A Prototype of an Immature Citrus Fruit Yield Mapping System

2017 ◽  
Keyword(s):  
Citrus Fruit ◽  
Fruit Yield ◽  
Yield Mapping ◽  
Mapping System

Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management

2014 ◽  
Author(s):  
W.S. Lee ◽  
Victor Alchanatis ◽  
Asher Levi
Keyword(s):  
Image Registration ◽  
Navigation System ◽  
Thermal Imaging ◽  
Imaging System ◽  
Citrus Fruit ◽  
Mobile Platform ◽  
Yield Estimation ◽  
Yield Mapping ◽  
Thermal Images ◽  
Mapping System

Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved. 

Citrus Yield Mapping System in Natural Outdoor Scenes using the Watershed Transform

2006 ◽  
Author(s):  
Citrus ◽  
Fruit size ◽  
Machine vision ◽  
Watershed transform ◽  
Yield mapping
Keyword(s):  
Yield Mapping ◽  
Watershed Transform ◽  
Mapping System ◽  
Outdoor Scenes

Computer vision system for wild blueberry fruit yield mapping

2010 ◽  
Vol 106 (4) ◽  
pp. 389-394 ◽  
Author(s):  
Kishore C. Swain ◽  
Qamar U. Zaman ◽  
Arnold W. Schumann ◽  
David C. Percival ◽  
Dionysis D. Bochtis
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Fruit Yield ◽  
Computer Vision System ◽  
Yield Mapping ◽  
Wild Blueberry

Citrus Yield Mapping System on a Canopy Shake and Catch Harvester

2007 ◽  
Author(s):  
Radnaabazar Chinchuluun ◽  
Won Suk Lee ◽  
Reza Ehsani
Keyword(s):  
Yield Mapping ◽  
Mapping System

ESTIMATION OF CITRUS FRUIT YIELD USING ULTRASONICALLY-SENSED TREE SIZE

2006 ◽  
Vol 22 (1) ◽  
pp. 39-44 ◽  
Author(s):  
Q. U. Zaman ◽  
A. W. Schumann ◽  
H. K. Hostler
Keyword(s):  
Citrus Fruit ◽  
Fruit Yield ◽  
Tree Size

Citrus fruit yield response to nitrogen and potassium fertilization depends on nutrient-water management system

2019 ◽  
Vol 249 ◽  
pp. 329-333 ◽  
Author(s):  
José A. Quaggio ◽  
Thais R. Souza ◽  
Fernando C.B. Zambrosi ◽  
Dirceu Mattos ◽  
Rodrigo M. Boaretto ◽  
...  
Keyword(s):  
Water Management ◽  
Management System ◽  
Citrus Fruit ◽  
Fruit Yield ◽  
Yield Response ◽  
Water Management System ◽  
Potassium Fertilization

scholarly journals Development of a Telemetry and Yield-Mapping System of Olive Harvester

Sensors ◽  
2015 ◽  
Vol 15 (2) ◽  
pp. 4001-4018 ◽  
Author(s):  
Francisco Castillo-Ruiz ◽  
Manuel Pérez-Ruiz ◽  
Gregorio Blanco-Roldán ◽  
Jesús Gil-Ribes ◽  
Juan Agüera
Keyword(s):  
Yield Mapping ◽  
Mapping System

A yield mapping system for hand-harvested fruits based on RFID and GPS location technologies: field testing

2008 ◽  
Vol 10 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Y. G. Ampatzidis ◽  
S. G. Vougioukas ◽  
D. D. Bochtis ◽  
C. A. Tsatsarelis
Keyword(s):  
Field Testing ◽  
Yield Mapping ◽  
Mapping System

scholarly journals Yield mapping, soil fertility and tree gaps in an orange orchard

2012 ◽  
Vol 34 (4) ◽  
pp. 1256-1265 ◽  
Author(s):  
José Paulo Molin ◽  
André Freitas Colaço ◽  
Eduardo Fermino Carlos ◽  
Dirceu de Mattos Junior
Keyword(s):  
Spatial Variability ◽  
Soil Fertility ◽  
Precision Agriculture ◽  
Nutrient Management ◽  
Fruit Production ◽  
Fruit Yield ◽  
Chemical Characteristics ◽  
Yield Mapping ◽  
Orange Orchard ◽  
Representative Area

The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA) has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB) in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production.

A CITRUS HARVESTING LABOR TRACKING AND YIELD MAPPING SYSTEM

2001 ◽  
Vol 17 (2) ◽  
Author(s):  
J. D. Whitney ◽  
Q. Ling ◽  
T. A. Wheaton ◽  
W. M. Miller
Keyword(s):  
Yield Mapping ◽  
Mapping System ◽  
Citrus Harvesting
Sign in / Sign up

Export Citation Format

Share Document