Predicting sensitivity of recently harvested tomatoes and tomato sepals to future fungal infections.

Tomato is an important commercial product which is perishable by nature and highly susceptible to fungal incidence once it is harvested. Not all tomatoes are equally vulnerable to pathogenic fungi, and an early detection of the vulnerable ones can help in taking timely preventive actions, ranging from isolating tomato batches to adjusting storage conditions, but also in making right business decisions like dynamic pricing based on quality or better shelf life estimate. More importantly, early detection of vulnerable produce can help in taking timely actions to minimize potential post-harvest losses. This paper investigates Near-infrared (NIR) hyperspectral imaging (1000-1700 nm) and machine learning to build models to automatically predict the susceptibility of sepals of recently harvested tomatoes to future fungal infections. Hyperspectral images of newly harvested tomatoes (cultivar Brioso) from 5 different growers were acquired before the onset of any visible fungal infection. After imaging, the tomatoes were placed under controlled conditions suited for fungal germination and growth for a 4-day period, and then imaged using normal color cameras. All sepals in the color images were ranked for fungal severity using crowdsourcing, and the final severity of each sepal was fused using principal component analysis. A novel hyperspectral data processing pipeline is presented which was used to automatically segment the tomato sepals from spectral images with multiple tomatoes connected via a truss. The key modelling question addressed in this research is whether there is a correlation between the hyperspectral data captured at harvest and the fungal infection observed 4 days later. Using 10-fold and group k-fold cross-validation, XG-Boost and Random Forest based regression models were trained on the features derived from the hyperspectral data corresponding to each sepal in the training set and tested on hold out test set. The best model found a Pearson correlation of 0.837, showing that there is strong linear correlation between the NIR spectra and the future fungal severity of the sepal. The sepal specific predictions were aggregated to predict the susceptibility of individual tomatoes, and a correlation of 0.92 was found. Besides modelling, focus is also on model interpretation, particularly to understand which spectral features are most relevant to model prediction. Two approaches to model interpretation were explored, feature importance and SHAP (SHapley Additive exPlanations), resulting in similar conclusions that the NIR range between 1390-1420 nm contributes most to the model's final decision.

Cloning and characterisation of a maize carotenoid cleavage dioxygenase (ZmCCD1) and its involvement in the biosynthesis of apocarotenoids with various roles in mutualistic and parasitic interactions.

Colonisation of maize roots by arbuscular mycorrhizal (AM) fungi leads to the accumulation of apocarotenoids (cyclohexenone and mycorradicin derivatives). Other root apocarotenoids (strigolactones) are involved in signalling during early steps of the AM symbiosis but also in stimulation of germination of parasitic plant seeds. Both apocarotenoid classes are predicted to originate from cleavage of a carotenoid substrate by a carotenoid cleavage dioxygenase (CCD), but the precursors and cleavage enzymes are unknown. A Zea mays CCD (ZmCCD1) was cloned by RT-PCR and characterised by expression in carotenoid accumulating E. coli strains and analysis of cleavage products using GC-MS. ZmCCD1 efficiently cleaves carotenoids at the 9, 10 position and displays 78% amino acid identity to Arabidopsis thaliana CCD1 having similar properties. ZmCCD1 transcript levels were shown to be elevated upon root colonisation by AM fungi. Mycorrhization led to a decrease in seed germination of the parasitic plant Striga hermonthica as examined in a bioassay. ZmCCD1 is proposed to be involved in cyclohexenone and mycorradicin formation in mycorrhizal maize roots but not in strigolactone formation.