College of Engineering, China Agricultural University, Beijing, P. R. China.
J Texture Stud. 2023 Apr;54(2):237-244. doi: 10.1111/jtxs.12740. Epub 2023 Feb 9.
Firmness is a valid and widely acknowledged indication of fruit quality that is directly connected to physical structure and mechanical qualities. The deformation signals of kiwifruit for firmness assessment were acquired using an assessment system based on airflow and laser technology in this investigation. Using partial least squares regression (PLSR), genetic algorithm optimization of bp neural network (GA-BP), and an extreme learning machine (ELM), deformation data from kiwifruit was used to create models of Magness-Taylor penetration firmness prediction. The ELM model outperformed the PLSR model, and GA-BP model in the prediction set, with a correlation coefficient of 0.876 and a root mean squared error of 3.576 N in the prediction set. These findings showed that an assessment system based on airflow and laser techniques can be utilized to assess the firmness of kiwifruit quickly and nondestructively.
硬度是果实品质的一个有效且广泛认可的指标，它与果实的物理结构和机械特性直接相关。在这项研究中，我们使用基于气流和激光技术的评估系统来获取猕猴桃硬度评估的变形信号。利用偏最小二乘回归（PLSR）、遗传算法优化的 bp 神经网络（GA-BP）和极限学习机（ELM），我们建立了猕猴桃 Magness-Taylor 穿透硬度预测的变形数据模型。在预测集中，ELM 模型的表现优于 PLSR 模型和 GA-BP 模型，其相关系数为 0.876，预测集的均方根误差为 3.576 N。这些发现表明，基于气流和激光技术的评估系统可用于快速无损地评估猕猴桃的硬度。
