Yangling International Academy of Modern Agriculture

Yangling, China

Yangling International Academy of Modern Agriculture

Yangling, China
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He D.,Northwest Agriculture and Forestry University | He D.,Yangling International Academy of Modern Agriculture | Yang C.,U.S. Department of Agriculture | Yang C.,Yangling International Academy of Modern Agriculture | And 8 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2012

In order to develop a real-time analyzer for soil attributes, the needs for real-time measurement of soil attributes were analyzed and major soil attributes to be measured in soil testing and commonly-used testing methods were reviewed, including traditional chemical analysis, methods based on electro-optical dispersion and electrochemical sensors, and indirect measurement of soil electrical conductivity. Emphasis was given to the review of the basic principles, laboratory studies, prototype development, and field experiments of near-infrared spectroscopic. The described methods and prototype instruments and the proposed scientific problems to be solved in this paper will be useful and provide important guidance for research and development of real-time analyzers for soil attributes.


Hu G.,Northwest University, China | Hu G.,Yangling International Academy of Modern Agriculture | Sudduth K.A.,U.S. Department of Agriculture | Myers D.B.,University of Missouri | And 3 more authors.
American Society of Agricultural and Biological Engineers Annual International Meeting 2013, ASABE 2013 | Year: 2013

Visible and near infrared (VNIR) diffuse reflectance spectroscopy has potential in site-specific measurement of soil properties. However, previous studies have reported VNIR estimates of plant available soil phosphorus (P) and potassium (K) to be of variable accuracy. In this study, we used a database of over 1500 soil samples to investigate what factors influenced P and K estimation accuracy. Specifically, the effect of classifying soil samples by major land resource areas (MLRAs), cation exchange capacity (CEC) or organic matter (OM) was investigated. Additionally, calibrations using only those samples within the approximate range of interest for fertilizer application to field crops - P from 0 to 108 mg kg-1 and K from 0 to 768 mg kg-1 - were compared to calibrations using the full range of soil samples. Pretreatments of log10(1/reflectance) plus mean normalization plus median filter smoothing with or without direct orthogonal signal correction (DOSC) were investigated. Results from partial least squares regression (PLSR), principal component regression (PCR) and support vector regression (SVR) were compared. Reasonable estimates of P and K were obtained for soil samples from two Missouri MLRAs (109 and 115B) out of the eight analyzed. Model estimates were poor when soil samples were grouped by CEC or OM; however, there was some indication that VNIR estimation of P and K might be possible for soils low in OM. Accuracy was maintained when analyzing a reduced wavelength range from 1100 to 2450 nm, suggesting this narrower sensing range might be used for on-the-go sensors. PLSR provided better accuracy than PCR or SVR for both P and K. The DOSC pretreatment significantly improved P and K estimation accuracy. The results of this research provided some insight into the factors affecting the accuracy of P and K estimation by VNIR models, but additional research is needed to determine if these findings can lead to P and K estimations sufficiently accurate to guide variable-rate fertilization.


Wang Y.,Northwest University, China | Yang F.,Northwest University, China | Yang F.,Yangling International Academy of Modern Agriculture | Zhou Y.,Northwest University, China | And 4 more authors.
International Journal on Smart Sensing and Intelligent Systems | Year: 2013

A fuzzy control system was designed to command driving directions for a mountain agriculture robot. First, a fuzzy control system program was developed based on the scheme of the robot driving control system. Then, the core part of the system--the fuzzy controller--was designed. Finally, a system model was created and a simulation test was conducted through the application of the Fuzzy Toolbox in MATLAB and SIMULINK. The results showed that the system is effective.


Wang Y.,Northwest University, China | Yang F.,Northwest University, China | Yang F.,Yangling International Academy of Modern Agriculture | Wang T.,Northwest University, China | And 2 more authors.
International Journal on Smart Sensing and Intelligent Systems | Year: 2013

To solve the problems of instability of agricultural robot when avoiding obstacles, a kind of navigation method which combined monocular visual navigation technology and remote monitoring technology was proposed: using the centerline method to extract the navigation path to achieve visual navigation; the monitoring center received two-way real-time image signals of the agricultural robot, when the agricultural robot met the obstacle or other situations, the remote monitoring center would start the alarm, then the operators could send control signals through the monitoring software to implement manual intervention. The experiment showed that the system improved the reliability of the navigation.

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