties surface soil, leading to inadequate model generalization. With exponential growth data, development pixel-level soil correction methods multi-source data has become an interesting challenging...

It is generally believed that stable airflow can effectively reduce tip burn, a common lettuce plant disease in closed factories severely restricts the sustainable development of these factories. This study aims to achieve cultivator by zoning seedling and growth stage crops installing differential fans, while ensuring comprehensive quality. In this study, three-dimensional simulation factory model was created simulate inside cultivator, taking crop shading heat dissipation from LED light...

Regulating plant factories is crucial for optimal growth and yield. Although LEDs (light-emitting diode) are called cold light sources, more than 80% of the heat still emitted into surrounding environment. In high-density vertical agricultural facilities, crop canopy positioned close to source maximize absorption promote growth. LED dissipation can cause disturbances in microclimate canopies, which lead tip burn disease crops result economic losses factories. CFD (computational fluid...

In order to solve the problem of accuracy and speed disease identification in real-time spraying operation maize field, an improved ResNet50 model was proposed. Firstly, this paper uses Adam algorithm optimize model, adjusts learning strategy through inclined triangle rate, increases L2 regularization reduce over fitting, adopts exit ReLU incentive function. Then, first convolution kernel is modified into three 3 x small kernels. Finally, ratio training set verification : 1. Through...

Soil organic matter (SOM) is important for the global carbon cycle, and hyperspectral remote sensing has proven a promising method fast SOM content estimation. However, soil physical properties significantly affect sensitivity of satellite imaging to SOM, leading poor generalization ability estimation model. This study aims improve spatiotemporal transferability prediction model by alleviating coupling effect on spectra. Based images variables, including moisture (SM), surface roughness...

In this study, the feasibility of classifying soybean frogeye leaf spot (FLS) is investigated. Leaf images and hyperspectral reflectance data healthy FLS diseased leaves were acquired. First, image processing was used to classify create a reference for subsequent analysis data. Then, dimensionality reduction methods obtain relevant information pertaining FLS. Three single methods, namely spectral index (SI), principal component (PCA), competitive adaptive reweighted sampling (CARS), along...

Soil nutrient content is an important index to determine the amount of fertilizer. Traditional soil obtained by manual sampling, which greatly increases cost agricultural production input. In order solve this problem, paper studies relationship between nutrients, fertilizer amount, yield and next year's establishes optimized BP neural network model realize prediction content. Aiming at problem that traditional will affect accuracy due different weights thresholds, Grey Wolf algorithm with...

The information acquisition about potassium, which affects the quality and yield of crops, is great significance for crop nutrient management intelligent decision making in smart agriculture. This article proposes a method predicting rice leaf potassium content (LKC) using spectral characteristics random forests (RF). screens characteristic variables based on linear correlation analysis results LKC four transformed spectra (original reflectance (R), first derivative (FDR), continuum-removed...

Soil organic matter (SOM) is important for the global carbon cycle, and hyperspectral remote sensing has proven to be a promising method fast SOM content estimation. However, because of neglect spectral response soil physical properties, accuracy spatiotemporal transferability prediction model are poor. This study aims improve by alleviating coupling effect properties on spectra. Based satellite images variables, including moisture (SM), surface roughness (root-mean-square height, RMSH),...

Abstract With the continuous advancement of agricultural Internet Things (IoT) technologies, real-time monitoring environments has become increasingly significant. This provides valuable information on pest and disease occurrences corresponding ecological conditions. However, as have extensive coverage, number IoT devices volume will rapidly increase. leads to a surge in network traffic computing demands. To address this issue, article proposes an environmental system that utilizes edge deep...

Although nitrogen deficiency and sucrose are linked to anthocyanin synthesis, the potential role of in regulating biosynthesis under low conditions (LN) purple lettuce (Lactuca sativa L.) remains unclear. We found that adding exogenous enhanced but significantly inhibited growth at high concentrations. Optimal results were obtained using 1 mmol/L a low-nitrogen nutrient solution (LN + T1). Chlorophyll fluorescence imaging indicated addition induced mild stress. Meanwhile, activities...

In computer vision, object detection is an important task. Whether it a single-stage or two-stage method, has been based on anchor-based detectors for several years. recent years, due to multi-scale feature fusion and Focal Loss, anchor-free have become popular. However, both the problems of large computation, poor stability, many hyperparameters, imbalance between positive negative samples. This paper proposes one-stage target network (AMBNet) that automatically matches ground truth boxes,...

Aggregate depth residual network (ResNeXt) can not only improve the accuracy without increasing parameter complexity, but also reduce number of super parameters. It is one popular convolutional neural models for image recognition. Maize diseases have a great impact on maize yield, quality and farmers’ income. Rapid effective identification severity plays an important role in accurate control drug use. The general ResNeXt model has large spots extracting features, corn are small extracted...

With the extensive use of Internet Things (IoT) in agriculture, number terminals are also grow rapidly. This will increase network traffic and computing pressure centralized server. The data processing mode used traditional agriculture cannot meet needs everything era. paper designs a gateway based on edge-computing technology for monitoring crop growth environment. It uses virtualized container to package long-range wide-area (LoRaWAN) server, pest identification, environmental information...

The activation function plays a key role in influencing the performance and training dynamics of neural networks.There are hundreds functions widely used as rectified linear units (ReLUs), but most them applied to complex large networks, which often have gradient explosion vanishing problems.By studying variety non-monotonic functions, we propose method construct function, x•Φ(x), with Φ(x)  [0, 1].With hardening treatment Φ(x), an adaptive segmented called quadratic unit, abbreviated...

The Internet of Things (IoT) technology focuses on the application information-sensing equipment, transmission network, and intelligent information processing technology. Through scientific management, it can achieve rational use agricultural resources, thus improving ecological environment, reducing production costs, yield quality products. At present, IoT faces problems including small network coverage, limited monitoring projects, high cost, short power supply time, which limit popularity...

The human population is growing at an extremely rapid rate, the demand of food supplies for survival and sustainability life a gleaming challenge.Each living being in planet gets bestowed with healthy to remain active healthy.Agriculture domain which important as it provides fundamental resources terms supplying thus economy entire world highly dependent on agricultural production.The production often affected by various environmental geographical factors are difficult avoid part...