Location: Sugarbeet and Bean Research
2011 Annual Report
Second, commercially viable infield mobile sorting technology will be developed for sorting and grading harvested apples into two or three quality grades (fresh market, processing, and cull). A cost effective machine vision system and a fruit bin filler will be designed and built; they will then be integrated into existing infield apple handling systems for effective segregation of unmarketable or defective fruit from fresh market grade fruit. Laboratory and infield tests will be performed to evaluate the mobile infield sorting prototype for performance and bruising to apples. We will collaborate with a horticultural equipment manufacturer and university extension specialists, so that the developed technology can be quickly adopted by growers to achieve production cost savings.
Third, research will be conducted on the development of a hyperspectral imaging-based spatially-resolved method for measuring the optical absorption and scattering properties of horticultural and food products. An optical property measuring prototype will be built and tested for automatic measurement of the optical properties of fruits and other food and agricultural products. Optimization of the hardware (light source, source-detector distance, etc.) and algorithms will be performed through Monte Carlo simulation and experiment to improve measurement accuracy and repeatability. Experiments and mathematical or statistical analyses will be performed to relate the optical properties to the structural/mechanical properties of apples and to the quality attributes of apples, peaches and tomatoes. Moreover, research will be conducted to improve spectral scattering technology for sorting and grading apples for firmness and soluble solids content. Improved hardware designs and new spectral scattering analysis methods integrating both spectral and image features will be considered and incorporated into the laboratory spectral scattering prototype for classification of apples into different quality grades based on firmness/soluble solids content. Finally, an online hyperspectral imaging system, which integrates reflectance in the visible spectral region and transmittance in the short-wave near-infrared region, will be developed for online sorting and grading of pickling cucumbers and/or pickled products for external and internal quality (or defect). Different lighting designs and spectral imaging acquisition modalities will be considered and evaluated. Image processing and analysis algorithms will be developed for rapid detection and segregation of defective pickling cucumbers/pickles.
An improved machine vision system that utilized a low-cost digital color camera was built and incorporated into the first version presorting prototype for sorting apples into two grades (i.e., fresh market and cull). Experiments were conducted for three varieties of apple to evaluate the performance of the machine vision system. In addition, different types of defective fruit, including scab, cuts, hail damage, insect bites, etc., were collected from two research orchards. Color images acquired for these fruit were used for developing an automatic fruit defect detection algorithm and building a fruit defects database. The machine vision system has fully met initial expectations in sorting apples for size and color. Based on the test evaluations and inputs from the apple growers, a new design for the presorting system has been proposed, and it will be ready for testing for the 2011 harvest season.
Optical absorption and scattering spectra for 500-1,000 nm were measured for ‘Golden Delicious’ and ‘Granny Smith’ apples of various firmness levels, using an inhouse developed instrument. Tissue specimens were then excised for microscopic image analysis using scanning electron microscope (SEM) and confocal laser scanning microscope (CLSM). The optical absorption and scattering properties were found to correlate with the area and diameter of fruit cells, and they were also related to the mechanical properties (i.e., elasticity) of apple tissues. Further research was conducted to measure the optical absorption and scattering properties of apples and peaches and determine their correlation with the fruit firmness and soluble solids content. Good to excellent correlations between the optical property measurements and fruit firmness and soluble solids content were obtained for both apple and peach.
Experiments were conducted during the 2010 harvest season and continued for three months after the harvest to evaluate the firmness and soluble solids content (SSC) of more than 3,400 ‘Delicious’, ‘Golden Delicious’, and ‘Jonagold’ apples, using four nondestructive instruments/sensors (i.e., bioyield firmness, sonic firmness, visible/near-infrared spectroscopy, and spectral scattering). Different spectral/image analysis methods and sensors combinations were evaluated and compared for firmness and SSC prediction. Significantly better predictions of fruit firmness and SSC were obtained using the sensor and data fusion approach, with the improvements ranging between 8% and 26%. The integration of spectral scattering and near-infrared techniques showed particular promising results for accurate measurement of fruit firmness and SSC.
Cen, H., Lu, R., Dolan, K. 2010. Optimization of the inverse algorithm for estimating the optical properties of biological materials using spatially-resolved diffuse reflectance technique. Inverse Problems in Science and Engineering. 18(6):853-872.
Mizushima, A., Noguchi, N., Ishii, K., Matsuo, Y., Lu, R. 2011. Development of a low-cost attitude sensor for agricultural vehicles. Computers and Electronics in Agriculture. 76(2):198-204.
Cen, H., Lu, R. 2010. Optimization of the hyperspectral imaging-based spatially-resolved system for measuring the optical properties of biological materials. Optics Express. 18(16):17412-17432.
Lu, R., Ariana, D.P., Cen, H. 2011. Optical absorption and scattering properties of normal and defective pickling cucumbers for 700-1000 nm. Sensing and Instrumentation for Food Quality and Safety. 5(2):198-204.
Ariana, D.P., Lu, R. 2010. Hyperspectral waveband selection for internal defect detection of pickling cucumbers and whole pickles. Computers and Electronics in Agriculture. 741(1):137-144.
Mizushima, A., Lu, R. 2011. Cost benefits analysis of in-field presorting for the apple industry. Applied Engineering in Agriculture. 27(1):33-40.
Ruiz-Altisent, M., Ruiz-Garcia, L., Moreda, G., Lu, R., Hernandez-Sanchez, N., Correa, E., Diezma, B., Nicolai, B., Garcia-Ramos, J. 2010. Sensors for product characterization and quality of specialty crops - A review. Computers and Electronics in Agriculture. 74(2):176-194.
Huang, M., Lu, R. 2010. Apple mealiness detection using hyperspectral scattering technique. Postharvest Biology and Technology. 58(3):168-175.
Huang, M., Lu, R. 2010. Optimal wavelengths selection for hyperspectral scattering prediction of apple firmness and soluble solids content. Transactions of the ASABE. 53(4):1175-1182.