Abstract
We compared two approaches to non-invasive proximal sensing of the early changes in fresh-cut lettuce leaf quality: hyperspectral imaging and imaging of variable chlorophyll fluorescence contained in the leaves. The estimations made by the imaging techniques were confronted with the quality assessments made by traditional biochemical assays (i.e., relative water content and foliar pigment (chlorophyll and carotenoid) composition. The hyperspectral imaging-based approach provided the highest sensitivity to the decline of fresh-cut lettuce leaf quality taking place within 24 h from cutting. Using of the imaging pulse-amplitude modulated PAM chlorophyll fluorometer was complicated by (i) weak correlation of the spatial distribution pattern of the Qy parameter with the actual physiological condition of the plant object and (ii) its high degree of heterogeneity. Accordingly, the imaging PAM-based approach was sensitive only to the manifestations of leaf quality degradation at advanced stages of the process. Sealing the leaves in polyethylene bags slowed down the leaf quality degradation at the initial stages (<three days) but promoted its rate at more advanced stages, likely due to build-up of ethylene in the bags. An approach was developed to the processing of hyperspectral data for non-invasive monitoring of the lettuce leaves with a potential for implementation in greenhouses and packing lines.
Highlights
Producing high-quality vegetables for the consumer is a priority goal of any grower regardless of the company size and the farm setup
In the past two decades, the hyperspectral reflectance image (HRI)-based technology has evolved into a powerful noninvasive inspection tool commercially available as instrumentation for packing lines [9,10]
For the purpose of this study, we considered photosynthetic activity as a potential marker of the physiological condition of the studied plant objects [12,13,29]
Summary
Producing high-quality vegetables for the consumer is a priority goal of any grower regardless of the company size and the farm setup. The highest quality of production needs to be assured at all stages of the production chain, from farm to table. This goal calls for the development of affordable and efficient, and preferably non-invasive techniques, for monitoring the quality of vegetable produce. A wide array of methods has been proposed for this task; currently the most widespread approaches are based on recording of light reflected by or chlorophyll (Chl) fluorescence emitted from leaf and/or fruits [1,2]. Light reflected by plant carries ample information about its biochemical composition, tissue architecture, and physiological condition [3]. With the advent of imaging spectrometers and PAM fluorometers, a breakthrough was made in this field empowered by the devices of these type capable of capturing spatially resolved information about the object [14]
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