The Arabidopsis (Arabidopsis thaliana) leaf veins bundle-sheath cells (BSCs)—a selective barrier to water and solutes entering the mesophyll—increase the leaf radial hydraulic conductance (Kleaf) by acidifying the xylem sap by their plasma membrane H+-ATPase, AHA2. Based on this and on the BSCs’ expression of phototropins PHOT1 and PHOT2, and the known blue light (BL)-induced Kleaf increase, we hypothesized that, resembling the guard cells, BL perception by the BSCs’ phots activates its H+-ATPase, which, consequently, upregulates Kleaf. Indeed, under BL, the Kleaf of the knockout mutant lines phot1-5, phot2-1, phot1-5 phot2-1, and aha2-4 was lower than that of the wild-type (WT). BSC-only-directed complementation of phot1-5 or aha2-4 by PHOT1 or AHA2, respectively, restored the BL-induced Kleaf increase. BSC-specific silencing of PHOT1 or PHOT2 prevented such Kleaf increase. A xylem-fed kinase inhibitor (tyrphostin 9) replicated this also in WT plants. White light—ineffective in the phot1-5 mutant—acidified the xylem sap (relative to darkness) in WT and in the PHOT1-complemented phot1-5. These results, supported by BL increase of BSC protoplasts’ water permeability and cytosolic pH and their hyperpolarization by BL, identify the BSCs as a second phot-controlled water conductance element in leaves, in series with stomatal conductance. Through both, BL regulates the leaf water balance.

Cellulose nanocrystals (CNCs) are composed of chiral cellulose units, which form chiral nematic liquid crystals in water that, upon drying, self-assemble to more complex spiral chiral sheets. This secondary structure arrangement is found to change with an external magnetic or electric field. Here, we show that one of the basic organization driving forces is electron spin, which is produced as the charge redistributes in the organization process of the chiral building blocks. It is important to stress that the electron spin-exchange interactions supply the original driving force and not the magnetic field per se. The results present the first utilization of the chiral-induced spin selectivity (CISS) effect in sugars, enabling one to regulate the CNC bottom-up fabrication process. Control is demonstrated on the organization order of the CNC by utilizing different magnetization directions of the ferromagnetic surface. The produced spin is probed using a simple Hall device. The measured Hall resistance shows that the CNC sheets’ arrangement is affected during the first four hours as long as the CNC is in its wet phase. On introducing the 1,2,3,4-butanetetracarboxylic acid cross-linker into the CNC sheet, the packing density of the CNC helical structure is enhanced, presenting an increase in the Hall resistance and the chiral state.Cellulose nanocrystals (CNCs) are composed of chiral cellulose units, which form chiral nematic liquid crystals in water that, upon drying, self-assemble to more complex spiral chiral sheets. This secondary structure arrangement is found to change with an external magnetic or electric field. Here, we show that one of the basic organization driving forces is electron spin, which is produced as the charge redistributes in the organization process of the chiral building blocks. It is important to stress that the electron spin-exchange interactions supply the original driving force and not the magnetic field per se. The results present the first utilization of the chiral-induced spin selectivity (CISS) effect in sugars, enabling one to regulate the CNC bottom-up fabrication process. Control is demonstrated on the organization order of the CNC by utilizing different magnetization directions of the ferromagnetic surface. The produced spin is probed using a simple Hall device. The measured Hall resistance shows that the CNC sheets’ arrangement is affected during the first four hours as long as the CNC is in its wet phase. On introducing the 1,2,3,4-butanetetracarboxylic acid cross-linker into the CNC sheet, the packing density of the CNC helical structure is enhanced, presenting an increase in the Hall resistance and the chiral state.

Litchi is a highly perishable fruit. Ripe litchi fruit loses quality quickly as they hang on tree, giving a very short hanging life and thus harvest period. This study attempted to explore the roles of cytokinin in regulating fruit ripening and senescence of litchi and examine the possibility of applying cytokinin in “on-tree storage” of the fruit. Exogenous cytokinin, forchlorfenuron (CPPU), was applied at 20 mg L⁻¹ 7 weeks after full bloom on litchi (Litchi chinensis cv. Feizixiao) fruit clusters. Color parameters, chlorophylls, anthocyanins, fruit and fruit part weights, total soluble solutes (TSSs), soluble sugars, organic acids, non-anthocyanin flavonoids, ethanol, and also CPPU residue in fruit were traced. CPPU residue was higher but decreased faster in the pericarp than in the aril, where it maintained < 10 μg kg⁻¹. CPPU had no significant effect on fruit weight but tended to increase pericarp weight. The treatment suppressed chlorophyll loss and anthocyanin accumulation in the pericarp, increased non-anthocyanin flavonoids in the aril, but had no significant effects on non-anthocyanin flavonoids in the pericarp and total sugar and organic acids in the aril. As the commercially ripe fruit hanged on tree, TSSs, total sugar, and sucrose decreased with ethanol and acetic acid accumulation in the aril. CPPU significantly suppressed the loss of sucrose and total sugar and the accumulation of ethanol and acetic acid in the aril and inhibited malondialdehyde accumulation in the pericarp of the overripe fruit. Soluble invertase, alcohol dehydrogenase, and pyruvate decarboxylase (PDC) activity and gene expression in the aril were downregulated by CPPU. The results suggest that cytokinin partially suppresses the ripening process in litchi and is effective to slow quality loss in the overripe fruit on tree.

A comprehensive collection of 1254 tomato accessions, corresponding to European traditional and modern varieties, early domesticated varieties, and wild relatives, was analyzed by genotyping by sequencing. A continuous genetic gradient between the traditional and modern varieties was observed. European traditional tomatoes displayed very low genetic diversity, with only 298 polymorphic loci (95% threshold) out of 64 943 total variants. European traditional tomatoes could be classified into several genetic groups. Two main clusters consisting of Spanish and Italian accessions showed higher genetic diversity than the remaining varieties, suggesting that these regions might be independent secondary centers of diversity with a different history. Other varieties seem to be the result of a more recent complex pattern of migrations and hybridizations among the European regions. Several polymorphic loci were associated in a genome-wide association study with fruit morphological traits in the European traditional collection. The corresponding alleles were found to contribute to the distinctive phenotypic characteristic of the genetic varietal groups. The few highly polymorphic loci associated with morphological traits in an otherwise a low-diversity population suggests a history of balancing selection, in which tomato farmers likely maintained the morphological variation by inadvertently applying a high selective pressure within different varietal types.

Nutrient enrichment of natural ecosystems is a primary characteristic of the Anthropocene and a known cause of biodiversity loss, particularly in grasslands. In a global meta-analysis of 630 resource addition experiments, we conduct a simultaneous test of the three most prominent explanations of this phenomenon. Our results conclusively indicate that nitrogen is the leading cause of species loss. This result is important because of the increase in nitrogen deposition and the frequent use of nitrogen-based fertilizers worldwide. Our findings provide global-scale, experimental evidence that minimizing nitrogen inputs to ecological systems may help to conserve the diversity of grassland ecosystems. Eutrophication is a major driver of species loss in plant communities worldwide. However, the underlying mechanisms of this phenomenon are controversial. Previous studies have raised three main explanations: 1) High levels of soil resources increase standing biomass, thereby intensifying competitive interactions (the “biomass-driven competition hypothesis”). 2) High levels of soil resources reduce the potential for resource-based niche partitioning (the “niche dimension hypothesis”). 3) Increasing soil nitrogen causes stress by changing the abiotic or biotic conditions (the “nitrogen detriment hypothesis”). Despite several syntheses of resource addition experiments, so far, no study has tested all of the hypotheses together. This is a major shortcoming, since the mechanisms underlying the three hypotheses are not independent. Here, we conduct a simultaneous test of the three hypotheses by integrating data from 630 resource addition experiments located in 99 sites worldwide. Our results provide strong support for the nitrogen detriment hypothesis, weaker support for the biomass-driven competition hypothesis, and negligible support for the niche dimension hypothesis. The results further show that the indirect effect of nitrogen through its effect on biomass is minor compared to its direct effect and is much larger than that of all other resources (phosphorus, potassium, and water). Thus, we conclude that nitrogen-specific mechanisms are more important than biomass or niche dimensionality as drivers of species loss under high levels of soil resources. This conclusion is highly relevant for future attempts to reduce biodiversity loss caused by global eutrophication.

The distribution and stability of biomes are critical for understanding, modeling, and managing the land biosphere. While studies have emphasized abiotic factors such as climate, geology, or fire regimes, we here identify a biological mechanism—plant–plant competition for belowground resources—as critical for maintaining the boundary between the Fynbos and Afrotemperate Forest biomes in South Africa. We demonstrate an apparent general mechanism in which local competition triggers a biome-scale feedback between plant traits and soil resources, which, in turn, stabilizes the biome boundary by allowing plants to maintain their own preferred soil conditions. Our findings are of general importance for understanding the organization of biodiversity across landscapes, for managing alien plant invasions, and for modeling the future of biome boundaries. Recent findings point to plant root traits as potentially important for shaping the boundaries of biomes and for maintaining the plant communities within. We examined two hypotheses: 1) Thin-rooted plant strategies might be favored in biomes with low soil resources; and 2) these strategies may act, along with fire, to maintain the sharp boundary between the Fynbos and Afrotemperate Forest biomes in South Africa. These biomes differ in biodiversity, plant traits, and physiognomy, yet exist as alternative stable states on the same geological substrate and in the same climate conditions. We conducted a 4-y field experiment to examine the ability of Forest species to invade the Fynbos as a function of growth-limiting nutrients and belowground plant–plant competition. Our results support both hypotheses: First, we found marked biome differences in root traits, with Fynbos species exhibiting the thinnest roots reported from any biome worldwide. Second, our field manipulation demonstrated that intense belowground competition inhibits the ability of Forest species to invade Fynbos. Nitrogen was unexpectedly the resource that determined competitive outcome, despite the long-standing expectation that Fynbos is severely phosphorus constrained. These findings identify a trait-by-resource feedback mechanism, in which most species possess adaptive traits that modify soil resources in favor of their own survival while deterring invading species. Our findings challenge the long-held notion that biome boundaries depend primarily on external abiotic constraints and, instead, identify an internal biotic mechanism—a selective feedback among traits, plant–plant competition, and ecosystem conditions—that, along with contrasting fire regime, can act to maintain biome boundaries.

Wood warping is a phenomenon known as a deformation in wood that occurs when changes in moisture content cause an unevenly volumetric change due to fiber orientation. Here we present an investigation of wood warped objects that were fabricated by 3D printing. Similar to natural wood warping, water evaporation causes volume decrease of the printed object, but in contrast, the printing pathway pattern and flow rate dictate the direction of the alignment and its intensity, all of which can be predesigned and affect the resulting structure after drying. The fabrication of the objects was performed by an extrusion-based 3D printing technique that enables the deposition of water-based inks into 3D objects. The printing ink was composed of 100% wood-based materials, wood flour, and plant-extracted natural binders cellulose nanocrystals, and xyloglucan, without the need for any additional synthetic resins. Two archetypal structures were printed: cylindrical structure and helices. In the former, we identified a new length scale that gauges the effect of gravity on the shape. In the latter, the structure exhibited a shape transition analogous to the opening of a seedpod, quantitatively reproducing theoretical predictions. Together, by carefully tuning the flow rate and printing pathway, the morphology of the fully dried wooden objects can be controlled. Hence, it is possible to design the printing of wet objects that will form different final 3D structures.

Earliness and ripening behavior are important attributes of fruits on and off the vine, and affect quality and preference of both growers and consumers. Fruit ripening is a complex physiological process that involves metabolic shifts affecting fruit color, firmness, and aroma production. Melon is a promising model crop for the study of fruit ripening, as the full spectrum of climacteric behavior is represented across the natural variation. Using Recombinant Inbred Lines (RILs) population derived from the parental lines “Dulce” (reticulatus, climacteric) and “Tam Dew” (inodorus, non-climacteric) that vary in earliness and ripening traits, we mapped QTLs for ethylene emission, fruit firmness and days to flowering and maturity. To further annotate the main QTL intervals and identify candidate genes, we used Oxford Nanopore long-read sequencing in combination with Illumina short-read resequencing, to assemble the parental genomes de-novo. In addition to 2.5 million genome-wide SNPs and short InDels detected between the parents, we also highlight here the structural variation between these lines and the reference melon genome. Through systematic multi-layered prioritization process, we identified 18 potential polymorphisms in candidate genes within multi-trait QTLs. The associations of selected SNPs with earliness and ripening traits were further validated across a panel of 177 diverse melon accessions and across a diallel population of 190 F1 hybrids derived from a core subset of 20 diverse parents. The combination of advanced genomic tools with diverse germplasm and targeted mapping populations is demonstrated as a way to leverage forward genetics strategies to dissect complex horticulturally important traits.

Abstract Domestication is considered as a model of adaptation which can be used to draw conclusions about the modus operandi of selection in natural systems. Investigating domestication may give insights on how plants react to different intensities of human manipulation, which has direct implication for the ongoing efforts of crop improvement. Therefore, scientists of various disciplines study domestication related questions to understand its biological and cultural bases. We employed RAD-sequencing of 494 pea samples from all wild and domesticated groups to analyse the collection’s genetic structure. Patterns of ancient admixture were investigated by analysis of admixture graphs. We used two complementary approaches, one diversity based and one based on differentiation, to detect selection signatures putatively associated with domestication. Analysis of subpopulation structure of wild Pisum sativum exposed five distinct groups with a notable geographic pattern. Pisum abyssinicum clustered unequivocally within the P. sativum complex without indication for a hybrid origin. We detected 32 genomic regions putatively subjected to selection, 29 in P. sativum ssp. sativum and three in P. abyssinicum. The two domesticated groups did not share regions under selection and did not display similar haplotype patterns within those regions. Wild Pisum sativum is structured into well diverged subgroups. While P. s. ssp. humile is not supported as a taxonomic entity, the so-called 'southern humile' is a genuine wild group. Introgression did not shape the variation observed within the sampled germplam. The two cultivated pea groups display distinct genetic bases of domestication, suggesting two genetically independent domestication events.

To address the challenge of predicting tomato yields in the field, we used whole-plant functional phenotyping to evaluate water relations under well-irrigated and drought conditions. The genotypes tested are known to exhibit variability in their yields in wet and dry fields. The examined lines included two lines with recessive mutations that affect carotenoid biosynthesis, zeta z2083 and tangerine t3406, both isogenic to the processing tomato variety M82. The two mutant lines were reciprocally grafted onto M82, and multiple physiological characteristics were measured continuously, before, during and after drought treatment in the greenhouse. A comparative analysis of greenhouse and field yields showed that the whole-canopy stomatal conductance (gsc) in the morning and cumulative transpiration (CT) were strongly correlated with field measurements of total yield (TY: r2 = 0.9 and 0.77, respectively) and plant vegetative weight (PW: r2 = 0.6 and 0.94, respectively). Furthermore, the minimum CT during drought and the rate of recovery when irrigation was resumed were both found to predict resilience.

Water availability in vineyards varies in space and time. The spatiotemporal variability of water availability to vines is affected by terrain, meteorology, and irrigation. This study aimed to analyze the response of vegetative and reproductive attributes of vines to spatiotemporal variability in water availability. We quantified the spatial autocorrelation of terrain covariates and grapevine attributes and determined the relative influence (RI) of the covariates on these attributes. In each of four growing seasons (2017-2020), in a Vitis vinifera cv. ``Sauvignon Blanc'' vineyard, five vegetative and reproductive attributes were collected for 240 vines. Terrain covariates included elevation, slope, aspect, topographic wetness index, and categorical landforms; and meteorological covariates consisted of annual rainfall and chilling hours. A Moran's I statistic was computed for each spatial covariate and each grapevine attribute during each season to define temporal changes in spatial variability. A multivariate analysis using gradient boosted regression trees algorithm was applied to extract the RI of the covariates. The results showed high spatial autocorrelation of the terrain covariates and a strong negative shift in spatial dependency of the grapevine attributes throughout the experiment. Yield and number of clusters per vine were highly affected by seasonal precipitation (RI of 46.15% and 42.59%), while changes in inter-seasonal cluster weight and pruning weight were highly subjected to irrigation amounts (RI of 23% and 26.66%), with complementary terrain influences. The number of canes per vine was mainly affected by terrain characteristics. Long-term changes in grapevine attributes depended on meteorological shifts, while higher precipitation amounts were associated with weaker responses of vines to irrigation strategies. The spatial patterns of terrain affected water distribution in the vineyard and controlled the spatial dynamics of grapevine attributes. Knowledge regarding the space-time trends of water availability effects on grapevine attributes may assist decision making of irrigation practices in vineyards.

Multiple and heterogenous Earth observation (EO) platforms are broadly used for a wide array of applications, and the integration of these diverse modalities facilitates better extraction of information than using them individually. The detection capability of the multispectral unmanned aerial vehicle (UAV) and satellite imagery can be significantly improved by fusing with ground hyperspectral data. However, variability in spatial and spectral resolution can affect the efficiency of such dataset's fusion. In this study, to address the modality bias, the input data was projected to a shared latent space using cross-modal generative approaches or guided unsupervised transformation. The proposed adversarial networks and variational encoder-based strategies used bi-directional transformations to model the cross-domain correlation without using cross-domain correspondence. It may be noted that an interpolation-based convolution was adopted instead of the normal convolution for learning the features of the point spectral data (ground spectra). The proposed generative adversarial network-based approach employed dynamic time wrapping based layers along with a cyclic consistency constraint to use the minimal number of unlabeled samples, having cross-domain correlation, to compute a cross-modal generative latent space. The proposed variational encoder-based transformation also addressed the cross-modal resolution differences and limited availability of cross-domain samples by using a mixture of expert-based strategy, cross-domain constraints, and adversarial learning. In addition, the latent space was modelled to be composed of modality independent and modality dependent spaces, thereby further reducing the requirement of training samples and addressing the cross-modality biases. An unsupervised covariance guided transformation was also proposed to transform the labelled samples without using cross-domain correlation prior. The proposed latent space transformation approaches resolved the requirement of cross-domain samples which has been a critical issue with the fusion of multi-modal Earth observation data. This study also proposed a latent graph generation and graph convolutional approach to predict the labels resolving the domain discrepancy and cross-modality biases. Based on the experiments over different standard benchmark airborne datasets and real-world UAV datasets, the developed approaches outperformed the prominent hyperspectral panchromatic sharpening, image fusion, and domain adaptation approaches. By using specific constraints and regularizations, the network developed was less sensitive to network parameters, unlike in similar implementations. The proposed approach illustrated improved generalizability in comparison with the prominent existing approaches. In addition to the fusion-based classification of the multispectral and hyperspectral datasets, the proposed approach was extended to the classification of hyperspectral airborne datasets where the latent graph generation and convolution were employed to resolve the domain bias with a small number of training samples. Overall, the developed transformations and architectures will be useful for the semantic interpretation and analysis of multimodal data and are applicable to signal processing, manifold learning, video analysis, data mining, and time series analysis, to name a few.