In response to the current key issues in field of smart irrigation for farmland, such as lack data sources and insufficient integration, a low degree automation drive execution control, over-reliance on cloud platforms analyzing calculating decision making processes, we have developed nodes gateways irrigation. These developments are based EC-IOT edge computing IoT architecture long range radio (LoRa) communication technology, utilizing STM32 MCU, WH-101-L low-power LoRa modules, 4G...

To meet the demand of intelligent irrigation for accurate moisture sensing in soil vertical profile, a profile sensor was designed based on principle high-frequency capacitance. The consists five groups probes, data processor, and some accessory components. Low-resistivity copper rings were used as components probes. Composable simulation sensor’s probes carried out using structure simulator. According to effective radiation range electric field intensity, width spacing ring set 30 mm...

Real-time monitoring of nitrogen status in rice and wheat plant is significant importance for diagnosis, fertilization recommendation, productivity prediction. With 11 field experiments involving different cultivars, rates, water regimes, time-course measurements were taken canopy hyperspectral reflectance between 350-2 500 nm leaf accumulation (LNA) wheat. A new spectral analysis method through the consideration characteristics components growth varied with phenological stages was designed...

Accurate forecasting of N required for plant growth can help optimize grain yields, farm profits, and use efficiency reduce the risk environmental pollution. The objectives this study were to: (i) establish a critical ( c ) dilution curve winter wheat Triticum aestivum L.) based on leaf area index (LAI), (ii) compare with curves that are dry matter, (iii) assess plausibility using new to estimate status wheat. Four field experiments conducted different application rates. Twenty plants from...

In view of the demand for a low-cost, high-throughput method continuous acquisition crop growth information, this study describes crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as operating platform. The is capable real-time online various major indexes, e.g., normalized difference vegetation index (NDVI) canopy, ratio (RVI), leaf nitrogen accumulation (LNA), area (LAI), and dry weight (LDW). By carrying out three-dimensional numerical simulations based on...

Single-modal images carry limited information for features representation, and RGB fail to detect grass weeds in wheat fields because of their similarity shape. We propose a framework based on multi-modal fusion accurate detection natural environment, overcoming the limitation single modality detection. Firstly, we recode single-channel depth image into new three-channel like structure image, which is suitable feature extraction convolutional neural network (CNN). Secondly, multi-scale...

Various sensors have been used to obtain the canopy spectral reflectance for monitoring above-ground plant nitrogen (N) uptake in winter wheat. Comparison and intercalibration of vegetation indices derived from different are important multi-sensor data fusion utilization. In this study, its three ground-based (ASD Field Spec Pro spectrometer, CropScan MSR 16 GreenSeeker RT 100) six wheat field experiments were compared. Then, best sensor (ASD) normalized difference index (NDVI (807, 736))...

Wireless channel propagation characteristics and models are important to ensure the communication quality of wireless sensor networks in agriculture. attenuation experiments were carried out at different node antenna heights (0.8 m, 1.2 1.6 2.0 m) tillering, jointing, grain filling stages rice fields. We studied path loss variation trends transmission distances analyzed differences between estimated values measured a free space model two-ray model. Regression analysis was used establish...

Due to the low recognition rate of weeds in wheat fields and inability accurately locate weeds, we propose a method for natural based on fusion RGB image features depth features. The breaks through limitations two-dimensional spatial extracted from images when recognizing grass similar wheat. According species, distribution fields, color, position, texture, during tillering jointing stages. And then used AdaBoost algorithm integrated learning multiple classifiers, thereby achieving fields....

Canopy spectral reflectance can indicate both crop nutrient and canopy structural information. Differences in structure affect reflectance. However, a non-imaging spectrometer cannot distinguish such differences while monitoring nutrients, because the results are likely to be influenced by structure. In addition, nitrogen application rate is one of main factors influencing crops. Strong correlations exist between indices leaf nitrogen, thus, these used compensate for content wheat leaves....

To non-destructively acquire leaf nitrogen content (LNC), accumulation (LNA), area index (LAI), and dry weight (LDW) data at high speed low cost, a portable apparatus for crop-growth monitoring diagnosis (CGMD) was developed according to the spectral mechanisms of crop growth. According canopy characteristics crops actual requirements field operation environments, splitting light beams by using an optical filter proper structural parameters were determined sensors. Meanwhile, integral-type...

Unmanned aerial vehicles (UAVs) equipped with dual-band crop-growth sensors can achieve high-throughput acquisition of information. However, the downwash airflow field UAV disturbs crop canopy during sensor measurements. To resolve this issue, we used computational fluid dynamics (CFD), numerical simulation, and three-dimensional testers to study UAV-borne multispectral-sensor method for monitoring growth. The results show that when flying height is 1 m from canopy, generated on surface...

The accurate estimation of nitrogen accumulation is great significance to fertilizer management in wheat production. To overcome the shortcomings spectral technology, which ignores anisotropy canopy structure when predicting wheat, resulting low accuracy and unstable prediction results, we propose a method for based on fusion features. After depth images are repaired using hole-filling algorithm, RGB fused through IHS transformation, textural features then extracted order express...

High-throughput phenotype monitoring systems for field crops can not only accelerate the breeding process but also provide important data support precision agricultural monitoring. Traditional methods relying on artificial sampling and measurement have some disadvantages including low efficiency, strong subjectivity, single characteristics. To solve these problems, rapid monitoring, acquisition, analysis of phenotyping information become focus current research. The research explores...

Plant nitrogen (N) uptake is a good indicator of crop N status. In this study, new method was designed to determine the central wavelength, optimal bandwidth and vegetation indices for predicting plant (g m−2) in winter wheat (Triticum aestivum L.). The data were collected from ground-based hyperspectral reflectance measurements eight field experiments on different years, eco-sites, varieties, rates, sowing dates, densities. index (PNUI) based NDVI 807 nm combined with 736 selected as index,...

The high-flux acquisition of crop growth information can be realized using field monitoring robotic platforms. However, most the existing agricultural robots have been converted from expensive commercial platforms, and they thus a hard time adapting to farmland working environment, let alone satisfying basic requirements sensor testing. To address these problems, wheeled crop-growth-monitoring robot that features accurate, nondestructive, efficient was developed based on cultivation...