基于高光谱成像技术的菜花净菜货架期检测

Minimally processed vegetables, including fresh-cut products, are today particularly appreciated by consumers, due to their nutritive properties, convenience and ease of use. The commercial feasibility of minimally processed commodities is closely connected with their ability to keep quality attributes. The shelf life of these products is affected by a number of factors, such as growing techniques, harvesting operations, processing and storage conditions. In this proposal, cauliflower will be chosen as the research object; heat shock treatment, mini-dehydration and storage temperature will be chosen as the pretreatment of preservation technology. The effect of integrating optimized combination of pretreatment on shelf life of minimally processed cauliflower will be appraised through analysis of their sensory attributes(color, texture and crude fiber content), content of nutrients(vitamin C, soluble sugar and soluble protein) ,antioxidant characteristics(peroxidase/POD, polyphenol oxidase/PPO, superoxide dismutase/SOD and catalase/CAT) and microbial population during storage. Based on this, hyperspectral image technique will be used to detect the quality and shelf life of minimally processed cauliflower. The spectral and image information will be collect by hyperspectral imaging, then, the coupling relationship will be established between spectral, image information and quality parameters (sensory attributes, content of nutrients, antioxidant characteristics and microbial population) by using lots of linear and nonlinear regression models, in order to realize the on-line and nondestructive detection of quality parameters and shelf life of minimally processed cauliflower. In summary, our study will enrich the theory of minimally processed vegetables, and developing the development of on-line detection equipment for minimally processed cauliflower.

净菜由于具有特殊的加工特点，其品质维护的难度很大，在加工、贮藏和销售各个环节中都非常容易引起品质下降。因此，本项目以菜花作为研究对象，在对菜花进行净菜加工前处理的基础上，着重研究菜花净菜加工与保鲜的关键工艺，包括热激处理、微脱水处理、储藏温度等加工工艺，并分析了菜花净菜在各种保鲜处理过程和贮藏环境下生理生化的衰变趋势，以得到适用于菜花净菜加工的保鲜工艺手段及相应参数。在此基础上，采用高光谱成像技术，研究菜花净菜的光谱及图像信息与其多项品质参数（感官品质、营养物质含量、抗氧化指标、细菌总数）之间的耦合关系，实现对菜花净菜货架期间多项品质参数的实时检测，并对菜花净菜的最佳食用期进行预判。本项目的研究可丰富净菜加工理论，也为开发菜花净菜在线检测设备奠定基础。

随着净菜产品日益增多，且净菜的保鲜货架期较短，因此本项目以菜花净菜作为研究对象，主要针对净菜的保鲜加工工艺进行研究，进而实现对菜花净菜货架期间多项内、外部品质进行无损、快速的含量预测及品质分类。. 为探究采后外源性褪黑素处理、不同温度氯化钙溶液处理对菜花净菜货架期间品质及生理的影响，试验以“雪白”花椰菜为材料，从生理、细胞和基因表达水平解析不同保鲜工艺对鲜切花椰菜保鲜品质的调节作用。结果表明：0.10 mmol L−1褪黑素处理和40℃的2%Cacl2溶液处理都可能是延长其采后寿命和提高品质的有效技术。利用可见/近红外光谱技术对菜花净菜的色泽、抗坏血酸、总硫代葡萄糖苷、硬度、超氧阴离子自由基含量、总酚6项内部指标建立了PLS预测模型，经过预处理、特征波长提取等模型优化手段，分别建立了6项指标最优的预测模型，各模型的R2可分别达到0.9089、0.9703、0.7382、0.9606、0.9354、0.8590。在此基础上，以抗坏血酸为例，应用MLR算法建立菜花净菜的抗坏血酸动力学模型，从而确立了菜花净菜贮藏时间与近红外光谱和抗坏血酸含量的线性回归关系，实现了菜花净菜室温贮藏期间抗坏血酸含量的实时监测及贮藏时间的预测。此外，利用计算机视觉技术和可见/今红外光谱技术完成了对菜花净菜外部品质（腐烂及早期病害）的检测。利用图像处理技术首先完成对相互粘连的净菜样本的分离，通过图像信息的提取技术，提取完好和腐烂样本的相关图像信息并建模判别模型，该模型对菜花净菜腐烂样本的判别准确率可达到90%以上。而利用光谱技术可实现对菜花净菜早期灰霉病害的分类检测，分类模型的建模精度可达到92%以上。. 本项目在丰富净菜加工理论的同时，为后期菜花净菜在线工厂化检测设备的研发提供参考和基础数据支持。