Authors
Filter results5 paper(s) found. |
---|
1. Development Of Batch Type Yield Monitor For Small FieldsAbstract The yield monitor is intended to give the user an accurate assessment of yield variations y within a field. A yield monitor can assist grain producers in many aspects of crop management. A yield monitor by itself can provide useful information and enhance on-farm research. Yield data can... M. Singh, A. Sharma, G. Singh, P. Fixen |
2. Spectral Models for Estimation of Chlorophyll Content, Nitrogen, Moisture Stress and Growth of Wheat CropField experiments were conducted during 2009-10 and 2010-11 at research farm of the department of Farm Machinery and Power Engineering, Punjab Agricultural university, Ludhiana. Three wheat ... B.S. Sekhon, J. Mukherjee, A. Sharma, S.K. Thind, R. Kaur, M.S. Makkar |
3. Development of Ground Based Multi-source Crop Information Collection System.Precision agriculture requires reliable technology to acquire accurate information on crop conditions. A ground-based integrated sensor and instrumentation system was developed to measure real-time crop conditions. The integration system included multispectral camera and N-sensor for real time Nitrogen application. The system was interfaced with a DGPS receiver to provide spatial coordinates for sensor readings. Before mounting of the sensors on modified paddy transplanter, different mountings... A. Sharma, M.S. Makkar, S. Gupta |
4. Estimation Of Nitrogen And Chlorophyll Content In Wheat Crop Using Hand Held SensorsA Field experiment was conducted to estimate crop nitrogen (N) status and chlorophyll content in wheat crop by using chlorophyll content meter(Apogee’s CCM-200) and N-Tester® (Make YARA International). The experiment was conducted by sowing university recommended wheat variety viz. PBW 550 with 5 nitrogen levels i.e. 0, 30, 60, 90, 120 & 150 kg N/ha. It was found that at tillering stage when nitrogen rates were increased from 0 to 150 kg ha-1 , the... M.S. Makkar, A. Kaul, R. Kumar, A. Sharma, B.S. Sekhon, C.S. Pannu |
5. Identifying and Filtering Out Outliers in Spatial DatasetsOutliers present in the dataset is harmful to the information quality contained in the map and may lead to wrong interpretations, even if the number of outliers to the total data collected is small. Thus, before any analysis, it is extremely important to remove these errors. This work proposes a sequential process model capable of identifying outlier data when compared their neighbors using statistical parameters. First, limits are determined based on the median range of the values of all the... L. Maldaner, J. Molin, T. Tavares, L. Mendez, L. Corrêdo, C. Duarte |