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.
Remotely-Piloted Helicopter Citrus Yield Map Estimation
A remotely-piloted Gas Xcell mini-helicopter with GPS, wireless Ethernet, and a machinevision system was flown over orange trees to take overhead images. The individual tree images were processed to estimate the number of orange pixels in the images. The fruit yield of individualtrees at harvest a month later had an r-squared value of 0.373 with the number of orange pixels onthe irrigated tree images. While it was demonstrated that a remotely-piloted mini-helicopter could beused to acquire useful overhead images of citrus trees, substantial further research is needed toimprove the accuracy of estimates of individual tree yields or health.
On the fractionation of β-lactoglobulin and α-lactalbumin
Abstract Existing methods for the preparation of α-lactalbumin and β-lactoglobulin are examined critically. It is proposed that the most satisfactory method for the preparation of the whey protein fraction from bovine milk is (NH 4 ) 2 SO 4 fractionation. A number of new gentle procedures for the fractionation of the whey proteins are compared with some existing methods. The distribution of total protein at various stages is determined by total Kjeldahl nitrogen and the kind of protein by starch-gel electrophoresis. The effect of variables, such as pH, salt concentration and temperature on the separation of α-lactalbumin and serum albumin from β-lactoglobulin is studied. Differences in the behavior ( e.g. solubility) of genetic variants of β-lactoglobulin are noted. The solubility of each of the major whey proteins, under similar conditions to those used in the fractionation, is compared with its solubility in the whey protein mixture. The understanding gained of factors important in the fractionation is used in recommending new procedures for α-lactalbumin and β-lactoglobulin isolation.