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Abstract
Controlled environment agriculture (CEA) leads to higher crop productivity by maintaining optimum environmental conditions but results in high operating costs as a trade-off. To overcome this, an ideal lettuce (Lactuca sativa) cultivar in CEA is one that can achieve high dry matter (DM) production with relatively low inputs. DM production is dependent on incident light on the crop canopy and the light use efficiency (LUE, grams of DM per mole incident photons), associated with canopy size and photosynthesis, respectively. A simple chlorophyll fluorescence imaging (CFI) was used to quantify the projected canopy size (PCS) of 11 lettuce cultivars over the cropping cycle. Variation in early PCS predicted differences in the final shoot DM of green lettuce but not in red cultivars. Because anthocyanins absorb a fraction of incoming photons, making them unavailable to light reactions, they reduce photosynthesis and DM production. The inhibitory effect of anthocyanin on photosynthesis and its interaction with photosynthetic photon flux density (PPFD) was characterized. The decrease in lettuce photosynthesis and quantum yield of CO2 assimilation (QYCO2) at each PPFD was proportional to the anthocyanin concentration and this trend was more prominent at higher PPFDs. The QYCO2 was 92% lower under the combination of high anthocyanin concentrations and high PPFD compared to low anthocyanin concentrations and low PPFD. Changes in DM partitioning and LUE over the cropping cycle were studied with periodic destructive measurements in lettuce. Cultivar-specific parameterization accurately estimated growth parameters needed for crop growth models. The LUE depended on anthocyanin and chlorophyll content, which have a negative and positive relationship with LUE. Given the importance of anthocyanins in DM production, a spatially-resolved phenotyping system for anthocyanin quantification is needed. Thus, the normalized difference anthocyanin index (NDAI) was developed based on the optical properties of anthocyanins: high absorptance in the green and low absorptance in the red part of the spectrum. The NDAI, using multispectral or RGB images, predicted lettuce anthocyanin concentrations accurately. The image-based phenotyping methods and a better understanding of their underlying physiology will facilitate more efficient DM production in CEA.