In Field Fruit Sizing Using A Smart Phone Application

Abstract

In field (on tree) fruit sizing has value in assessing crop health and for yield estimation. As the mobile phone is a sensor and communication rich device carried by almost all farm staff, an Android application (“FruitSize”) was developed for measurement of fruit size in field using the phone camera, with a typical assessment rate of 240 fruit per hour achieved. The application was based on imaging of fruit against a backboard with a scale using a mobile phone, with operational limits set on camera to object plane angle and camera to object distance. Image processing and object segmentation techniques available in the OpenCV library were used to segment the fruit from background in images to obtain fruit sizes. Phone camera parameters were accessed to allow calculation of fruit size, with camera to fruit perimeter distance obtained from fruit allometric relationships between fruit thickness and width. Phone geolocation data was also accessed, allowing for mapping fruits of data. Under controlled lighting, RMSEs of 3.4, 3.8, 2.4, and 2.0 mm were achieved in estimation of avocado, mandarin, navel orange, and apple fruit diameter, respectively. For mango fruit, RMSEs of 5.3 and 3.7 mm were achieved on length and width, benchmarked to manual caliper measurements, under controlled lighting, and RMSEs of 5.5 and 4.6 mm were obtained in-field under ambient lighting.

Attempting to Estimate the Unseen—Correction for Occluded Fruit in Tree Fruit Load Estimation by Machine Vision with Deep Learning

“…The mango fruit shape can be approximated using an ellipse [18][19][20]. The use of ellipse fitting technique has been used to discriminate fully exposed mango fruit from partly occluded fruit in canopy images for fruit size estimation [21,22]. A similar approach was implemented in the current study.…”

A Survey on Mobile Applications for Smart Agriculture

“…LandPKS [33] Land management Soil assessment 2-tier Android SOCiT [2] Land management Soil assessment 2-tier Android SIFSS [2] Land management Soil assessment 2-tier Android GeoFoto [50] Land management Land parcel identification 2-tier Android MapIT [28] Farm management Equipment tracking 2-tier Android SafeDriving [42] Farm management Equipment tracking 1-tier iOS FarmManager [41] Farm management Capturing farm data 2-tier Android SmartHof [18] Animal welfare Monitoring animal health Edge computing Android SmartFarm [16] Animal welfare Monitoring animal health Edge computing Android Agri-IoT [38] Animal welfare Livestock fertility management 2-tier -BioLeaf [46] Crop health Leaf health monitoring 1-tier Android Plant Disease [67,68] Crop health Plant disease diagnosis 1-tier iOS, Android, Windows Canopeo [64] Crop health Estimating canopy development 2-tier iOS, Android vitisFlower [4] Crop health Flower assessment 1-tier Android vitisBerry [3] Crop health Berry assessment 1-tier Android FruitSize [80] Crop health Fruit size assessment 2-tier Android PulAm [66] Crop health Crop pest monitoring 2-tier Android UbiQON [82] Greenhouse monitoring Oyster mushroom monitoring 2-tier Android Blynk [75] Storage monitoring Paddy rice monitoring 2-tier iOS, Android iDee [2] River monitoring Water assessment 2-tier Android ConnectedFarm [74] Environment monitoring Remote monitoring and control 2-tier Android SmartFarmKit [54] Environment monitoring Oyster mushroom and maize monitoring 2-tier -Nitrogen Index [24] Environment monitoring Nitrogen monitoring 1-tier Android Meaningful information can be derived when the input data are compared to the application data. One such application that performs such comparison is EVAPO [49].…”

Smartphone Application-Enabled Apple Fruit Surface Temperature Monitoring Tool for In-Field and Real-Time Sunburn Susceptibility Prediction

“…Recently, researchers have taken advantage of the increased computing potential, accessibility, ease-of-operation and low cost of smartphones for developing pertinent use cases in medical diagnosis, environmental monitoring and food safety [13]. Related to agriculture applications, Wang et al [14] utilized the smartphone built-in camera and developed an application for in-field fruit size estimation. Das et al [15] has developed a prototype for a smartphone-based spectrometer for rapid and non-destructive fruit ripeness testing.…”