Machine Vision System for Determining Citrus Count and Size on a Canopy Shake and Catch Harvester
A machine vision-based citrus fruit counting system was developed for a continuous canopy shake and catch harvester. The system consisted of a 3CCD camera, four halogen lamps, an encoder, and a laptop computer. A total of 719 images were taken during an experiment on a test bench at the Citrus Research and Education Center (Lake Alfred, Fla.) and were used for analysis. The system was also tested on a canopy shake and catch harvester at a grove located in Fort Basinger, Florida, where a total of 773 images were acquired and 60 images were used for validation. Fruit weight was measured during image acquisition in 14 test bench experiments and in two field tests with a commercial canopy shake and catch harvester. An image processing algorithm that could identify fruit and measure its size was developed using a Bayesian classifier, morphological operations, and watershed segmentation. From the sets of color images, the number of fruit and total fruit areas were measured using the developed algorithm. Finally, the number of citrus fruits that were identified by the image processing algorithm during the test bench experiment was compared against actual fruit weight. The coefficient of determination (R2) between them was 0.962. To validate the canopy shake and catch harvester experiment, the number of fruit was counted manually from a total of 60 images. Density clustering was used to enhance the result of the Bayesian classifier. The manual count was compared with the image processing algorithm count. The R2 value was 0.891 between the actual and estimated number of fruit.
Wagon-Based Silage Yield Mapping System
A silage yield mapping system was developed using a DGPS receiver, load cells, a header
switch, Bluetooth modules for wireless data transmission, and a moisture sensor. A total of 13
loads of silage crops were harvested during tests in commercial silage fields. The masses of the
empty and full silage wagon were measured with a platform scale before and after harvesting,
and were compared with load cell measurements in the silage yield mapping system. The system
yielded errors less than 5.0% of the total harvested crop, compared with measurements by a
platform scale. A Bluetooth module (wireless transmission) was successfully implemented to
transfer moisture sensor information to a host computer. A silage yield map was created for a
site-specific crop management.
Ertragskartierung mit Feldhäckslern
Die Kenntnis der ortsdifferenzierten Ertragsfahigkeit fur die wichtigsten Anbaukulturen innerhalb eines Schlages ist eine notwendige Voraussetzung fur die teilflachenspezifische Pflanzenproduktion. Da mit Feldhackslern bedeutende Anteile der Produktionsflachen abgeerntet werden, erscheint ihre Ausstattung mit einer Technik zum Erstellen von Ertragskarten sinnvoll. Durch Messen des Spaltes zwischen Presswalze und Glattwalze vor der Schneidtrommel kann ein dem momentanen Gutdurchsatz entsprechender Messwert gewonnen werden. Erste Kartierungsergebnisse werden diskutiert.