Apple Fruit Diameter and Length Estimation by Using the Thermal and Sunshine Hours Approach and Its Application to the Digital Orchard Management Information System

Ming Li,Meixiang Chen,Bin Xing,Hui Wang,Yujing Yan,Xinting Yang,Sha Li,Wenyong Li,Chunxia Fu,Yan’An Wang,Xiaodan Fan,Yong Zhang,Jianping Qian

doi:10.1371/journal.pone.0120124

Abstract

In apple cultivation, simulation models may be used to monitor fruit size during the growth and development process to predict production levels and to optimize fruit quality. Here, Fuji apples cultivated in spindle-type systems were used as the model crop. Apple size was measured during the growing period at an interval of about 20 days after full bloom, with three weather stations being used to collect orchard temperature and solar radiation data at different sites. Furthermore, a 2-year dataset (2011 and 2012) of apple fruit size measurements were integrated according to the weather station deployment sites, in addition to the top two most important environment factors, thermal and sunshine hours, into the model. The apple fruit diameter and length were simulated using physiological development time (PDT), an indicator that combines important environment factors, such as temperature and photoperiod, as the driving variable. Compared to the model of calendar-based development time (CDT), an indicator counting the days that elapse after full bloom, we confirmed that the PDT model improved the estimation accuracy to within 0.2 cm for fruit diameter and 0.1 cm for fruit length in independent years using a similar data collection method in 2013. The PDT model was implemented to realize a web-based management information system for a digital orchard, and the digital system had been applied in Shandong Province, China since 2013. This system may be used to compute the dynamic curve of apple fruit size based on data obtained from a nearby weather station. This system may provide an important decision support for farmers using the website and short message service to optimize crop production and, hence, economic benefit.

Highlights

Apples are one of the four most popular fruits worldwide because of their high fruit quality, which is important for human health [1]
Where physiological development time (PDT) is the sum of the relative physiological development effectiveness (RPDE) each day after full bloom (DAFB) for apples
The estimation results were similar for both the PDT and calendar-based development time (CDT) models, the PDT model was more consistent than the CDT model, because the mean absolute error (MAE), mean bias error (MBE), and RMSE of the PDT model were 0.1908, -0.1514, and 0.2791, respectively, in 2013 (Table 1, Fig 4A and 4B), which was better than that obtained for the CDT model

Summary

Introduction

Apples are one of the four most popular fruits worldwide because of their high fruit quality, which is important for human health [1]. Farmers make decisions based on huge volumes of information obtained from a diverse number of devices, such as meteorological sensors, farming machinery, and short messages, to enhance production and to ensure fruit quantity and quality for maximum economic gain [2]. With the maturation of mobile technology, such as cellular phones and Personal Digital Assistants (PDAs), and the widespread adoption of the Internet, farmers are able to collect agricultural production data and obtain decision-support by wireless devices wherever and whenever they want [5]. Much work has been devoted to modeling the growth and development of fruit trees in relation to orchard management and decision-making processes [8]. Experimental data based on optimized simulations are essential to ensure that models reflect fruit development on real-life trees [11]

Methods

Results

Discussion

Conclusion