|Qin, J - MICHIGAN ST UNIVERSITY|
Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 21, 2009
Publication Date: August 1, 2009
Citation: Qin, J., Lu, R. 2009. Monte Carlo Simulation for Quantification of Light Transport Features in Apples. Computers and Electronics in Agriculture. 68(1):44-51. Interpretive Summary: Quantitative understanding of light interaction with the plant tissue is needed for the development of an effective optical system for quality inspection of fruit. To achieve this goal, it is necessary to measure the optical properties of fruit and develop computer simulation models to quantify light transfer and distribution inside the fruit. In this research, spectral absorption and scattering coefficients, two fundamental optical properties, were measured from Golden Delicious apples in the visible and near-infrared spectral range using a new optical technique developed in our lab. Simulation models were developed using the Monte Carlo method, a stochastic numerical algorithm, to quantify light absorption and scattering in Golden Delicious apples, two basic phenomena that take place as light propagates in the fruit tissue. The simulations provided detailed information on light absorption profiles inside the fruit and diffuse reflectance profiles at the fruit surface. In addition, light penetration depths were estimated for the apples. The research also showed how computer simulation could guide the design and selection of an appropriate optical sensing configuration for effective measurement of diffuse reflectance from the fruit. The research offered a systematic approach for measuring the optical properties of fruit and using computer simulation to quantify light transfer in the fruit and to assist in development of an optical system for quality inspection of fruits and agricultural products. Researchers and engineers can use the methodology developed in this research to gain better understanding of light interaction with the fruit tissue and improve optical measurement for quality inspection of fruit.
Technical Abstract: Light interaction with turbid biological materials involves absorption and scattering. Quantitative understanding of light propagation features in the fruit is critical to designing better optical systems for inspection of food quality. This article reports on the quantification of light propagation in the apple fruit in the visible and short-wave near-infrared region using Monte Carlo simulations. Spectral absorption and scattering properties were determined from 600 ‘Golden Delicious’ apples over the spectral range of 500-1000 nm using a hyperspectral imaging method coupled with a diffusion theory model, and they were then used in Monte Carlo (MC) models to simulate light transport in the fruit tissue. MC simulation models were validated by comparing with the diffusion theory model and experimental data. The patterns of diffuse reflectance, internal absorption, and light penetration depth were determined using typical values of the absorption and reduced scattering coefficients for the apples. Simulation results showed that up to 96.4% of the photons were absorbed under the maximum absorption condition, whereas 75.9% photons exited as diffuse reflectance for the maximum scattering case. The optimum sensing range under our imaging system setup was found to be 1 to 11 mm for ‘Golden Delicious’ apples. Fruit tissue with a larger absorption coefficient value absorbed light energy rapidly in short depths and radial distances, and light in the tissue with a small reduced scattering coefficient value tended to propagate forward to the deeper area of the sample. Light penetration depths in ‘Golden Delicious’ apples, defined as the depths at which the incident light was reduced by 99%, were in the range of 0.43 to 8.67 cm over the 500-1000 nm spectral range, with a majority of the samples (approximately 68%) in the range of 0.81 to 4.48 cm. Pigments and water in the fruit tissue greatly influenced light penetration depth.