1. Monte Carlo: A flexible and accurate technique for modeling light transport in food and agricultural products
- Author
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Yibin Ying, Lijian Yao, Zidong Yang, Aichen Wang, Sun Tong, and Dong Hu
- Subjects
Flexibility (engineering) ,Scope (project management) ,business.industry ,Computer science ,Monte Carlo method ,Optical property ,04 agricultural and veterinary sciences ,01 natural sciences ,040501 horticulture ,Domain (software engineering) ,010309 optics ,Computer graphics ,Agriculture ,0103 physical sciences ,Lack of knowledge ,Biochemical engineering ,0405 other agricultural sciences ,business ,Food Science ,Biotechnology - Abstract
Background Monte Carlo (MC) has been widely used in fields such as biomedicine and computer graphics owing to its unique capabilities of flexibility, high-accuracy and simplicity for modeling light transport in tissues, but the applications in food and agricultural domain are limited or hindered due to the lack of knowledge on the optical properties of food products. Thanks to major breakthroughs in optical measuring and computing technologies since the year of 2000, significant advances have been made in sensing techniques for measuring tissue optical properties. Therefore, MC has witnessed great progress in food and agricultural domain over the past two decades. Scope and approach The development of MC for modeling light transport in food and agricultural products, including the principle, advanced MC methods, relevant applications, and future perspectives were reviewed. The paper is aimed at helping interested researchers to gain a better understanding of the MC technique, thus stimulating quality and safety assessment of food and agricultural products. Key findings and conclusions This paper provides an overview of the procedure of MC modeling for light transport in food and agricultural products and commonly used MC models. Advanced methods for accelerating MC simulations are then presented. Applications of MC simulations in food and agricultural products, since the year of 2000, for optimizing the design of sensing configuration and parameter, estimating tissue optical property, and assessing quality and safety are then reviewed. Finally, challenges and future perspectives for MC technique in modeling light transport are discussed.
- Published
- 2020