Reflectance based non-destructive assessment of tomato fruit firmness
2022
Kumar, Rajeev | Paul, Vijay | Pandey, Rakesh | Sahoo, R. N. | Gupta, V. K. | Asrey, Ram | Jha, Surya Kant
Tomato fruit firmness is an important quality parameter as it plays decisive role in its preference and acceptability by the consumers. So, non-destructive and rapid assessment of firmness of tomato fruit is of immense significance in view of monitoring, postharvest management (PHM), marketing and processing. This study identified reflectance-based indices and developed models for non-destructive assessment of tomato fruit firmness. Tomato fruits of two varieties and two hybrids (at different ripening stages) were taken either directly from the plants or during the period of postharvest storage. Reflectance (350 to 2500 nm) of individual fruit was recorded by spectroradiometer. Fruits were then subjected for actual firmness (N) measurement (ranged from 11.74 to 1.13 N) along with the determination of ripening stages (immature to over-ripe stage). Thereafter, reflectance and firmness data were subjected to chemometric analysis for the development of models. Out of different models developed, model [y (firmness in N) = 1260.800 x + 3.309] based on the index i.e., x = R₅₀₁ (1st derivative) was found to be the best. This model can accurately predict the firmness for a difference of ≥ 1.05 N with biasness of − 0.01 N. The second-best model [y = − 5.377 x² + 18.209 x + 2.951] was based on the index R₅₂₁ (= x). This had the predictability of ≥ 1.11 N with biasness of − 0.002 N. The developed models were able to predict the firmness of tomato fruits across the varieties/hybrids, ripening stages and ripening conditions i.e., plant harvested (fresh) and stored (aged) fruits. The findings will prove useful in developing cost-effective tools for automation of firmness-based sorting and monitoring resulting in rapid phenotyping and better PHM of tomatoes.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par National Agricultural Library
Découvrez la collection de ce fournisseur de données dans AGRIS