Computer and Computing Technologies in Agriculture VI: 6th by Yuechan Shi, Guijun Yang, Haikuan Feng (auth.), Daoliang Li,

By Yuechan Shi, Guijun Yang, Haikuan Feng (auth.), Daoliang Li, Yingyi Chen (eds.)

The two-volume set IFIP AICT 392 and 393 constitutes the refereed post-conference court cases of the sixth IFIP TC five, SIG 5.1 overseas convention on desktop and Computing applied sciences in Agriculture, CCTA 2012, held in Zhangjiajie, China, in October 2012. The 108 revised papers awarded have been conscientiously chosen from various submissions. They conceal quite a lot of attention-grabbing theories and purposes of knowledge know-how in agriculture, together with net of items and cloud computing; simulation types and decision-support structures for agricultural construction; shrewdpermanent sensor, tracking, and keep watch over expertise; traceability and e-commerce expertise; laptop imaginative and prescient, special effects, and digital truth; the appliance of knowledge and communique expertise in agriculture; and common details provider expertise and repair platforms improvement in rural components. The fifty five papers incorporated within the moment quantity specialize in GIS, GPS, RS, and Precision Farming.

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Extra info for Computer and Computing Technologies in Agriculture VI: 6th IFIP WG 5.14 International Conference, CCTA 2012, Zhangjiajie, China, October 19-21, 2012, Revised Selected Papers, Part II

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344 in pre-planting in soils) at Suoshi village in Nanjing from July to October of 2009 (autumn crop) and from March to June of 2010 (spring crop). The experiments were a split plot design with three whole-plot treatments arranged in a randomized complete block design with three blocks and three sub-plot treatments. 6m2). FN was the normal nitrogen level: compound fertilizer (N:P:K=16%:16%:17%) 750 kg·hm-2. 88 plants/m2, the pruning method of continuous decapitation was adopted in the experiments of spring crop and autumn crop, and 3 4 and 2 3 clusters were left in spring crop and autumn crop, respectively.

At last the accuracy of the developed model was evaluated by in-situ sample data. Results showed that the waterlogged paddy scattered everywhere in the study, mainly around the Huaihe River system. The spatial distribution pattern was in conformity with the occurrence tendency of paddy waterlogging provided by local agricultural department as a whole. 737. According the t-test of independent samples, the p-value reached the extremely significant level. Results showed that paddy waterlogging reduced the local yield considerably.

Compared with the former, the latter is that a large amount of column values fast assign the variable value of Matlab. 1 Plane Scatter Plots In order to show each sampling point location, need to draw a plane scatter plot of the sampling points. Draw blue scatter diagram, Matlab command sentences are as follows. 3. Fig. 3. 2 Data Interpolation Sampling points is an irregular distribution practically in farmland. In order to generate isoline and isosurface with Matlab, we should conduct data interpolation and gridding.

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