scholarly journals Integration and Development of On-Site Grain Yield Monitoring System Based on IPC

Author(s):  
Xiang Guo ◽  
Lihua Zheng ◽  
Xiaofei An ◽  
Jia Wu ◽  
Minzan Li
2021 ◽  
Author(s):  
Swati V. Shinde ◽  
Rajveer Shastri ◽  
Atul Kumar Dwivedi ◽  
Anandakumar Haldorai ◽  
Varsha Sahni ◽  
...  

Abstract In recent years, the diverse application in various disciplines and the versatility has gained a huge interest for the researchers to research on the multi-sensor data fusion technology. The remote sensing process involves the measurement and recording of the data from a scene. Thus, the remote sensing systems are known to be a powerful tool as they help in the earth's atmosphere and surface monitor at different scales. The remote sensing of the data faces a serious challenge as the data captured by the multiple sensors are heterogeneous. This affects the efficient processing and the effectiveness of the data that is being sensed. Thus, the increase in the diversity in data increases the ancillary datasets. These multimodal datasets are used jointly to improve the processing performance as per the application requirement. Initially, the fusion of the temporal data with the backscattered/temporal data is possible from the data retrieved from remote sensing. Many researchers made several types of research on fusing the multi-temporal and multimodal data and gave different ideas for a different type of researchers. This paper presents the cross-validation technique for monitoring the yield. This monitoring system is developed by fusing the multi-sensor data and the temporal images. This fusion is performed, and the performance of the yield monitoring system is analyzed from the results obtained. By using the cross-validation technique, the efficiency of the system is found to be improved.


Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 897
Author(s):  
Chaiyan Sirikun ◽  
Grianggai Samseemoung ◽  
Peeyush Soni ◽  
Jaturong Langkapin ◽  
Jakkree Srinonchat

Rice grain yield was estimated from a locally made Thai combine harvester using a specially developed sensing and monitoring system. The yield monitoring and sensing system, mounted on the rice combine harvester, collected and logged grain mass flow rate and moisture content, as well as pertinent information related to field, position and navigation. The developed system comprised a yield meter, GNSS receiver and a computer installed with customized software, which, when assembled on a local rice combine, mapped real-time rice yield along with grain moisture content. The performance of the developed system was evaluated at three neighboring (identically managed) rice fields. ArcGIS® software was used to create grain yield map with geographical information of the fields. The average grain yield values recorded were 3.63, 3.84 and 3.60 t ha−1, and grain moisture contents (w.b.) were 22.42%, 23.50% and 24.71% from the three fields, respectively. Overall average grain yield was 3.84 t ha−1 (CV = 63.68%) with 578.10 and 7761.58 kg ha−1 as the minimum and maximum values, respectively. The coefficients of variation in grain yield of the three fields were 57.44%, 63.68% and 60.41%, respectively. The system performance was evaluated at four different cutter bar heights (0.18, 0.25, 0.35 and 0.40 m) during the test. As expected, the tallest cutter bar height (0.40 m) offered the least error of 12.50% in yield estimation. The results confirmed that the developed grain yield sensor could be successfully used with the local rice combine harvester; hence, offers and ‘up-gradation’ potential in Thai agricultural mechanization.


2011 ◽  
Vol 54 (5) ◽  
pp. 1555-1567 ◽  
Author(s):  
U. A. Rosa ◽  
T. S. Rosenstock ◽  
H. Choi ◽  
D. Pursell ◽  
C. J. Gliever ◽  
...  

2001 ◽  
Author(s):  
Caryn E. Benjamin ◽  
Dr. Michael P. Mailander ◽  
Dr. Randy R. Price

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