Development of a smartphone-based peanut data logging system
- PDF / 5,904,518 Bytes
- 13 Pages / 439.37 x 666.142 pts Page_size
- 38 Downloads / 192 Views
Development of a smartphone‑based peanut data logging system Rui Li1 · Zhuo Zhao1 · W. Scott Monfort2 · Kyle Johnsen1 · Zion T. H. Tse1 · Donald J. Leo3 Accepted: 24 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The southeastern states of the USA, namely Georgia, Florida and Alabama, account for two-thirds of the total peanut production in the USA. Determining the optimal harvest day for peanuts is critical because it directly impacts their yield and grade. The conventional method is to identify the percentage of black peanuts in representative field samples using a peanut profile board. In this study, a new assistive system for peanut data logging was developed, which was able to upload user information and harvest conditions to an online database. Field tests showed the system had errors of 9.0%, 18.8% and 5.8% in estimating the percentage of black-and-brown peanuts, the percentage of black peanuts and the total peanut number when compared to results from human graders, respectively. This proof-ofconcept data logging system has the potential to provide fast and reliable results. Future work will include applying a segmentation algorithm to increase the accuracy of the system as well as creating a harvest prediction model using the online database. Keywords Peanut maturity · Optimal harvest day · Image processing · Smartphone application · Data logging
Introduction The peanut is an important crop with an annual global production of 45 Mt (National Peanut Board 2019). In the USA, the states of Georgia, Florida and Alabama account for twothirds of the country’s total peanut production (Srinivasan et al. 2017). Determining the optimum harvest maturity is of paramount importance because it directly impacts the yield and grade of the peanuts (Daigle et al. 1988; Lopez et al. 2001; Mozingo et al. 1991).
* Zion T. H. Tse [email protected] 1
School of Electrical and Computer Engineering, College of Engineering, University of Georgia, Athens, GA, USA
2
Department of Crop and Soil Sciences, College of Agricultural and Environmental Sciences, University of Georgia, Tifton, GA, USA
3
College of Engineering, University of Georgia, Athens, GA, USA
13
Vol.:(0123456789)
Precision Agriculture
One of the primary methods for determining peanut maturity is to use a peanut profile board. Williams and Drexler (1981) pioneered the method by designing a peanut maturity profile board inspired by previous studies (Pattee et al. 1977; Sanders et al. 1980). Their design was based on the close relationship between the pod mesocarp colour and pod maturity. The colour of the mesocarp could be observed by removing the outer layer (exocarp) with a knife or pressurized water (Carter et al. 2016; Williams 2003). Figure 1 shows the gradual colour change of the mesocarp layer at different maturity stages and the peanut profile board. In the method using peanut profile board, samples are initially collected from the most representative locations of peanut fields. The exocarp of each
Data Loading...
