China Institute of Water Resources and Hydropower Research

Zhigong Peng

Zheng Wei

Baozhong Zhang

He Chen

Jiabing Cai

Qian Zhang

Lu Liu

Yinong Li

Yaqi Wang

Xin Han

Lijuan Du

Shaozhe Lin

Songjun Han

Nana Han

Congying Han

Taisheng Du

A farmland reference crop evapotranspiration prediction method based on uncertainty of meteorological factors, includes: S. acquiring a set number of groups of weather forecast data of a prediction region within a preset time period; S. inputting each group of weather forecast data into a Bayesian probability forecast system to obtain corrected weather forecast data; and S. inputting each group of the corrected weather forecast data into a trained RBF neural network, and predicting to obtain a farmland reference crop evapotranspiration. In the present invention, the Bayesian probability forecast system is configured to correct the weather forecast data and eliminate uncertainty of weather forecast data to obtain the accurate reference crop evapotranspiration forecasted by the RBF neural network using these data.

Farmland reference crop evapotranspiration prediction method considering uncertainty of meteorological factors

An Internet-of-Things-based crop growth monitoring device includes a plurality of monitoring mechanisms. Each monitoring mechanism includes a base and a support rod fixed on the base. The support rod is provided with an electric element installation casing formed by snap-fitting an upper conical cover and a lower conical cover. A component for driving a swing cantilever to rotate is provided on the support rod at a position near a lowermost surface of the upper conical cover. A plurality of distance measuring laser sensors are provided on the swing cantilever. A component for driving an ultra-high-definition camera to rotate is provided on the support rod at the section of the upper conical cover. The images captured by the ultra-high-definition camera is used to obtain the leaf growth situation of the crops, and the data collected by the distance measuring laser sensors is used to determine the plant height of the crops.

Internet-of-things based crop growth monitoring device and method thereof

According to an irrigation method based on water usage characteristics and real-time weather condition during different crop growth stages, whether the crops are in a shortage of water in the growth is determined based on an actual soil water content, a water usage amount of the crops during the given growth stage, and a rainfall amount during the next day. If the shortage of water occurs, the actual water usage amount of the crops is calculated, and a water pump can be self-adaptively turned on to water the crops and an administrator is informed when the reservoir has an insufficient water storage, according to the relation between the water storage amount of the reservoir and the actual water usage amount.

Irrigation method and device based on water usage characteristics and real-time weather condition during different crop growth stages

A method for establishing a monitoring model of a water content of a winter wheat canopy based on spectral parameters, includes the following steps: measuring a spectral reflectance and a water content of the winter wheat canopy; constructing the spectral parameters through the spectral reflectance; wherein, the spectral parameters comprise spectral transformation forms and 'trilateral' parameters; performing correlation analysis on the water content of the winter wheat canopy and the spectral transformation forms and the trilateral parameters, selecting comprehensive spectral parameters with a significant correlation for each growth stage, performing principal component analysis on the comprehensive spectral parameters, separately constructing a water content monitoring model for each growth stage, and combining the water content monitoring model for each growth stage into the monitoring model of the water content of the winter wheat canopy for the whole growth stage.

Method for establishing content monitoring model of canopy water of winter wheat based on spectral parameters

Growing community of inventors

Beijing, China

Zhigong Peng