Tomato is one of the most produced crop plants on earth and growing in the fields and greenhouses all over the world. Breeding with known traits of wild species can enhance stress tolerance of cultivated crops. In this study, we investigated responses of the transcriptome as well as primary and secondary metabolites in leaves of a cultivated and a wild tomato to several abiotic stresses such as nitrogen deficiency, chilling or warmer temperatures, elevated light intensities and combinations thereof. The wild species responded different to varied temperature conditions compared to the cultivated tomato. Nitrogen deficiency caused the strongest responses and induced in particular the secondary metabolism in both species but to much higher extent in the cultivated tomato. Our study supports the potential of a targeted induction of valuable secondary metabolites in green residues of horticultural production, that will otherwise only be composted after fruit harvest. In particular, the cultivated tomato showed a strong induction in the group of mono caffeoylquinic acids in response to nitrogen deficiency. In addition, the observed differences in stress responses between cultivated and wild tomato can lead to new breeding targets for better stress tolerance.

Plants have evolved energy dissipation pathways to reduce photooxidative damage under drought when photosynthesis is hampered. Non-volatile and volatile isoprenoids are involved in non-photochemical quenching of excess light energy and scavenging of reactive oxygen species. A better understanding of trees’ ability to cope with and withstand drought stress will contribute to mitigate the negative effects of prolonged drought periods expected under future climate conditions. Therefore we investigated if Douglas-fir (Pseudotsuga menziesii(Mirb.)) provenances from habitats with contrasting water availability reveal intraspecific variation in isoprenoid-mediated energy dissipation pathways. In a controlled drought experiment with 1-year-old seedlings of an interior and a coastal Douglas-fir provenance, we assessed the photosynthetic capacity, pool sizes of non-volatile isoprenoids associated with the photosynthetic apparatus, as well as pool sizes and emission of volatile isoprenoids. We observed variation in the amount and composition of non-volatile and volatile isoprenoids among provenances, which could be linked to variation in photosynthetic capacity under drought. The coastal provenance exhibited an enhanced biosynthesis and emission of volatile isoprenoids, which is likely sustained by generally higher assimilation rates under drought. In contrast, the interior provenance showed an enhanced photoprotection of the photosynthetic apparatus by generally higher amounts of non-volatile isoprenoids and increased amounts of xanthophyll cycle pigments under drought. Our results demonstrate that there is intraspecific variation in isoprenoid-mediated energy dissipation pathways among Douglas-fir provenances, which may be important traits when selecting provenances suitable to grow under future climate conditions.

This article presents GrowliFlower, a georeferenced, image-based UAV time series dataset of two monitored cauliflower fields of size 0.39 and 0.60 ha acquired in 2020 and 2021. The dataset contains RGB and multispectral orthophotos from which about 14,000 individual plant coordinates are derived and provided. The coordinates enable the dataset users the extraction of complete and incomplete time series of image patches showing individual plants. The dataset contains collected phenotypic traits of 740 plants, including the developmental stage as well as plant and cauliflower size. As the harvestable product is completely covered by leaves, plant IDs and coordinates are provided to extract image pairs of plants pre and post defoliation, to facilitate estimations of cauliflower head size. Moreover, the dataset contains pixel-accurate leaf and plant instance segmentations, as well as stem annotations to address tasks like classification, detection, segmentation, instance segmentation, and similar computer vision tasks. The dataset aims to foster the development and evaluation of machine learning approaches. It specifically focuses on the analysis of growth and development of cauliflower and the derivation of phenotypic traits to foster the development of automation in agriculture. Two baseline results of instance segmentation at plant and leaf level based on the labeled instance segmentation data are presented. The entire data set is publicly available.

Tomato is one of the most produced crop plants on earth and growing in the fields and greenhouses all over the world. Breeding with known traits of wild species can enhance stress tolerance of cultivated crops. In this study, we investigated responses of the transcriptome as well as primary and secondary metabolites in leaves of a cultivated and a wild tomato to several abiotic stresses such as nitrogen deficiency, chilling or warmer temperatures, elevated light intensities and combinations thereof. The wild species responded different to varied temperature conditions compared to the cultivated tomato. Nitrogen deficiency caused the strongest responses and induced in particular the secondary metabolism in both species but to much higher extent in the cultivated tomato. Our study supports the potential of a targeted induction of valuable secondary metabolites in green residues of horticultural production, that will otherwise only be composted after fruit harvest. In particular, the cultivated tomato showed a strong induction in the group of mono caffeoylquinic acids in response to nitrogen deficiency. In addition, the observed differences in stress responses between cultivated and wild tomato can lead to new breeding targets for better stress tolerance.