Isabelle, S. | bioRxiv Science

bioRxiv2026

Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth

Non-invasive, high-throughput phenotyping tools are needed that can identify environmental effects on plant structure and function to diagnose factors responsible for reduced growth in commercial and non-commercial settings. In this study, we explored whether the integration of 3D-multispectral (3D) and 2D-hyperspectral imaging (HSI), aided by machine learning (ML), could be used to identify environmental stress treatments imposed during plant growth. Controlled environment-grown Nicotiana Benthamiana plants were subjected to a range of abiotic treatments - including different growth irradiances, heat treatment and drought stress - with the treatments resulting in differences in shoot height, biomass, leaf area and spectral reflectance. ML models were trained to identify these treatments using morphological and spectral traits measured at 27, 29, 31, and 34 days after sowing (DAS). A 3D-multispectral scanner was used to obtain information on plant height, biomass, and leaf area. A visible and near-infrared (VNIR) HSI camera provided detailed spectral information for deriving spectral indices including the Normalised Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI) and Normalized Difference Red Edge (NDRE). Manual measurements provided baseline comparative data. The 3D-multispectral scanner reliably estimated above-ground traits, with high correlations between manual and scanner-derived measurements. The ML models accurately differentiated among environmental stress treatments, with the fused 3D+HSI model achieving the best overall predictive performance across all evaluated metrics compared with models based on either imaging modality alone. Results demonstrated the effectiveness of combining 3D-multispectral and 2D-HSI data with ML analyses for non-destructive, high-throughput phenotyping. The integration of these techniques enabled non-destructive, high-throughput identification of environmental stress treatments imposed during plant growth.

plant biology↗

bioRxiv2022

Structural variations in the phytoene synthase 1 gene affect carotenoid accumulation in tomato fruits and result in bicolor and yellow phenotypes

Tomato fruits normally accumulate large amounts of the red pigment lycopene in their chromoplasts. Some tomato cultivars (Solanum lycopersicum) show however distinct phenotypes, from a pure yellow hue to bicolor fruits with red and yellow sections. In this study, we show that alleles of the phytoene synthase 1 gene (PSY1), the first gene of carotenoid synthesis pathway, are responsible for the yellow, but also the bicolor phenotype. Introgression lines with the PSY1 allele from the green-fruited species S. habrochaites express less the enzyme, resulting in a bicolor phenotype. On the other hand, in tomato bicolor cultivars, the same coloration pattern is caused by a 3789 bp-deletion in the promoter region of PSY1. Since the deletion contains part of the 5UTR region of PSY1, translation efficiency is likely decreased resulting in a reduction of lycopene accumulation. Furthermore, we identified that the yellow ry phenotype is caused by a duplication and an inversion implicating PSY1 and the downstream neighbor gene. The genomic rearrangement change the end of PSY1 amino acid sequence. The fruits of yellow ry cultivars are still able in certain conditions to accumulate lycopene near the blossom-end of the fruit, though to a lesser extent than in bicolor cultivars. In contrast, fruits of the yellow r cultivars never present fleshy red sections. These cultivars have an insertion of a single long terminal repeat from the Rider transposon in the first exon of PSY1 resulting in a non-functional protein. These results demonstrate how multiple phenotypes can arise from structural variations in a key gene.

plant biology↗