Plant Physiological Traits Research Articles

Effect of High-Temperature Stress on Plant Physiological Traits and Mycorrhizal Symbiosis in Maize Plants.

Increasing high temperature (HT) has a deleterious effect on plant growth. Earlier works reported the protective role of arbuscular mycorrhizal fungi (AMF) under stress conditions, particularly influencing the physiological parameters. However, the protective role of AMF under high-temperature stress examining physiological parameters with characteristic phospholipid fatty acids (PLFA) of soil microbial communities including AMF has not been studied. This work aims to study how high-temperature stress affects photosynthetic and below-ground traits in maize plants with and without AMF. Photosynthetic parameters like quantum yield of photosystem (PS) II, PSI, electron transport, and fractions of open reaction centers decreased in HT exposed plants, but recovered in AMF + HT plants. AMF + HT plants had significantly higher AM-signature 16:1ω5cis neutral lipid fatty acid (NLFA), spore density in soil, and root colonization with lower lipid peroxidation than non-mycorrhizal HT plants. As a result, enriched plants had more active living biomass, which improved photosynthetic efficiency when exposed to heat. This study provides an understanding of how AM-mediated plants can tolerate high temperatures while maintaining the stability of their photosynthetic apparatus. This is the first study to combine above- and below-ground traits, which could lead to a new understanding of plant and rhizosphere stress.

Detection of ozone stress in rice cultivars using spectral reflectance

Ozone stress identification in crops through remote sensing is a promising technology that has a major role in predicting stress-related physiological response. The spectral reflectance approach to phenotyping of rice cultivars is a non-destructive and accurate method to assess ozone stress. In this study, the leaf spectral reflectance of 15 rice cultivars was explored to evaluate the photosynthetic capacity under elevated ozone stress. Ozone injury percentage (OIP), a common indicator to identify ozone stress of rice leaves combined with leaf spectral signatures was used to identify the best fit spectral indices. The normalized difference spectral index (NDSI) was used to determine significant wavebands that showed the best correlation with leaf ozone injury. The correlation coefficient (r) between NDSI and OIP were ranged from -0.79 to 1. Normalized difference spectral index, NDSI[R564,R568], and NDSI[R558,R573] were identified as the best Pearson's correlation with leaf ozone injury percentage with correlation coefficient more than 0.96. The evaluated NDSI in visible regions were identified as a sensitive region to ozone injury. Additionally, results were compared with previously established indices and also evaluated for correlation with plant physiological traits. The correlation coefficient of determination (R2) > 0.5 was observed for newly developed spectral indices, NDSI[R564,R568] and NDSI[R558,R573] with physiological traits compared to previously established 20 indices. The highest R2 of 0.674 were observed for the spectral index, NDSI[R558,R573] with photosynthetic rate and R2 of 0.673 for NDSI[R564,R568] with relative chlorophyll content. As a result, the current research has implications for the selection of the best capable spectral regions for early detection of ozone stress in rice cultivars without destructing the crop. The outcome of the present work suggests that newly developed spectral indices could assist in remote sensing technology in monitoring large scale ozone stress and crop modeling studies to ensure food security.

Effect of lignosulfonate application to sandy soil on plant nutrition and physiological traits

The application of nutrient-rich substrates to soils characterized by low natural fertility is discussed as a strategy to improve soil fertility and, consequently, affect plant physiological traits. This study aimed to evaluate if sodium lignosulfonate (LS), a by-products of pulp and paper industry, may improve plant ecophysiological traits under contrasting nutrient conditions. A pot culture experiment was conducted with cucumber plants, using LS concentrations of 0, 1, 2.5, 5, and 10 vol.% in sandy soil, and two soil nutrient levels: sufficient and low nutrient availability (SNA and LNA, accordingly). The LS increased N and P content in SNA leaves when 1% of LS was used and decreased N content in LNA leaves regardless of soil LS content. The LS did reduce mass-, N-, and P-based respiration rates of the SNA leaves, and increased the N-based respiration rate under LNA. The LS did not have a significant impact on the ratio of respiration to photosynthesis in SNA leaves, but decreased it under LNA. The LS application contributed to a slight activation of some physiological processes in LNA plants, but it was not successful to recover these activities to the level of plants grown under SNA.

Shifts and plasticity of plant leaf mass per area and leaf size among slope aspects in a subalpine meadow.

The composition of vegetation on a slope frequently changes substantially owing to the different micro‐environments of various slope aspects. To understand how the slope aspect affects the vegetation changes, we examined the variations in leaf mass per area (LMA) and leaf size (LS) within and among populations for 66 species from 14 plots with a variety of slope aspects in a subalpine meadow. LMA is a leaf economic trait that is tightly correlated with plant physiological traits, while the LS shows a tight correlation with leaf temperature, indicating the strategy of plants to self‐adjust in different thermal and hydraulic conditions. In this study, we compared the two leaf traits between slope aspects and between functional types and explored their correlation with soil variables and heat load. Our results showed that high‐LMA, small‐leaved species were favored in south‐facing slopes, while the reverse was true in north‐facing areas. In detail, small dense‐leaved graminoids dominated the south slopes, while large thin‐leaved forbs dominated the north slopes. Soil moisture and the availability of soil P were the two most important soil factors that related to both LMA and LS, and heat load also contributed substantially. Moreover, we disentangled the relative importance of intraspecific trait variation and species turnover in the trait variation among plots and found that the intraspecific variation contributed 98% and 56% to LMA and LS variation among communities, respectively, implying a large contribution of intraspecific trait plasticity. These results indicate that LMA and LS are two essential leaf traits that affect the adaptation or acclimation of plants underlying the vegetation composition changes in different slope aspects in the subalpine meadow.

Responses of morphological and physiological traits to herbivory by snails of three invasive and native submerged plants

AbstractThe submerged plant species Carolina fanwort (Cabomba caroliniana) has become a dominant invasive aquatic plant in the Lake Taihu Basin (LTB) in China. Introduced species may escape their original specialist enemies and encounter fewer enemies in their new environment. They were assumed to have suffered less herbivory than native species as they are relatively unpalatable (the enemy release hypothesis [ERH]). The objective of this study was to compare the responses of C. caroliniana with those of co-occurring native species to herbivory from native herbivores. We conducted a mesocosm experiment to record the responses of C. caroliniana and two commonly co-occurring native submerged plant counterparts, water thyme (Hydrilla verticillata) and Eurasian watermilfoil (Myriophyllum spicatum), to herbivory by two native generalist gastropod snails, Radix swinhoei and Sinotaia quadrata. Plant morphological traits (total biomass, shoot/root [S/R] biomass ratio and relative growth rate [RGR]) and physiological traits (leaf total nonstructural carbohydrate [TNC], lignin, and cellulose) were recorded. The snail S. quadrata rarely influenced the plant traits of the three submerged plants. With the increasing numbers of R. swinhoei treatments, most of the plant traits of H. verticillata and M. spicatum changed, while those of C. caroliniana showed a relatively stable fluctuation. This result indicates that C. caroliniana is more resistant to herbivory by the snail R. swinhoei, which is consistent with the ERH hypothesis. This finding indicates that herbivorous snail species contributes to the invasion of C. caroliniana, which potentially alters the species composition of submerged plants in the plant community.

Cushion bog plant community responses to passive warming in southern Patagonia

Abstract. Vascular plant-dominated cushion bogs, which are exclusive to the Southern Hemisphere, are highly productive and constitute large sinks for atmospheric carbon dioxide compared to their moss-dominated counterparts around the globe. In this study, we experimentally investigated how a cushion bog plant community responded to elevated surface temperature conditions as they are predicted to occur in a future climate. We conducted the study in a cushion bog dominated by Astelia pumila on Tierra del Fuego, Argentina. We installed a year-round passive warming experiment using semicircular plastic walls that raised average near-surface air temperatures by between 0.4 and 0.7 ∘C (at the 3 of the 10 treatment plots which were equipped with temperature sensors). We focused on characterizing differences in morphological cushion plant traits and in carbon dioxide exchange dynamics using chamber gas flux measurements. We used a mechanistic modeling approach to quantify physiological plant traits and to partition the net carbon dioxide flux into its two components of photosynthesis and total ecosystem respiration. We found that A. pumila reduced its photosynthetic activity under elevated temperatures. At the same time, we observed enhanced respiration which we largely attribute, due to the limited effect of our passive warming on soil temperatures, to an increase in autotrophic respiration. Passively warmed A. pumila cushions sequestered between 55 % and 85 % less carbon dioxide than untreated control cushions over the main growing season. Our results suggest that even moderate future warming under the SSP1-2.6 scenario could decrease the carbon sink function of austral cushion bogs.

Drought stress introduces growth, physiological traits and ecological stoichiometry changes in two contrasting Cunninghamia lanceolata cultivars planted in continuous-plantation soils

BackgroundThe decrease in Cunninghamia lanceolata (Lamb.) production on continuously planted soil is an essential problem. In this study, two-year-old seedlings of two cultivars (a normal cultivar, NC, and a super cultivar, SC) were grown in two types of soil (not planted (NP) soil; continuously planted (CP) soil) with three watering regimes, and the interactive effects on plant growth and physiological traits were investigated in a greenhouse experiment. The water contents of the soil in the control (CK) (normal water content), medium water content (MWC) and low water content (LWC) treatments reached 75−80 %, 45−50 % and 20−25 % of the field water capacity, respectively.ResultsThe results indicated that the CP soil had a negative effect on growth and physiological traits and that the LWC treatment caused even more severe and comprehensive negative effects. In both cultivars, the CP soil significantly decreased the height increment (HI), basal diameter increment (DI), dry matter accumulation (DMA), net photosynthetic rate (Pn), total chlorophyll content (TChl), carotenoid content (Caro) and photosynthetic nitrogen use efficiency (PNUE). Compared to the NP soil, the CP soil also decreased the proline and soluble protein contents, nitrogen use efficiency (NUE) and phosphorus use efficiency (PUE) and increased the nitrogen:phosphorus ratio in roots, stems and leaves. The LWC treatment decreased growth and photosynthesis, changed ecological stoichiometry, induced oxidative stress, promoted water use efficiency and damaged chloroplast ultrastructure. Significant increases in ascorbate peroxidase (APX), peroxidase (POD), soluble protein and proline contents were found in the LWC treatment. Compared with the NC, the SC was more tolerant to the CP soil and water stress, as indicated by the higher levels of DMA, Pn, and WUE. After exposure to the CP soil and watering regimes, the decreases in biomass accumulation and gas exchange were more pronounced.ConclusionsThe combination of drought and CP soil may have detrimental effects on C. lanceolata growth, and low water content enhances the impacts of CP soil stress on C. lanceolata seedlings. The superiority of the SC over the NC is significant in Chinese fir plantation soil. Therefore, continuously planted soil can be utilized to cultivate improved varieties of C. lanceolata and maintain water capacity. This can improve their growth and physiological performance to a certain extent.

Biochar Application Mitigates the Effect of Heat Stress on Rice (Oryza sativa L.) by Regulating the Root-Zone Environment.

Coping with global warming by developing effective agricultural strategies is critical to global rice (Oryza sativa L.) production and food security. In 2020, we observed that the effect of heat stress on rice plants was mitigated by biochar application (40 g kg−1 soil) in a pot experiment with six consecutive days (6–11 days after transplanting) of daily mean temperatures beyond the critical high temperature (33°C) for tillering in rice. To further determine the eco-physiological processes underlying the effect of biochar on resistance to heat stress in rice plants, we compared root-zone soil properties as well as some plant growth and physiological traits related to nitrogen (N) utilization between rice plants grown with and without biochar in the pot experiment. The results showed that the application of biochar improved the root-zone environment of rice plants by reducing soil bulk density, increasing soil organic matter content, and altering soil bacterial community structure by increasing the ratio of Proteobacteria to Acidobacteria, for example. As a consequence, root morphology, architecture, and physiological traits, such as N assimilation and transport proteins, as well as shoot N uptake and utilization (e.g., photosystems I and II proteins), were improved or up-modulated, while the heat-shock and related proteins in roots and leaves were down-modulated in rice plants grown with biochar compared to those without biochar. These results not only expand our understanding of the basic eco-physiological mechanisms controlling increased heat-stress tolerance in rice plants by the application of biochar, but also imply that improving the root-zone environment by optimizing management practices is an effective strategy to mitigate heat stress effects on rice production.

Better revisiting chlorophyll content retrieval with varying senescent material and solar-induced chlorophyll fluorescence simulation on paddy rice during the entire growth stages

Solar-induced chlorophyll fluorescence at 760 nm (SIF) is a promising proxy of photosynthesis and can help improving plant stress monitoring. The Soil-Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model combines radiative transfer and enzyme kinetics of photosynthesis and is widely used to interpret SIF at different temporal and spatial scales. In this study, growing season canopy hyperspectral reflectance between 400 nm and 900 nm was used to retrieve chlorophyll content (Cab) and leaf inclination (LIDFa) using radiative transfer models (RTMs) combined with the shuffled complex evolution-University of Arizona (SCE-UA) method. These parameters were then used to simulate diurnal and seasonal trends of SIF for paddy rice. The results showed that the accuracy of Cab retrieval was improved when the variation in senescent material (Cs) was considered, especially in the later growth stages. The SCOPE model was able to reliably interpret the diurnal cycle and seasonal trend of SIF with a correlation coefficient of 0.92 and RMSE of 0.12 w m−2 sr-1 um−1. Our results revealed that the SCOPE model provides a promising method for interpreting SIF variations but its accuracy should be evaluated in different growth stages. This will serve as a significant reference for detecting plant photosynthetic activity and physiological traits at different growth stages.

Divergent responses of primary production to increasing precipitation variability in global drylands.

Interannual variability in precipitation has increased globally as climate warming intensifies. The increased variability impacts both terrestrial plant production and carbon (C) sequestration. However, mechanisms driving these changes are largely unknown. Here, we examined mechanisms underlying the response of aboveground net primary production (ANPP) to interannual precipitation variability in global drylands with mean annual precipitation (MAP) <500mmyear-1 , using a combined approach of data synthesis and process-based modeling. We found a hump-shaped response of ANPP to precipitation variability along the MAP gradient. The response was positive when MAP<~300mmyear-1 and negative when MAP was higher than this threshold, with a positive peak at 140mmyear-1 . Transpiration and subsoil water content mirrored the response of ANPP to precipitation variability; evaporation responded negatively and water loss through runoff and drainage responded positively to precipitation variability. Mean annual temperature, soil type, and plant physiological traits all altered the magnitude but not the pattern of the response of ANPP to precipitation variability along the MAP gradient. By extrapolating to global drylands (<500mmyear-1 MAP), we estimated that ANPP would increase by 15.2±6.0TgCyear-1 in arid and hyper-arid lands and decrease by 2.1±0.5TgCyear-1 in dry sub-humid lands under future changes in interannual precipitation variability. Thus, increases in precipitation variability will enhance primary production in many drylands in the future.

Functional physiological phenotyping with functional mapping: A general framework to bridge the phenotype-genotype gap in plant physiology

SummaryThe recent years have witnessed the emergence of high-throughput phenotyping techniques. In particular, these techniques can characterize a comprehensive landscape of physiological traits of plants responding to dynamic changes in the environment. These innovations, along with the next-generation genomic technologies, have brought plant science into the big-data era. However, a general framework that links multifaceted physiological traits to DNA variants is still lacking. Here, we developed a general framework that integrates functional physiological phenotyping (FPP) with functional mapping (FM). This integration, implemented with high-dimensional statistical reasoning, can aid in our understanding of how genotype is translated toward phenotype. As a demonstration of method, we implemented the transpiration and soil-plant-atmosphere measurements of a tomato introgression line population into the FPP-FM framework, facilitating the identification of quantitative trait loci (QTLs) that mediate the spatiotemporal change of transpiration rate and the test of how these QTLs control, through their interaction networks, phenotypic plasticity under drought stress.

Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0

Timely and reliable information about crop management, production, and yield is considered of great utility by stakeholders (e.g., national and international authorities, farmers, commercial units, etc.) to ensure food safety and security. By 2050, according to Food and Agriculture Organization (FAO) estimates, around 70% more production of agricultural products will be needed to fulfil the demands of the world population. Likewise, to meet the Sustainable Development Goals (SDGs), especially the second goal of “zero hunger”, potential technologies like remote sensing (RS) need to be efficiently integrated into agriculture. The application of RS is indispensable today for a highly productive and sustainable agriculture. Therefore, the present study draws a general overview of RS technology with a special focus on the principal platforms of this technology, i.e., satellites and remotely piloted aircrafts (RPAs), and the sensors used, in relation to the 5th industrial revolution. Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs), which is further pushing the boundaries of proficiency through the upgrading of sensors capable of higher spectral, spatial, and temporal resolutions. More prominently, wireless sensor technologies (WST) have streamlined real time information acquisition and programming for respective measures. Improved algorithms and sensors can, not only add significant value to crop data acquisition, but can also devise simulations on yield, harvesting and irrigation periods, metrological data, etc., by making use of cloud computing. The RS technology generates huge sets of data that necessitate the incorporation of artificial intelligence (AI) and big data to extract useful products, thereby augmenting the adeptness and efficiency of agriculture to ensure its sustainability. These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible. Futuristic approaches for benefiting from these cutting-edge technologies are discussed in this study. This study can be helpful for researchers, academics, and young students aspiring to play a role in the achievement of sustainable agriculture.

Physiological response of onion (Allium cepa L.) seedlings to shungite application under two soil water regimes

The application of carbon-rich substrates to agricultural soils is discussed as a strategy to improve soil properties and fertility, which can affect plant physiological traits and enhance agricultural crop yield. The aim of this study was to evaluate if shungite, carbon-rich sedimentary-volcanic rock, may improve plant ecophysiological traits under sufficient water supply as well as soil water deficit. A pot culture experiment was conducted with onion (Allium cepa L.) seedlings, using four shungite concentrations (0, 5, 10 and 20 g kg−1) in an Umbric Podzols and two water regimes: well-watered and drying-wetting cycles. Soil water deficit decreased root nutrient content, depressed seedlings growth, net CO2 assimilation rate (An), stomatal conductance (gs) and the respiration rates in both darkness (Rd) and the light (Rl), but increased water use efficiency (WUE) at leaf level. Shungite application decreased the leaf necrosis under both water regimes and increased total leaf length of DW seedlings. Compared with the well-watered conditions, under drying-wetting cycle shungite stimulated the increase of the An rate and WUE at low measurement temperature. No significant effect of shungite was found for Rd, Rl, Rl/Rd, Rd/Ag (Ag = An + Rl) and Rl/Ag regardless soil water regimes. Shungite application was not so successful to eliminate the negative effects of soil water deficit on growth and physiological processes of A. cepa. The observed positive effects of shungite on the physiological traits of onion seedlings were more likely associated with the increase in the content of nutrients than with the improvement in soil water properties.

Elevated CO2 causes different growth stimulation, water- and nitrogen-use efficiencies, and leaf ultrastructure responses in two conifer species under intra- and interspecific competition.

The continuously increasing atmospheric carbon dioxide concentration ([CO2]) has substantial effects on plant growth, and on the composition and structure of forests. However, how plants respond to elevated [CO2] (e[CO2]) under intra- and interspecific competition has been largely overlooked. In this study, we employed Abies faxoniana Rehder & Wilson and Picea purpurea Mast. seedlings to explore the effects of e[CO2] (700p.p.m.) and plant-plant competition on plant growth, physiological and morphological traits, and leaf ultrastructure. We found that e[CO2] stimulated plant growth, photosynthesis and nonstructural carbohydrates (NSC), affected morphological traits and leaf ultrastructure, and enhanced water- and nitrogen (N)- use efficiencies in A. faxoniana and P. purpurea. Under interspecific competition and e[CO2], P. purpurea showed a higher biomass accumulation, photosynthetic capacity and rate of ectomycorrhizal infection, and higher water- and N-use efficiencies compared with A. faxoniana. However, under intraspecific competition and e[CO2], the two conifers showed no differences in biomass accumulation, photosynthetic capacity, and water- and N-use efficiencies. In addition, under interspecific competition and e[CO2], A. faxoniana exhibited higher NSC levels in leaves as well as more frequent and greater starch granules, which may indicate carbohydrate limitation. Consequently, we concluded that under interspecific competition, P. purpurea possesses a positive growth and adjustment strategy (e.g. a higher photosynthetic capacity and rate of ectomycorrhizal infection, and higher water- and N-use efficiencies), while A. faxoniana likely suffers from carbohydrate limitation to cope with rising [CO2]. Our study highlights that plant-plant competition should be taken into consideration when assessing the impact of rising [CO2] on the plant growth and physiological performance.

Minimizing the Adversely Impacts of Water Deficit and Soil Salinity on Maize Growth and Productivity in Response to the Application of Plant Growth-Promoting Rhizobacteria and Silica Nanoparticles

The development of new approaches for sustaining soil quality, leaf health, and maize productivity are imperative in light of water deficit and soil salinity. Plant growth-promoting rhizobacteria (PGPR) and silica nanoparticles (SiNP) are expected to improve soil chemistry leading to improved plant performance and productivity. In this field experiment, water deficit is imposed by three irrigation intervals—12 (I1), 15 (I2), and 18 (I3) days. Plants are also treated with foliar and soil applications (control, PGPR, SiNP, and PGPR + SiNP) to assess soil enzymatic activity, soil physicochemical properties, plant physiological traits, biochemical analysis, nutrient uptake, and productivity of maize (Zea mays L.) plants grown under salt-affected soil during the 2019 and 2020 seasons. With longer irrigation intervals, soil application of PGPR relieves the deleterious impacts of water shortage and improves yield-related traits and maize productivity. This is attributed to the improvement in soil enzymatic activity (dehydrogenase and alkaline phosphatase) and soil physicochemical characteristics, which enhances the plants’ health and growth under longer irrigation intervals (i.e., I2 and I3). Foliar spraying of SiNP shows an improvement in the physiological traits in maize plants grown under water shortage. This is mainly owing to the decline in oxidative stress by improving the enzymatic activity (CAT, SOD, and POD) and ion balance (K+/Na+), resulting in higher photosynthetic rate, relative water content, photosynthetic pigments, and stomatal conductance, alongside reduced proline content, electrolyte leakage, lipid peroxidase, and sodium content under salt-affected soil. The co-treatment of SiNP with PGPR confirms greater improvement in yield-related traits, maize productivity, as well as nutrient uptake (N, P, and K). Accordingly, their combination is a good strategy for relieving the detrimental impacts of water shortage and soil salinity on maize production.

Effects of polyethylene terephthalate (PET) microplastics and acid rain on physiology and growth of Lepidium sativum

This study evaluated the chronic toxicity (30 days) of different sizes of polyethylene terephthalate (PET) microplastics (60–3000 μm) provided alone or in combination with acid rain, on garden cress (Lepidium sativum). Both biometrical and physiological traits have been evaluated: i) percentage inhibition of seed germination, plant height, leaf number and fresh biomass production; ii) oxidative stress responses (hydrogen peroxide; ascorbic acid and glutathione production); iii) impairment in photosynthetic machinery in term of pigments production; iv) aminolevulinic acid and proline production. Results highlighted that different sizes of PET, alone or in combination with acid rain, are able to negatively affect both biometrical and physiological plant traits. In particular, the lower size of microplastics is able to negatively affect growth and development, as well as to trigger the oxidative burst. Regarding the pigments production, PET coupled with acid rain, induced a higher production of Chl-b, and an inhibition of aminolevulinic acid.

Effect of Salicylic Acid on Plant Physiological and Yield Traits of Soybean

Background: Salicylic acid (SA) is an endogenous plant growth regulator plays a vital role in plant growth, ion uptake, transport, interaction with other organisms and in the responses to environmental stress. The aim of the study was to find the effect of salicylic acid on chlorophyll content, superoxide dismutase and malondialdehyde level of leaves and seed yield parameters of soybean.Methods: Field trials were conducted during kharif 2018 and 2019 at ICAR-Indian Institute of Soybean Research, Indore farm (22.78oN, 75.88oE), India. Salicylic acid applied as foliar spray with (50,100 and 200 ppm) concentrations at vegetative stage (22-25 days after sowing) and at pod filling stage (57-60 days after sowing). Chlorophyll content, lipid peroxidation activity and superoxide dismutase enzyme, plant height, number of pod per plant, seed yield and seed index were determined.Result: Chlorophyll content, antioxidant enzyme were enhanced and the level of lipid peroxidation of leaves was reduced as compared to untreated plant when salicylic acid applied at critical stage of crop growth. Significant increase in soybean seed yield was observed both with concentration of 100 and 200 ppm salicylic acid. Foliar spray with salicylic acid @ 100 ppm at vegetative and at pod filling stage was very effective for better seed production programme to improve quantity as well as quality of soybean seeds.

Proximal Hyperspectral Imaging Detects Diurnal and Drought-Induced Changes in Maize Physiology.

Hyperspectral imaging is a promising tool for non-destructive phenotyping of plant physiological traits, which has been transferred from remote to proximal sensing applications, and from manual laboratory setups to automated plant phenotyping platforms. Due to the higher resolution in proximal sensing, illumination variation and plant geometry result in increased non-biological variation in plant spectra that may mask subtle biological differences. Here, a better understanding of spectral measurements for proximal sensing and their application to study drought, developmental and diurnal responses was acquired in a drought case study of maize grown in a greenhouse phenotyping platform with a hyperspectral imaging setup. The use of brightness classification to reduce the illumination-induced non-biological variation is demonstrated, and allowed the detection of diurnal, developmental and early drought-induced changes in maize reflectance and physiology. Diurnal changes in transpiration rate and vapor pressure deficit were significantly correlated with red and red-edge reflectance. Drought-induced changes in effective quantum yield and water potential were accurately predicted using partial least squares regression and the newly developed Water Potential Index 2, respectively. The prediction accuracy of hyperspectral indices and partial least squares regression were similar, as long as a strong relationship between the physiological trait and reflectance was present. This demonstrates that current hyperspectral processing approaches can be used in automated plant phenotyping platforms to monitor physiological traits with a high temporal resolution.

Characterization on the physiological traits of plants and yield formation capacity upon water- and N-saving conditions in wheat (T. aestivum L.)

Improving water and nitrogen (N) use efficiencies of the Triticum aestivum species contributes to the sustainable agriculture worldwide. In this study, we investigated the physiological traits of plants and the yield formation capacity of winter wheat treated with deficit irrigation together with N-saving condition. Compared with OI-ON (optimum irrigation, OI together with optimum nitrogen, ON), treatment DI-DN (deficit irrigation, DI combined with deficient N (DN, N120) led to decreased contents of chlorophyll, nitrogen (N), and osmolytes, Pn, and the activities of SOD and POD in leaves at various stages together with reduced yields in Jimai 585 and Shimai 22, two cultivars with contrast drought stress responses. The moisture contents in soil profile planted by tested cultivars showed significant reduction under OI-ON with respect to those under DI-DN, suggesting the positive impact of elevated soil water consumption on plant physiological and agronomic traits. The drought-tolerant cultivar Shimai 22 displayed much more improvement on the physiological and agronomic traits, WUE, and NUE than drought-sensitive cultivar Jimai 585 under DI-DN, due to effective usage for soil water and N storage. Yields and grain weights under DI-DN were positively correlated with chlorophyll and osmolytes contents, Pn, and antioxidant enzyme activities, suggesting that the improved physiological traits under DI-DN contributed to the elevated yield for the drought-tolerant cultivar. Two nitrate transporter (NRT) family ones TaNRT2.1 and TaNRT2.2 and TaPYR3 and TaPYR6, two abscisic acid receptor (PYR) family genes exhibited induced transcripts upon DI-DN in wheat cultivars, with more abundance in Shimai 22 than in Jimai 585. Transgenic analysis on the differential genes confirmed their functions in mediating plant drought and N deprivation responses, suggesting that distinct PYR and NRT family members mediate drought and N deprivation adaptation in wheat plants. Our investigation provided insights into high WUE and NUE cultivation of winter wheat under the limited-water and N-saving management.

Predicting Plant Growth from Time-Series Data Using Deep Learning

Phenotyping involves the quantitative assessment of the anatomical, biochemical, and physiological plant traits. Natural plant growth cycles can be extremely slow, hindering the experimental processes of phenotyping. Deep learning offers a great deal of support for automating and addressing key plant phenotyping research issues. Machine learning-based high-throughput phenotyping is a potential solution to the phenotyping bottleneck, promising to accelerate the experimental cycles within phenomic research. This research presents a study of deep networks’ potential to predict plants’ expected growth, by generating segmentation masks of root and shoot systems into the future. We adapt an existing generative adversarial predictive network into this new domain. The results show an efficient plant leaf and root segmentation network that provides predictive segmentation of what a leaf and root system will look like at a future time, based on time-series data of plant growth. We present benchmark results on two public datasets of Arabidopsis (A. thaliana) and Brassica rapa (Komatsuna) plants. The experimental results show strong performance, and the capability of proposed methods to match expert annotation. The proposed method is highly adaptable, trainable (transfer learning/domain adaptation) on different plant species and mutations.