Mechanical-based and Optical-based Methods for Nondestructive Evaluation of Fruit Firmness

Fruits are important agricultural products in the current society. The demands for high-quality fruits have promoted the development of various nondestructive firmness evaluation methods in recent 20 years. The nondestructive and fast techniques used in the prediction of the firmness of various fruits can be divided into two categories: optical-based methods and mechanical-based methods. Optical-based methods mainly refer to visible/near-infrared (Vis/NIR) spectroscopy, hyperspectral or multispectral imaging (HIS/MSI), spatially resolved reflectance spectroscopy (SRRS), laser light backscatter imaging (LLBI), and others. Mechanical-based methods including several techniques such as micro-deformation, vibration measurements, acoustic impact response, falling impact, hammer impact, and ultrasonic methods. Fundamental principles, as well as measured performances of mechanical-based methods and optical-based methods for measuring the firmness of fruit, are discussed in detail in this paper. The techniques that can be applied to on-line sorting are considered emphatically. Both mechanical-based and optical-based methods have advantages and disadvantages in predicting fruit firmness. The correlations between the firmness measured by mechanical-based methods and puncture firmness are poor in some studies, and the optical methods also have not obtained satisfactory results. Therefore, the on-line measurement of fruit firmness with high accuracy is still facing some challenges.

水果是当前社会重要的农产品。近20年来，市场对高品质果品的需求推动了各类无损硬度评估方法的发展。用于各类水果硬度预测的无损快速检测技术可分为两大类：基于光学的检测方法与基于力学的检测方法。其中，基于光学的检测方法主要包括可见/近红外（Visible/Near-Infrared, Vis/NIR）光谱技术、高光谱或多光谱成像（Hyperspectral/Multispectral Imaging, HIS/MSI）、空间分辨反射光谱（Spatially Resolved Reflectance Spectroscopy, SRRS）、激光后向散射成像（Laser Light Backscatter Imaging, LLBI）等。基于力学的检测方法则涵盖微形变检测、振动测试、声冲击响应、跌落冲击、锤击以及超声检测等多种技术。本文详细论述了用于水果硬度检测的基于力学与光学的两类检测方法的基本原理及其实测性能，并重点探讨了可应用于在线分选的检测技术。两类检测方法在水果硬度预测中各有优劣：部分研究显示，基于力学方法测得的硬度与穿刺硬度之间的相关性较差，而光学方法也未取得令人满意的检测效果。因此，实现高精度的水果硬度在线检测仍面临诸多挑战。