A coherent feed forward loop drives vascular regeneration in damaged aerial organs growing in normal developmental-context
. Development 2020
Aerial organs of plants being highly prone to local injuries, require tissue restoration to ensure their survival. However, knowledge of the underlying mechanism is sparse. In this study, we mimicked natural injuries in growing leaf and stem to study the reunion between mechanically disconnected tissues. We show that ()/ () genes, which encodes stem cell promoting factors, are activated and contribute to vascular regeneration in response to these injuries. PLT proteins bind to and activate the CUC2 promoter. Both PLT and CUC2 regulate the transcription of the local auxin biosynthesis gene YUC4 in a coherent feed forward loop, and this process is necessary to drive vascular regeneration. In the absence of this PLT mediated regeneration response, leaf ground tissue cells can neither acquire early vascular identity marker ATHB8, nor properly polarize auxin transporters to specify new venation paths. The PLT-CUC2 module is required for vascular regeneration, but is dispensable for midvein formation in leaf. We reveal the mechanisms of vascular regeneration in plants and distinguishes the wound repair ability of the tissue from its formation during normal development.
High-density NGS-based map construction and genetic dissection of fruit shape and rind netting in Cucumis melo
. Theor Appl Genet 2020
Melon is an important crop that exhibits broad variation for fruit morphology traits that are the substrate for genetic mapping efforts. In the post-genomic era, the link between genetic maps and physical genome assemblies is key for leveraging QTL mapping results for gene cloning and breeding purposes. Here, using a population of 164 melon recombinant inbred lines (RILs) that were subjected to genotyping-by-sequencing, we constructed and compared high-density sequence- and linkage-based recombination maps that were aligned to the reference melon genome. These analyses reveal the genome-wide variation in recombination frequency and highlight regions of disrupted collinearity between our population and the reference genome. The population was phenotyped over 3 years for fruit size and shape as well as rind netting. Four QTLs were detected for fruit size, and they act in an additive manner, while significant epistatic interaction was found between two neutral loci for this trait. Fruit shape displayed transgressive segregation that was explained by the action of four QTLs, contributed by alleles from both parents. The complexity of rind netting was demonstrated on a collection of 177 diverse accessions. Further dissection of netting in our RILs population, which is derived from a cross of smooth and densely netted parents, confirmed the intricacy of this trait and the involvement of major locus and several other interacting QTLs. A major netting QTL on chromosome 2 co-localized with results from two additional populations, paving the way for future study toward identification of a causative gene for this trait.
Pharmaceuticals in treated wastewater induce a stress response in tomato plants
. Sci Rep 2020
Pharmaceuticals remain in treated wastewater used to irrigate agricultural crops. Their effect on terrestrial plants is practically unknown. Here we tested whether these compounds can be considered as plant stress inducers. Several features characterize the general stress response in plants: production of reactive oxygen species acting as stress-response signals, MAPKs signaling cascade inducing expression of defense genes, heat shock proteins preventing protein denaturation and degradation, and amino acids playing signaling roles and involved in osmoregulation. Tomato seedlings bathing in a cocktail of pharmaceuticals (Carbamazepine, Valporic acid, Phenytoin, Diazepam, Lamotrigine) or in Carbamazepine alone, at different concentrations and during different time-periods, were used to study the patterns of stress-related markers. The accumulation of the stress-related biomarkers in leaf and root tissues pointed to a cumulative stress response, mobilizing the cell protection machinery to avoid metabolic modifications and to restore homeostasis. The described approach is suitable for the investigation of stress response of different crop plants to various contaminants present in treated wastewater.
Upregulation of photosynthesis in mineral nutrition-deficient tomato plants by reduced source-to-sink ratio
. Plant Signal Behav 2020
Photosynthetic activity is affected by environmental factors and endogenous signals controlled by the source-sink relationship. We recently showed upregulated photosynthetic rate following partial defoliation under favorable environmental conditions. Here, we examined the influence of partial defoliation on the remaining leaves' function in tomato plants under nutrient deficiency. The effect of partial defoliation was more pronounced under limited mineral supply vs. favorable conditions. Reduced source-sink ratio resulted in increased stomatal conductance and transpiration rate, as well as higher photosystem II efficiency. Although chlorophyll concentration was significantly reduced under limited nutrient supply, the photosynthetic rate in the remaining leaf was similar to that measured under normal fertilization. Expression of genes involved in the phloem loading of assimilated sugars was downregulated in the remaining source leaf of unfertilized plants, 15 d after partial defoliation; in fertilized plants, these genes' expression was similar in control and partially defoliated plants. We propose that at early stage, the additional carbon assimilated in the remaining leaf is devoted to increasing source size rather than sink growth. The size increase of the remaining leaf in unfertilized plants was not sufficient to rebalance the source-sink ratio, resulting in inhibited sugar export and further carbohydrate allocation in the remaining leaf.
Root-shoot communication in tomato plants: cytokinin as a signal molecule modulating leaf photosynthetic activity
. Journal of experimental botany 2020
, 247-257. Publisher's VersionAbstract
Photosynthetic activity is affected by exogenous and endogenous inputs, including source-sink balance. Reducing the source to sink ratio by partial defoliation or heavy shading resulted in significant elevation of the photosynthetic rate in the remaining leaf of tomato plants within 3 d. The remaining leaf turned deep green, and its area increased by almost 3-fold within 7 d. Analyses of photosynthetic activity established up-regulation due to increased carbon fixation activity in the remaining leaf, rather than due to altered water balance. Moreover, senescence of the remaining leaf was significantly inhibited. As expected, carbohydrate concentration was lower in the remaining leaf than in the control leaves; however, expression of genes involved in sucrose export was significantly lower. These results suggest that the accumulated fixed carbohydrates were primarily devoted to increasing the size of the remaining leaf. Detailed analyses of the cytokinin content indicated that partial defoliation alters cytokinin biosynthesis in the roots, resulting in a higher concentration of trans-zeatin riboside, the major xylem-translocated molecule, and a higher concentration of total cytokinin in the remaining leaf. Together, our findings suggest that trans-zeatin riboside acts as a signal molecule that traffics from the root to the remaining leaf to alter gene expression and elevate photosynthetic activity. © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology.
Multiseasonal grapevine water consumption – Drivers and forecasting
. Agricultural and Forest Meteorology 2020
. Publisher's VersionAbstract
The interactions between temperature, relative humidity, radiation, wind speed and their effect on plant transpiration in the context of water consumption for irrigation purposes have been studied for over a century. Leaf area has also been established as an important factor affecting water consumption. We analyzed a multivariable time series composed of both meteorological and vegetative variables with a daily temporal resolution for the growing seasons of 2013–2016 for Vitis vinfera ‘Cabernet Sauvignon’ vineyards in the mountainous region in Israel. Time-series analysis of this data was used to characterize seasonal patterns affecting water consumption (ETc) of vines and to quantify interrelations between meteorological and vegetative factors affecting vine water consumption. Moreover, we applied a machine learning regression model to determine the relative influence of meteorological and vegetative factors on ETc during four growing seasons. Finally, we developed an ensemble model for temporally forecasting vine ETc for an additional season using a training dataset of multiple variables. Our findings show that decomposing the time-series dataset uncovered a wider variety of underlying temporal patterns, and enabled quantification of seasonal and daily relationships. Leaf area had a substantial impact on ETc and was found to have a relative influence ranging between 62 and 86% for the different growing seasons. Mean temperature was ranked second followed by minor effects of relative humidity, solar radiation and wind speed that were interchangeably ordered. The ensemble model produced reliable results, with cross validation coefficients 0.9. Incorporating leaf area measurements into the regression model improved both the performance of the model and the training data correlation. Using time-series statistics to explore meteorological and vegetative temporal characteristics, patterns, interrelations and relative effect on evapotranspiration may facilitate the understanding of water consumption processes and assist in generating more effective and skillful irrigation models. © 2019 Elsevier B.V.
Genetic Screening for Mutants with Altered Seminal Root Numbers in Hexaploid Wheat Using a High-Throughput Root Phenotyping Platform
. G3 (Bethesda) 2019
Roots are the main channel for water and nutrient uptake in plants. Optimization of root architecture provides a viable strategy to improve nutrient and water uptake efficiency and maintain crop productivity under water-limiting and nutrient-poor conditions. We know little, however, about the genetic control of root development in wheat, a crop supplying 20% of global calorie and protein intake. To improve our understanding of the genetic control of seminal root development in wheat, we conducted a high-throughput screen for variation in seminal root number using an exome-sequenced mutant population derived from the hexaploid wheat cultivar Cadenza. The screen identified seven independent mutants with homozygous and stably altered seminal root number phenotypes. One mutant, Cadenza0900, displays a recessive extra seminal root number phenotype, while six mutants (Cadenza0062, Cadenza0369, Cadenza0393, Cadenza0465, Cadenza0818 and Cadenza1273) show lower seminal root number phenotypes most likely originating from defects in the formation and activation of seminal root primordia. Segregation analysis in F populations suggest that the phenotype of Cadenza0900 is controlled by multiple loci whereas the Cadenza0062 phenotype fits a 3:1 mutant:wild-type segregation ratio characteristic of dominant single gene action. This work highlights the potential to use the sequenced wheat mutant population as a forward genetic resource to uncover novel variation in agronomic traits, such as seminal root architecture.
Pathways to defense metabolites and evading fruit bitterness in genus Solanum evolved through 2-oxoglutarate-dependent dioxygenases
. Nat Commun 2019
The genus Solanum comprises three food crops (potato, tomato, and eggplant), which are consumed on daily basis worldwide and also producers of notorious anti-nutritional steroidal glycoalkaloids (SGAs). Hydroxylated SGAs (i.e. leptinines) serve as precursors for leptines that act as defenses against Colorado Potato Beetle (Leptinotarsa decemlineata Say), an important pest of potato worldwide. However, SGA hydroxylating enzymes remain unknown. Here, we discover that 2-OXOGLUTARATE-DEPENDENT-DIOXYGENASE (2-ODD) enzymes catalyze SGA-hydroxylation across various Solanum species. In contrast to cultivated potato, Solanum chacoense, a widespread wild potato species, has evolved a 2-ODD enzyme leading to the formation of leptinines. Furthermore, we find a related 2-ODD in tomato that catalyzes the hydroxylation of the bitter α-tomatine to hydroxytomatine, the first committed step in the chemical shift towards downstream ripening-associated non-bitter SGAs (e.g. esculeoside A). This 2-ODD enzyme prevents bitterness in ripe tomato fruit consumed today which otherwise would remain unpleasant in taste and more toxic.
Spectroscopic Discrimination of Sorghum Silica Phytoliths
. Front Plant Sci 2019
Grasses accumulate silicon in the form of silicic acid, which is precipitated as amorphous silica in microscopic particles termed phytoliths. These particles comprise a variety of morphologies according to the cell type in which the silica was deposited. Despite the evident morphological differences, phytolith chemistry has mostly been analysed in bulk samples, neglecting differences between the varied types formed in the same species. In this work, we extracted leaf phytoliths from mature plants of (L.) Moench. Using solid state NMR and thermogravimetric analysis, we show that the extraction methods alter greatly the silica molecular structure, its condensation degree and the trapped organic matter. Measurements of individual phytoliths by Raman and synchrotron FTIR microspectroscopies in combination with multivariate analysis separated bilobate silica cells from prickles and long cells, based on the silica molecular structures and the fraction and composition of occluded organic matter. The variations in structure and composition of sorghum phytoliths suggest that the biological pathways leading to silica deposition vary between these cell types.
Quantitative trait loci for cold tolerance in Chickpea
. Crop Science 2019
, 573-582. Publisher's VersionAbstract
Fall-sown chickpea (Cicer arietinum L.) yields are often double those of spring-sown chickpea in regions with Mediterranean climates that have mild winters. However, winter kill can limit the productivity of fall-sown chickpea. Developing cold-tolerant chickpea would allow the expansion of the current geographic range where chickpea is grown and also improve productivity. The objective of this study was to identify the quantitative trait loci (QTL) associated with cold tolerance in chickpea. An interspecific recombinant inbred line population of 129 lines derived from a cross between ICC 4958, a cold-sensitive desi type (C. arietinum), and PI 489777, a coldtolerant wild relative (C. reticulatum Ladiz), was used in this study. The population was phenotyped for cold tolerance in the field over four field seasons (September 2011-March 2015) and under controlled conditions two times. The population was genotyped using genotypingby- sequencing, and an interspecific genetic linkage map consisting of 747 single nucleotide polymorphism (SNP) markers, spanning a distance of 393.7 cM, was developed. Three significant QTL were found on linkage groups (LGs) 1B, 3, and 8. The QTL on LGs 3 and 8 were consistently detected in six environments with logarithm of odds score ranges of 5.16 to 15.11 and 5.68 to 23.96, respectively. The QTL CT Ca-3.1 explained 7.15 to 34.6% of the phenotypic variance in all environments, whereas QTL CT Ca-8.1 explained 11.5 to 48.4%. The QTLassociated SNP markers may become useful for breeding with further fine mapping for increasing cold tolerance in domestic chickpea. © Crop Science Society of America.
The Selaginella rhizophore has a unique transcriptional identity compared with root and shoot meristems
. New Phytologist 2019
, 882-894. Publisher's VersionAbstract
The genus Selaginella resides in an early branch of the land plant lineage that possesses a vasculature and roots. The majority of the Selaginella root system is shoot borne and emerges through a distinctive structure known as the rhizophore, the organ identity of which has been a long-debated question. The rhizophore of Selaginella moellendorffii – a model for the lycophytes – shows plasticity to develop into a root or shoot up until 8 d after angle meristem emergence, after which it is committed to root fate. We subsequently use morphology and plasticity to define the stage of rhizophore identity. Transcriptomic analysis of the rhizophore during its plastic stage reveals that, despite some resemblance to the root meristem, rhizophore gene expression patterns are largely distinct from both shoot and root meristems. Based on this transcriptomic analysis and on historical anatomical work, we conclude that the rhizophore is a distinct organ with unique features. © 2019, Blackwell Publishing Ltd. All rights reserved.
Characterization of Silicon Accumulation in Maize Cell Suspension Cultures
. Silicon 2019
, 2377-2383. Publisher's VersionAbstract
Purpose: Silicon (Si) is an abundant element in the earth’s crust and is available to plants as silicic acid. Silicon uptake by plants is correlated with increased tolerance to various biotic and abiotic stresses. However, cellular mechanisms responsible for its beneficial effects are still unknown. Even its cellular import mechanisms are not well understood. We thus aimed to characterize silicon localization within minimally differentiated Zea mays (Black Mexican Sweet) cells in suspension. Methods: Cells were grown in a medium containing silicon, and the mRNA levels of silicon transporters were measured by real-time PCR. Cells were separated into an insoluble (mainly walls and starch) and a cytoplasmic fraction. Soluble and total silicon was measured by inductively-coupled-plasma – atomic-emission-spectroscopy. Silicon distribution was assessed by transmission electron microscopy. The cell walls were analyzed chemically, and by Raman micro-spectroscopy and thermal gravimetric analysis. Results: Silicon treatment reduced the levels of silicon transporters transcripts, without affecting cell proliferation. About 70 % of the silicon was localized in the cytoplasm, mostly in vesicles. We found indications that silicon affected the secondary structure of proteins and thermally stabilized starch. Silicon was loosely bound, and diffused out of the cells within 24 hours. Conclusions: Our results show that silicon binds spontaneously to cell walls/starch and accumulates in cytoplasm vesicles. These processes allow the cells to accumulate silicon against its concentration gradient in solution. However, cellular intake acts against reversible diffusion processes, probably through the aquaporin silicon channels (Lsi1, Lsi6) that exchange the cellular silicon with the surrounding medium. © 2015, Springer Science+Business Media Dordrecht.
Transcriptome analysis and metabolic profiling reveal the key role of α-linolenic acid in dormancy regulation of European pear
. Journal of Experimental Botany 2019
, 734-737. Publisher's VersionAbstract
Deciduous trees require sufficient chilling during winter dormancy to grow. To decipher the dormancy-regulating mechanism, we carried out RNA sequencing (RNA-Seq) analysis and metabolic profiling of European pear (Pyrus communis L.) vegetative buds during the dormancy phases. Samples were collected from two cultivars that differed greatly in their chilling requirements: Spadona' (SPD), a low chilling requirement cultivar; and Harrow Sweet (HS), a high chilling requirement cultivar. Comparative transcriptome analysis revealed >8500 differentially expressed transcripts; most were related to metabolic pathways. Out of 174 metabolites, 44 displayed differential levels in both cultivars, 38 were significantly changed only in SPD, and 15 only in HS. Phospholipids were mostly accumulated at the beginning of dormancy, sugars between before dormancy and mid-dormancy, and fatty acids, including α-linolenic acid, at dormancy break. Differentially expressed genes underlying previously identified major quantitative trait loci (QTLs) in linkage group 8 included genes related to the α-linolenic acid pathway, 12-oxophytodienoate reductase 2-like, and the DORMANCY-ASSOCIATED MADS-BOX (DAM) genes, PcDAM1 and PcDAM2, putative orthologs of PpDAM1 and PpDAM2, confirming their role for the first time in European pear. Additional new putative dormancy-related uncharacterized genes and genes related to metabolic pathways are suggested. These results suggest the crucial role of α-linolenic acid and DAM genes in pear bud dormancy phase transitions. © 2018 The Author(s).
Comparison of water potential and yield parameters under uniform and variable rate drip irrigation in a cabernet sauvignon vineyard
. In Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019
; Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019; 2019; pp. 125-131. Publisher's VersionAbstract
An experiment in variable-rate drip irrigation (VRDI) was aimed at reducing variance of midday stem water potential (SWP) and in yield parameters by applying VRDI in a highly variable vineyard. During 2018, irrigation was separated into VRDI and uniform irrigation (UI) blocks. Each block was delineated to 10 management cells, and results of 2018 season were compared to 2017 season under UI. Standard error (SE) of SWP in the last 3 measurements before harvest decreased in the VRDI block in 2018 compared to 2017 by 14-44%. In contrast, in the UI block, SE in 2018 was higher by 11-42% compared to 2017. SE of fruit yield showed a similar trend. Applying principles of precision irrigation may lead to a more homogeneous vineyard in the parameters described above and to improved wine quality. © Wageningen Academic Publishers 2019
Evidence for large carbon sink and long residence time in semiarid forests based on 15 year flux and inventory records
. Global Change Biology 2019
. Publisher's VersionAbstract
The rate of change in atmospheric CO2 is significantly affected by the terrestrial carbon sink, but the size and spatial distribution of this sink, and the extent to which it can be enhanced to mitigate climate change are highly uncertain. We combined carbon stock (CS) and eddy covariance (EC) flux measurements that were collected over a period of 15 years (2001–2016) in a 55 year old 30 km2 pine forest growing at the semiarid timberline (with no irrigating or fertilization). The objective was to constrain estimates of the carbon (C) storage potential in forest plantations in such semiarid lands, which cover 18% of the global land area. The forest accumulated 145–160 g C m−2 year−1 over the study period based on the EC and CS approaches, with a mean value of 152.5 ± 30.1 g C m−2 year−1 indicating 20% uncertainty in carbon uptake estimates. Current total stocks are estimated at 7,943 ± 323 g C/m2 and 372 g N/m2. Carbon accumulated mostly in the soil ( 71% and 29% for soil and standing biomass carbon, respectively) with long soil carbon turnover time (59 years). Regardless of unexpected disturbances beyond those already observed at the study site, the results support a considerable carbon sink potential in semiarid soils and forest plantations, and imply that afforestation of even 10% of semiarid land area under conditions similar to that of the study site, could sequester 0.4 Pg C/year over several decades. © 2019 John Wiley & Sons Ltd
The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)
. Methods in Ecology and Evolution 2019
. Publisher's VersionAbstract
Climate change is a world-wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high-quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re-use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. To overcome these challenges, we collected best-practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re-use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re-use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second-order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's needs in a changing world. © 2019 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
Assessment of maize yield and phenology by drone-mounted superspectral camera
. Precision Agriculture 2019
. Publisher's VersionAbstract
The capability of unmanned aerial vehicle (UAV) spectral imagery to assess maize yield under full and deficit irrigation is demonstrated by a Tetracam MiniMCA12 11 bands camera. The MiniMCA12 was used to image an experimental field of 19 maize hybrids. Yield prediction models were explored for different maize development stages, with the best model found using maize plant development stage reproductive 2 (R2) for both maize grain yield and ear weight (respective R 2 values of 0.73 and 0.49, and root mean square error of validation (RMSEV) values of 2.07 and 3.41 metric tons per hectare using partial least squares regression (PLS-R) validation models). Models using vegetation indices for inputs rather than superspectral data showed similar R 2 but higher RMSEV values, and produced best results for the R4 development stage. In addition to being able to predict yield, spectral models were able to distinguish between different development stages and irrigation treatments. These abilities potentially allow for yield prediction of maize plants whose development stage and water status are unknown. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
Convolutional network architectures for super-resolution/sub-pixel mapping of drone-derived images
. Pattern Recognition 2019
, 431-446. Publisher's VersionAbstract
Spatial resolution enhancement is a pre-requisite for integrating unmanned aerial vehicle (UAV) datasets with the data from other sources. However, the mobility of UAV platforms, along with radiometric and atmospheric distortions, makes the task difficult. In this paper, various convolutional neural network (CNN) architectures are explored for resolving the issues related to sub-pixel classification and super-resolution of drone-derived datasets. The main contributions of this work are: 1) network-inversion based architectures for super-resolution and sub-pixel mapping of drone-derived images taking into account their spectral-spatial characteristics and the distortions prevalent in them 2) a feature-guided transformation for regularizing the inversion problem 3) loss functions for improving the spectral fidelity and inter-label compatibility of coarser to finer-scale mapping 4) use of multi-size kernel units for avoiding over-fitting. The proposed approach is the first of its kind in using neural network inversion for super-resolution and sub-pixel mapping. Experiments indicate that the proposed super-resolution approach gives better results in comparison with the sparse-code based approaches which generally result in corrupted dictionaries and sparse codes for multispectral aerial images. Also, the proposed use of neural network inversion, for projecting spatial affinities to sub-pixel maps, facilitates the consideration of coarser-scale texture and color information in modeling the finer-scale spatial-correlation. The simultaneous consideration of spectral bands, as proposed in this study, gives better super-resolution results when compared to the individual band enhancements. The proposed use of different data-augmentation strategies, for emulating the distortions, improves the generalization capability of the framework. Sensitivity of the proposed super-resolution and sub-pixel mapping frameworks with regard to the network parameters is thoroughly analyzed. The experiments over various standard datasets as well as those collected from known locations indicate that the proposed frameworks perform better when compared to the prominent published approaches. © 2018 Elsevier Ltd
Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning
. Plant Science 2019
. Publisher's VersionAbstract
Understanding plant disease resistance is important in the integrated management of Phytophthora infestans, causal agent of potato late blight. Advanced field-based methods of disease detection that can identify infection before the onset of visual symptoms would improve management by greatly reducing disease potential and spread as well as improve both the financial and environmental sustainability of potato farms. In-vivo foliar spectroscopy offers the capacity to rapidly and non-destructively characterize plant physiological status, which can be used to detect the effects of necrotizing pathogens on plant condition prior to the appearance of visual symptoms. Here, we tested differences in spectral response of four potato cultivars, including two cultivars with a shared genotypic background except for a single copy of a resistance gene, to inoculation with Phytophthora infestans clonal lineage US-23 using three statistical approaches: random forest discrimination (RF), partial least squares discrimination analysis (PLS-DA), and normalized difference spectral index (NDSI). We find that cultivar, or plant genotype, has a significant impact on spectral reflectance of plants undergoing P. infestans infection. The spectral response of four potato cultivars to infection by Phytophthora infestans clonal lineage US-23 was highly variable, yet with important shared characteristics that facilitated discrimination. Early disease physiology was found to be variable across cultivars as well using non-destructively derived PLS-regression trait models. This work lays the foundation to better understand host-pathogen interactions across a variety of genotypic backgrounds, and establishes that host genotype has a significant impact on spectral reflectance, and hence on biochemical and physiological traits, of plants undergoing pathogen infection. © 2019 Elsevier B.V.