Assessment of apple texture by quantitative MRI

Quantitative MRI is an appropriate tool to study microstructure of intact fruit. It allows accessing multi-exponential transverse relaxation times (T2) [1] providing insights on water status and distribution at the subcellular level and apparent microporosity maps providing information about gas distribution [2]. In this study, quantitative MRI measurements were carried out on several apple cultivars. Mechanical and biochemical analysis were also performed in order to investigate contributions of microporosity, water distribution and composition to mechanical properties characterizing fruit texture quality. Cultivars studied were Granny-Smith, Ariane, Fuji, EC (experimental cultivar), Florina and Rome-Beauty. MRI multi-exponential T2 and porosity were first measured with a 1.5T clinical scanner. Samples for destructive analysis were then extracted from outer parenchyma. Storage modulus (E’) and dampening factor (Tan∂) of the samples were measured by Dynamic Mechanical Analysis. Water and free-sugar contents and alcohol-insoluble solids were measured for all fruit. Results were analyzed using PCA and ANOVA. The T2 decay in all fruit was well fitted by a tri-exponential curve (T21~25ms; T22~125ms and T23~500ms). Both T2 and microporosity maps revealed parenchyma heterogeneity. PCA of combined MRI, compositional and mechanical data from the outer parenchyma tissue showed that 6 apple genotypes were divided into two groups: G1-Granny-Smith, Ariane and Fuji characterized by higher T22, T23 and E’ and G2-Florina, Rome-Beauty and EC with higher microporosity, Tan∂ and T21-associated amplitude. Apple flesh rigidity (~E’) was inversely related to microporosity. Rome-Beauty and Florina from the G2 are known to be mealy cultivar. The results agreed with previously reported relationship between T2 and apple mealiness [3] and reveal a link between mealiness and Tan∂. By uncovering clear relations between apple parenchyma tissue microporosity and water status with fruit texture, quantitative MRI represents a highly valuable tool for fruit quality assessment.