Summary Steroidal glycoalkaloids (SGAs) are protective metabolites constitutively produced by Solanaceae species. Genes and enzymes generating the vast structural diversity of SGAs have been largely identified. Yet, mechanisms of hormone pathways coordinating defence (jasmonate; JA) and growth (gibberellin; GA) controlling SGAs metabolism remain unclear. We used tomato to decipher the hormonal regulation of SGAs metabolism during growth vs defence tradeoff. This was performed by genetic and biochemical characterisation of different JA and GA pathways components, coupled with in vitro experiments to elucidate the crosstalk between these hormone pathways mediating SGAs metabolism. We discovered that reduced active JA results in decreased SGA production, while low levels of GA or its receptor led to elevated SGA accumulation. We showed that MYC1 and MYC2 transcription factors mediate the JA/GA crosstalk by transcriptional activation of SGA biosynthesis and GA catabolism genes. Furthermore, MYC1 and MYC2 transcriptionally regulate the GA signalling suppressor DELLA that by itself interferes in JA-mediated SGA control by modulating MYC activity through protein–protein interaction. Chemical and fungal pathogen treatments reinforced the concept of JA/GA crosstalk during SGA metabolism. These findings revealed the mechanism of JA/GA interplay in SGA biosynthesis to balance the cost of chemical defence with growth.

The plant hormone abscisic acid (ABA) plays a central role in the regulation of seed maturation and dormancy. ABA also restrains germination under abiotic-stress conditions. Here, we show in tomato (Solanum lycopersicum) that the ABA importer ABA-IMPORTING TRANSPORTER 1.1 (AIT1.1/NPF4.6) has a role in radicle emergence under salinity conditions. AIT1.1 expression was upregulated following seed imbibition, and CRISPR/Cas9-derived ait1.1 mutants exhibited faster radicle emergence, increased germination and partial resistance to ABA. AIT1.1 was highly expressed in the endosperm, but not in the embryo, and ait1.1 isolated embryos did not show resistance to ABA. On the other hand, loss of AIT1.1 activity promoted the expression of endosperm-weakening-related genes, and seed-coat scarification eliminated the promoting effect of ait1.1 on radicle emergence. Therefore, we propose that imbibition-induced AIT1.1 expression in the micropylar endosperm mediates ABA-uptake into micropylar cells to restrain endosperm weakening. While salinity conditions strongly inhibited wild-type M82 seed germination, high salinity had a much weaker effect on ait1.1 germination. We suggest that AIT1.1 evolved to inhibit germination under unfavorable conditions, such as salinity. Unlike other ABA mutants, ait1.1 exhibited normal seed longevity, and therefore, the ait1.1 allele may be exploited to improve seed germination in crops.

Sesame is mainly cultivated under traditional, low-input agro-systems. Recent breeding developments promoted the modernization and mechanization of sesame cultivation. However, only a few articles have been published concerning fertilization requirements for both modern and traditional agro-systems. In field trials at two locations, we determined the response of irrigated sesame to nitrogen (N). Three promising sesame lines were tested combining two irrigation levels with four N levels. At a high irrigation level, N had a significant effect on growth, branching, and consequently, seed yield exceeding two-ton ha−1. A high N doze was accompanied by a decrease in the photosynthetic rate and leaf water potential. The δ13C confirmed lower stomatal conductance under high N treatments. Under deficit irrigation, the N level had a minor effect on the monitored parameters, indicating N fertilization was not efficient. Seed oil content was negatively correlated with seed N concentration. Our results question the necessity of N application when water is limited, as N fertilization promotes vigorous development that rapidly depletes soil water. Thus, water availability should be considered when developing an N management strategy. For high-yielding agro-systems, roughly 80–120 ​kg ​ha−1 N is required for optimal yield, bearing in mind the negative association between seed-N and oil content.

Sesame is an ancient oilseed crop containing many valuable nutritional components. Recently, the demand for sesame seeds and their products has increased worldwide, making it necessary to enhance the development of high-yielding cultivars. One approach to enhance genetic gain in breeding programs is genomic selection. However, studies on genomic selection and genomic prediction in sesame are limited. In this study, we performed genomic prediction for agronomic traits using the phenotypes and genotypes of a sesame diversity panel grown under Mediterranean climatic conditions over two growing seasons. We aimed to assess the accuracy of prediction for nine important agronomic traits in sesame using single- and multi-environment analyses. In single-environment analysis, genomic best linear unbiased prediction, BayesB, BayesC, and reproducing kernel Hilbert spaces models showed no substantial differences. The average prediction accuracy of the nine traits across these models ranged from 0.39-0.79 for both growing seasons. In the multi-environment analysis, the marker-by-environment interaction model, which decomposed the marker effects into components shared across environments and environment-specific deviations, improved the prediction accuracies for all traits by 15%\-58% compared to the single-environment model, particularly when borrowing information from other environments was made possible. Our results showed that single-environment analysis produced moderate-to-high genomic prediction accuracy for agronomic traits in sesame. The multi-environment analysis further enhanced this accuracy by exploiting marker-by-environment interaction. We concluded that genomic prediction using multi-environmental trial data could improve efforts for breeding cultivars adapted to the semi-arid Mediterranean climate.Competing Interest StatementThe authors have declared no competing interest.

Removal of the root system induces the formation of new roots from the remaining shoot. This process is primarily controlled by the phytohormone auxin, which interacts with other signals in a yet unresolved manner. Here, we study the classical tomato mutation rosette (ro), which lacks shoot-borne roots. ro plants were severely inhibited in forming wound-induced roots and have reduced auxin transport rates. We mapped ro to the tomato ortholog of the Arabidopsis thaliana BIG and the mammalians UBR4/p600. RO/BIG is a large protein of unknown biochemical function. In A. thaliana, BIG was implicated in regulating auxin transport and calcium homeostasis. We show that exogenous calcium inhibits wound-induced root formation in tomato and A. thaliana ro/big mutants. Exogenous calcium antagonized the root-promoting effects of the auxin IAA but not of 2,4-D, an auxin analog that is not recognized by the polar transport machinery, and accumulation of the auxin transporter PIN1 was sensitive to calcium levels in the ro/big mutants. Consistent with a role for calcium in mediating auxin transport, both ro/big mutants and calcium-treated wild-type plants were hypersensitive to treatment with polar auxin transport inhibitors. Subcellular localization of BIG suggests that, like its mammalian ortholog, it is associated with the endoplasmic reticulum (ER). Analysis of subcellular morphology revealed that ro/big mutants exhibited disruption in cytoplasmic streaming. We suggest that RO/BIG maintain auxin flow by stabilizing PIN membrane localization, possibly by attenuating the inhibitory effect of Ca2+ on cytoplasmic streaming.

Summary Plants have a broad capacity to regenerate damaged organs. The study of wounding in multiple developmental systems has uncovered many of the molecular properties underlying plants' competence for regeneration at the local cellular level. However, in nature, wounding is rarely localized to one place, and plants need to coordinate regeneration responses at multiple tissues with environmental conditions and their physiological state. Here, we review the evidence for systemic signals that regulate regeneration on a plant-wide level. We focus on the role of auxin and sugars as short‑ and long-range signals in natural wounding contexts and discuss the varied origin of these signals in different regeneration scenarios. Together, this evidence calls for a broader, system-wide view of plant regeneration competence.

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under short-term, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions.

Abstract Two opposing models currently dominate Near Eastern plant domestication research. The core area-one event model depicts a knowledge-based, conscious, geographically centered, rapid single-event domestication, while the protracted-autonomous model emphasizes a non-centered, millennia-long process based on unconscious dynamics. The latter model relies, in part, on quantitative depictions of diachronic changes (in archaeological remains) in proportions of spikelet shattering to non-shattering, towards full dominance of the non-shattering (domesticated) phenotypes in cultivated cereal populations. Recent wild wheat genome assembly suggests that shattering and non-shattering spikelets may originate from the same (individual) genotype. Therefore, their proportions among archaeobotanical assemblages cannot reliably describe the presumed protracted-selection dynamics underlying wheat domestication. This calls for a reappraisal of the ?domestication syndrome? concept associated with cereal domestication.

The yeast two-hybrid (Y2H) assay is widely used for protein–protein interaction characterization due to its simplicity and accessibility. However, it may mask changes in affinity caused by mutations or ligand activation due to signal saturation. To overcome this drawback, we modified the Y2H system to have tunable protein expression by introducing a fluorescent reporter and a pair of synthetic inducible transcription factors to regulate the expression of interacting components. We found that the application of inducers allowed us to adjust the concentrations of interacting proteins to avoid saturation and observe interactions otherwise masked in the canonical Y2H assay, such as the abscisic acid-mediated increase in affinity of monomeric abscisic acid receptors to the coreceptor. When applied in future studies, our modified system may provide a more accurate characterization of protein–protein interactions.The yeast two-hybrid (Y2H) assay is widely used for protein–protein interaction characterization due to its simplicity and accessibility. However, it may mask changes in affinity caused by mutations or ligand activation due to signal saturation. To overcome this drawback, we modified the Y2H system to have tunable protein expression by introducing a fluorescent reporter and a pair of synthetic inducible transcription factors to regulate the expression of interacting components. We found that the application of inducers allowed us to adjust the concentrations of interacting proteins to avoid saturation and observe interactions otherwise masked in the canonical Y2H assay, such as the abscisic acid-mediated increase in affinity of monomeric abscisic acid receptors to the coreceptor. When applied in future studies, our modified system may provide a more accurate characterization of protein–protein interactions.

Developing sensory modules for specific molecules of interest represents a fundamental challenge in synthetic biology and its applications. A somewhat generalizable approach for this challenge is demonstrated here by evolving a naturally occurring chemically induced heterodimer into a genetically encoded sensor for herbicides. The interaction between PYRABACTIN-RESISTANT-like receptors and type-2C protein phosphatases is induced by abscisic acid─a small-molecule hormone in plants. We considered abscisic acid receptors as a potential scaffold for the development of biosensors because of past successes in their engineering, a structurally defined ligand cavity and the availability of large-scale assays for their activation. A panel of 475 receptor variants, mutated at ligand-proximal residues, was screened for activation by 37 herbicides from several classes. Twelve compounds activated at least one member of the mutant panel. To facilitate the subsequent improvement of herbicide receptors through directed evolution, we engineered a yeast two-hybrid platform optimized for sequential positive and negative selection using fluorescence-activated cell sorting. By utilizing this system, we were able to isolate receptors with low nanomolar sensitivity and a broad dynamic range in sensing a ubiquitous group of chloroacetamide herbicides. Aside from its possible applicative value, this work lays down conceptual groundwork and provides infrastructure for the future development of biosensors through directed evolution.Developing sensory modules for specific molecules of interest represents a fundamental challenge in synthetic biology and its applications. A somewhat generalizable approach for this challenge is demonstrated here by evolving a naturally occurring chemically induced heterodimer into a genetically encoded sensor for herbicides. The interaction between PYRABACTIN-RESISTANT-like receptors and type-2C protein phosphatases is induced by abscisic acid─a small-molecule hormone in plants. We considered abscisic acid receptors as a potential scaffold for the development of biosensors because of past successes in their engineering, a structurally defined ligand cavity and the availability of large-scale assays for their activation. A panel of 475 receptor variants, mutated at ligand-proximal residues, was screened for activation by 37 herbicides from several classes. Twelve compounds activated at least one member of the mutant panel. To facilitate the subsequent improvement of herbicide receptors through directed evolution, we engineered a yeast two-hybrid platform optimized for sequential positive and negative selection using fluorescence-activated cell sorting. By utilizing this system, we were able to isolate receptors with low nanomolar sensitivity and a broad dynamic range in sensing a ubiquitous group of chloroacetamide herbicides. Aside from its possible applicative value, this work lays down conceptual groundwork and provides infrastructure for the future development of biosensors through directed evolution.

Responses of terrestrial ecosystems to climate change have been explored in many regions worldwide. While continued drying and warming may alter process rates and deteriorate the state and performance of ecosystems, it could also lead to more fundamental changes in the mechanisms governing ecosystem functioning. Here we argue that climate change will induce unprecedented shifts in these mechanisms in historically wetter climatic zones, towards mechanisms currently prevalent in dry regions, which we refer to as ‘dryland mechanisms’. We discuss 12 dryland mechanisms affecting multiple processes of ecosystem functioning, including vegetation development, water flow, energy budget, carbon and nutrient cycling, plant production and organic matter decomposition. We then examine mostly rare examples of the operation of these mechanisms in non-dryland regions where they have been considered irrelevant at present. Current and future climate trends could force microclimatic conditions across thresholds and lead to the emergence of dryland mechanisms and their increasing control over ecosystem functioning in many biomes on Earth.

Rosemary (Salvia rosmarinus (L.) Schleid., Handb. syn. Rosmarinus officinalis L.) extracts are widely used as natural preservatives due to their antimicrobial and antioxidant properties, which are attributed to the phenolic diterpenoid carnosic acid (CA). Growers are rewarded based on CA content in their rosemary leaf harvested. Conventional methods for estimating leaf CA content are destructive and often time-consuming. This preliminary study presents a spectral non-destructive approach for in vivo estimation of CA content in different rosemary cultivars based on the reflectance spectra of their canopy. The proposed approach is based on the characteristic rosemary absorption features along the visible and shortwave infrared spectral regions at 550 nm, 1200 nm, and 1690 nm, respectively, attributed to leaf color, the oxygen-hydrogen bond bending in water molecules, and distinctive carbon-hydrogen bond features typical for terpenes and phenolic compounds. Correlations between measured CA content by high-performance liquid chromatography (HPLC) and leaf reflectance spectra, normalized spectral indices, and latent components obtained by genetic algorithm-based partial least squares regression (GA-PLSR) were assessed using data collected from 79 rosemary cultivars. The GA-PLSR model successfully predicted the CA content among the various cultivars, further providing evidence of high weightage to the above-mentioned absorption features also obtained from two best-wavelength combination selections. Randomly selected canopy spectra were used to calibrate and simultaneously cross-validate 100 iterations, using the ‘leave-k-out’ approach. The root mean squared error (RMSE) obtained for calibration and cross-validation were 0.86% and 1.15% CA content from the dry leaf matter, and the residual prediction deviation (RPD) were reported to be 2.71 and 2.05, respectively. This work will set the stage for precise planning of harvesting time to ensure increased yield and income for the farmers and improved utilization of resources.

AbstractResource competition theory predicts coexistence and exclusion patterns based on species? R*s, the minimum resource values required for a species to persist. A central assumption of the theory is that all species have equal access to resources. However, many systems are characterized by preemption exploitation, where some species deplete resources before their competitors can access them (e.g., asymmetric light competition, contest competition among animals). We hypothesized that coexistence under preemption requires an R*-preemption trade-off?that is, the species with the priority access should have a higher R* (lower ?efficiency?). Thus, we developed an extension of resource competition theory to investigate partial and total preemption (in the latter, the preemptor is unaffected by species with lower preemption rank). We found that an R*-preemption trade-off is a necessary condition for coexistence in all models. Moreover, under total preemption, the trade-off alone is sufficient for coexistence. In contrast, under partial preemption, more conditions are needed, which restricts the parameter space of coexistence. Finally, we discuss the implications of our finding for seemingly distinct trade-offs, which we view as special cases of the R*-preemption trade-off. These trade-offs include the digger-grazer trade-off, the competition-colonization trade-off, and trade-offs related to light competition between trees and understories.AbstractResource competition theory predicts coexistence and exclusion patterns based on species? R*s, the minimum resource values required for a species to persist. A central assumption of the theory is that all species have equal access to resources. However, many systems are characterized by preemption exploitation, where some species deplete resources before their competitors can access them (e.g., asymmetric light competition, contest competition among animals). We hypothesized that coexistence under preemption requires an R*-preemption trade-off?that is, the species with the priority access should have a higher R* (lower ?efficiency?). Thus, we developed an extension of resource competition theory to investigate partial and total preemption (in the latter, the preemptor is unaffected by species with lower preemption rank). We found that an R*-preemption trade-off is a necessary condition for coexistence in all models. Moreover, under total preemption, the trade-off alone is sufficient for coexistence. In contrast, under partial preemption, more conditions are needed, which restricts the parameter space of coexistence. Finally, we discuss the implications of our finding for seemingly distinct trade-offs, which we view as special cases of the R*-preemption trade-off. These trade-offs include the digger-grazer trade-off, the competition-colonization trade-off, and trade-offs related to light competition between trees and understories.

The bidirectional reflectance distribution function (BRDF) is crucial in determining the quantity of reflected light on the earth’s surface as a function of solar and view angles (i.e., azimuth and zenith angles). The Vegetation and ENvironment monitoring Micro-Satellite (VENµS) provides a unique opportunity to acquire data from the same site, with the same sensor, with almost constant solar and view zenith angles from two (or more) view azimuth angles. The present study was aimed at exploring the view angles’ effect on the stability of the values of albedo and of two vegetation indices (VIs): the normalized difference vegetation index (NDVI) and the red-edge inflection point (REIP). These products were calculated over three polygons representing urban and cultivated areas in April, June, and September 2018, under a minimal time difference of less than two minutes. Arithmetic differences of VIs and a change vector analysis (CVA) were performed. The results show that in urban areas, there was no difference between the VIs, whereas in the well-developed field crop canopy, the REIP was less affected by the view azimuth angle than the NDVI. Results suggest that REIP is a more appropriate index than NDVI for field crop studies and monitoring. This conclusion can be applied in a constellation of satellites that monitor ground features simultaneously but from different view azimuth angles.

To meet the ever-growing global population necessities, integrating climate-change-relevant plant traits into breeding programs is required. Developing new tools for fast and accurate estimation of chlorophyll parameters, chlorophyll a (Chl-a) content, chlorophyll b (Chl-b) content, and their ratio (Chl-a/b), can promote breeding programs of wheat with enhanced climate adaptability. Spectral reflectance of leaves is affected by changes in pigment concentration and can be used to estimate chlorophyll parameters. The current study identified and validated the top known spectral indices and developed new vegetation indices (VIs) for Chl-a and Chl-b content estimation and used them to non-destructively estimate Chl-a/b values and compare them to hyperspectral estimations. Three wild emmer introgression lines, with contrasting drought stress responsiveness dynamics, were selected. Well-watered and water-limited irrigation regimes were applied. The wheat leaves were spectrally measured with a handheld spectrometer to acquire their reflectance in the 330 to 790 nm range. Regression models based on calculated VIs as well as all hyperspectral curves were calibrated and validated against chlorophyll extracted values. The developed normalized difference spectral indices (NDSIs) resulted in high accuracy of Chl-a (NDSI415,614) and Chl-b (NDSI406,525) estimation, allowing for indirect non-destructive estimation of Chl-a/b with root mean square error (RMSE) values that could fit 6 to 10 times in the range of the measured values. They also performed similarly to the hyperspectral models. Altogether, we present here a new tool for a non-destructive estimation of Chl-a/b, which can serve as a basis for future breeding efforts of climate-resilient wheat as well as other crops.

Drought intensity as experienced by plants depends upon soil moisture status and atmospheric variables such as temperature, radiation, and air vapour pressure deficit. Although the role of shoot architecture with these edaphic and atmospheric factors is well characterized, the extent to which shoot and root dynamic interactions as a continuum are controlled by genotypic variation is less well known. Here, we targeted these interactions using a wild emmer wheat introgression line (IL20) with a distinct drought-induced shift in the shoot-to-root ratio and its drought-sensitive recurrent parent Svevo. Using a gravimetric platform, we show that IL20 maintained higher root water influx and gas exchange under drought stress, which supported a greater growth. Interestingly, the advantage of IL20 in root water influx and transpiration was expressed earlier during the daily diurnal cycle under lower vapour pressure deficit and therefore supported higher transpiration efficiency. Application of a structural equation model indicates that under drought, vapour pressure deficit and radiation are antagonistic to transpiration rate, whereas the root water influx operates as a feedback for the higher atmospheric responsiveness of leaves. Collectively, our results suggest that a drought-induced shift in root-to-shoot ratio can improve plant water uptake potential in a short preferable time window during early morning when vapour pressure deficit is low and the light intensity is not a limiting factor for assimilation.

Hydrated silica (SiO2·nH2O) aggregates in the root endodermis of grasses. Application of soluble silicates (Si) to roots is associated with variations in the balance of reactive oxygen species (ROS), increased tolerance to a broad range of stresses affecting ROS concentrations, and early lignin deposition. In sorghum (Sorghum bicolor L.), silica aggregation is patterned in an active silicification zone (ASZ) by a special type of aromatic material forming a spotted pattern. The deposition has a signature typical of lignin. Since lignin polymerization is mediated by ROS, we studied the formation of root lignin and silica controlled by ROS via modulating hydrogen peroxide (H2O2) concentrations in the growth medium. Sorghum seedlings were grown hydroponically and supplemented with Si, H2O2, and KI, an ionic compound that catalyses H2O2 decomposition. Lignin and silica deposits in the endodermis were studied by histology, scanning electron and Raman microscopies. Cell wall composition was quantified by thermal gravimetric analysis. Endodermal H2O2 concentration correlated to the extent of lignin-like deposition along the root, but did not affect its patterning in spots. Our results show that the ASZ spots were necessary for root silica aggregation, and suggest that silicification is intensified under oxidative stress as a result of increased ASZ lignin-like deposition.

Author summary Plants form organs continuously throughout their lives, and the number and shape of their organs is determined in a flexible manner according to the internal and external circumstances. Alongside this flexibility, plants maintain basic developmental programs to ensure proper functioning. Among the ways by which plants achieve flexible development is by tuning the pace of their maturation and differentiation, at both the plant and organ levels. One of the ways plants regulate the rate of maturation and differentiation is by changing gene expression. Here, we identified a gene that promotes plant and organ maturation and differentiation. This gene, CRAWLING ELEPHANT (CREL) acts by bringing a repressing complex to target genes. We show the importance of CREL in multiple developmental processes and in the expression of multiple genes throughout the tomato genome.

A major gene controls flowering pattern in peanut, possibly encoding a TFL1-like. It was subjected to gain/loss events of a deletion and changes in mRNA expression levels, partly explaining the evolution of flowering pattern in Arachis.

Grapevines are susceptible and responsive to their surrounding environment. Factors such as climate region and terroir are known to affect polyphenolic compounds in wine and therefore, its quality. The uniqueness of the terroir in Israel is the variety of soil types and the climatic conditions, ranging from Mediterranean to arid climates. Thus, understanding the effects of climate on grapevine performance in Israel may be a test case for the effect of climate change on grapevine at other areas in the future. First, we present a preliminary survey (2012–2014) in different climate zones and terroirs, which showed that trans-resveratrol concentrations in Merlot and Shiraz were high, while those of Cabernet Sauvignon were significantly lower. A further comprehensive countrywide survey (2016) of Merlot wines from 62 vineyards (53 wineries) compared several phenolic compounds’ concentrations between five areas of different climate and terroir. Results show a connection between trans-resveratrol concentrations, variety, and terroir properties. Furthermore, we show that trans-resveratrol concentrations are strongly correlated to humidity levels at springtime, precipitation, and soil permeability. This work can be considered a glimpse into the possible alterations of wine composition in currently moderate-climate wine-growing areas.