Application of Phenotyping Methods in Detection of Drought and Salinity Stress in Basil (Ocimum basilicum L.)

Evaluation of basil (Ocimum basilicum) accessions under different drought conditions based on yield and physio-biochemical traits

BACKGROUND

Basil is one of the most famous herbs, which has broad usage as a fresh vegetable and therapeutic and pharmaceutical services. The main abiotic stress limiting basil production globally is drought. As a result, appropriate drought screening-which effectively separates high-yielding but drought-sensitive genotypes from drought-tolerant genotypes-is necessary for the optimal selection of high-yielding basil cultivars under drought stress conditions. So, a split plot experiment with three replications based on a completely randomized design were carried out in a pot under field conditions for this investigation. Water levels (full irrigation or control, moderate stress, and severe stress) were assigned as main plots, while 22 basil accessions were given as sub-plots. In this study, leaf yield as well as physio-biochemical traits had measured on accessions.

RESULTS

Our results revealed large variation in yield, essential oil (%), protein, proline, chlorophyll, total phenol and flavonoids traits across the 22 accessions. The percentage of leaf yield reduction in moderate drought stress than normal conditions showed that G1 (-6.5%), G17 (-7.05%), G20 (-9.01%), and G12 (-10.9%) accessions had the least changes, respectively. Although in severe drought stress than normal conditions, the G1 (-32.01%), G12 (-33.12%), G4 (-33.24%), G7 (-34.11%), and G17 (-34.93%) accessions had the least amount of change in plant leaf yield, respectively. Furthermore, the highest yield reduction occurred in moderate and severe stress conditions in G18 (-25.36%) and G8 (-42.98%) accessions, respectively. Cluster analysis based on the ward method in both conditions (moderate and severe drought conditions) placed the accessions in three groups, and accessions were identified as tolerant, whose average traits in that group were higher than the total average. The principal component analysis also showed that in moderate drought conditions, the first two components explained about 95.28% of the total variation, while in severe drought conditions, these two components explained about 96.37% of the total variation.

CONCLUSIONS

The different multivariate analyses (cluster analysis, PCA, mean comparison) were used to identify tolerant and sensitive accessions based on all traits. The accessions G3, G4, G6, and G7 were found to be tolerant to stress, while G10, G15, G16, and G20 were found to be sensitive to drought. These accessions are a useful step in producing drought-tolerant, high-yielding accessions and can be utilized in breeding programs for basil.

Drought stress detection technique for wheat crop using machine learning

The workflow of this research is based on numerous hypotheses involving the usage of pre-processing methods, wheat canopy segmentation methods, and whether the existing models from the past research can be adapted to classify wheat crop water stress. Hence, to construct an automation model for water stress detection, it was found that pre-processing operations known as total variation with L1 data fidelity term (TV-L1) denoising with a Primal-Dual algorithm and min-max contrast stretching are most useful. For wheat canopy segmentation curve fit based K-means algorithm (Cfit-kmeans) was also validated for the most accurate segmentation using intersection over union metric. For automated water stress detection, rapid prototyping of machine learning models revealed that there is a need only to explore nine models. After extensive grid search-based hyper-parameter tuning of machine learning algorithms and 10 K fold cross validation it was found that out of nine different machine algorithms tested, the random forest algorithm has the highest global diagnostic accuracy of 91.164% and is the most suitable for constructing water stress detection models.

Monitoring weed mechanical and chemical damage stress based on chlorophyll fluorescence imaging

Currently, mechanical and chemical damage is the main way to carry out weed control. The use of chlorophyll fluorescence (CF) technology to nondestructively monitor the stress physiological state of weeds is significant to reveal the damage mechanism of mechanical and chemical stresses as well as complex stresses. Under simulated real field environmental conditions, different species and leaf age weeds (Digitaria sanguinalis 2-5 leaf age, and Erigeron canadensis 5-10 leaf age) were subjected to experimental treatments for 1-7 days, and fluorescence parameters were measured every 24 h using a chlorophyll fluorometer. The aim of this study was to investigate the changes in CF parameters of different species of weeds (Digitaria sanguinalis, Erigeron canadensis) at their different stress sites under chemical, mechanical and their combined stresses. The results showed that when weeds (Digitaria sanguinalis and Erigeron canadensis) were chemically stressed in different parts, their leaf back parts were the most severely stressed after 7 days, with photosynthetic inhibition reaching R=75%. In contrast, mechanical stress differs from its changes, and after a period of its stress, each parameter recovers somewhat after 1 to 2 days of stress, with heavy mechanical stress R=11%. Complex stress had the most significant effect on CF parameters, mainly in the timing and efficiency of changes in Fv/Fm, Fq'/Fm', ETR, Rfd, NPQ and Y(NO), with R reaching 71%-73% after only 3-4 days of complex stress, and its changes in complex stress were basically consistent with the pattern of changes in its chemical stress. The results of the study will help to understand the effects of mechanical and chemical stresses and combined stresses on CF parameters of weeds and serve as a guide for efficient weed control operations and conducting weed control in the future.

Garlic Ecotypes Utilise Different Morphological, Physiological and Biochemical Mechanisms to Cope with Drought Stress

Drought negatively affects plants by altering morphological, physiological and metabolic processes and ultimately reducing yields. Garlic (Allium sativum L.), an important member of the Alliaceae family, is also sensitive to drought and maximizing the yield of garlic bulbs is largely dependent on water availability. The objective of this study was to determine the effects of drought stress on morphological and physiological characteristics, as well as on phenolic, sugar, inulin and free amino acid content and antioxidant activity in two Croatian garlic ecotypes, 'Istarski crveni' (IC) and Istarski bijeli (IB). Drought was induced by using polyethylene glycol 8000 (PEG) solution (-0.6 MPa) starting 21 days after clove planting and lasted for 20 days. Drought reduced plant height, number of leaves and plant weight, but increased root length in both ecotypes compared to the control treatment. Among the physiological parameters, significant differences were observed between the two ecotypes studied in the spectral characteristics of the leaves, namely reflection in red, green and blue, VAL, values of the vegetation indices related to the chlorophyll content (CHI, GI), and the anthocyanin content (ARI). Ecotype IC showed higher antioxidant activity in the control treatment due to higher total phenolic content (TPC), but under drought conditions higher DPPH radical scavenging activity was determined in ecotype IB and higher values of FRAP in IC. Sucrose and glucose generally decreased under drought, while inulin increased in IB but decreased in IC. Total free amino acid content increased under drought in both ecotypes. In conclusion, drought tolerance of IB might be associated with increased accumulation of inulin and higher levels of amino acids, especially those shown to contribute to drought resistance. In IC, drought tolerance is associated with an increase in some amino acid compounds and better root growth in depth, probably due to a more efficient translocation of sucrose to the underground part of the plant.

Genome-wide characterization of sugarcane catalase gene family identifies a ScCAT1 gene associated disease resistance

In plants, catalase (CAT) mainly scavenges H₂O₂ from reactive oxygen species (ROS) and regulates the growth and development. So far, genome-wide identification of CAT gene family in Saccharum has not yet been reported. Here, 16 SsCAT genes were identified based on a Saccharum spontaneum genome. They were clustered into three subfamilies, with closer genes sharing similar structures. Most SsCAT proteins contained three conserved amino acids, one active catalytic site, one heme-ligand signature, and three peroxisomal targeting signal 1 (PTS1) sequences. The cis-regulatory element prediction revealed that SsCAT genes were involved in growth and development, and in response to various hormones and stresses. RNA-Seq databases showed that SsCAT genes were differentially expressed in Saccharum tissues and under cold, drought, and Sporisorium scitamineum stresses. The ScCAT1 gene transcript (GenBank accession number KF664183) and relevant CAT activity were up-regulated under S. scitamineum stress. Overexpression of ScCAT1 gene in Nicotiana benthamiana could enhance its resistance to pathogen infection through scavenging of excessive toxic ROS and up-regulated expressions of genes related to hypersensitive response (HR), ROS and salicylic acid (SA) pathways. This study provides comprehensive information for the CAT gene family and sets up a basis for its function identification in sugarcane.

Monitoring Drought Stress in Common Bean Using Chlorophyll Fluorescence and Multispectral Imaging

Drought is a significant constraint in bean production. In this study, we used high-throughput phenotyping methods (chlorophyll fluorescence imaging, multispectral imaging, 3D multispectral scanning) to monitor the development of drought-induced morphological and physiological symptoms at an early stage of development of the common bean. This study aimed to select the plant phenotypic traits which were most sensitive to drought. Plants were grown in an irrigated control (C) and under three drought treatments: D70, D50, and D30 (irrigated with 70, 50, and 30 mL distilled water, respectively). Measurements were performed on five consecutive days, starting on the first day after the onset of treatments (1 DAT-5 DAT), with an additional measurement taken on the eighth day (8 DAT) after the onset of treatments. Earliest detected changes were found at 3 DAT when compared to the control. D30 caused a decrease in leaf area index (of 40%), total leaf area (28%), reflectance in specific green (13%), saturation (9%), and green leaf index (9%), and an increase in the anthocyanin index (23%) and reflectance in blue (7%). The selected phenotypic traits could be used to monitor drought stress and to screen for tolerant genotypes in breeding programs.

Two independent loss-of-function mutations in anthocyanidin synthase homeologous genes are responsible for the all-green phenotype of sweet basil

Sweet basil, Ocimum basilicum L., is an important culinary herb grown worldwide. Although basil is green, many landraces, breeding lines, and exotic cultivars have purple stems and flowers. This anthocyanin pigmentation is unacceptable in traditional Italian basil used for Pesto sauce production. In the current study, we aimed to resolve the genetics that underlines the different colors. We used the recently published sweet basil genome to map quantitative trait loci (QTL) for flower and stem color in a bi-parental F₂ population. It was found that the pigmentation is governed by a single QTL, harboring an anthocyanidin synthase (ANS) gene (EC 1.14.20.4). Further analysis revealed that the basil genome harbors two homeologous ANS genes, each carrying a loss-of-function mutation. ObANS1 carries a single base pair insertion resulting in a frameshift, and ObANS2 carries a missense mutation within the active site. In the purple-flower parent, ANS1 is functional, and ANS2 carries a nonsense mutation. The functionality of the ObANS1 active allele was validated by complementation assay in an Arabidopsis ANS mutant. Moreover, we have restored the functionality of the missense-mutated ObANS2 using site-directed activation. We found that the non-functional alleles were expressed to similar levels as the functional allele, suggesting polyploids invest futile effort in expressing non-functional genes, offsetting their advantageous redundancy. This work demonstrated the usefulness of the genomics and genetics of basil to understand the basic mechanism of metabolic traits and raise fundamental questions in polyploid plant biology.

Study of High-Temperature-Induced Morphological and Physiological Changes in Potato Using Nondestructive Plant Phenotyping

Potato (Solanum tuberosum L.) is vulnerable to high temperatures, which are expected to increase in frequency and duration due to climate change. Nondestructive phenotyping techniques represent a promising technology for helping the adaptation of agriculture to climate change. In this study, three potato cultivars (Agria, Bellarosa and Desiree) were grown under four temperature treatments: 20/15 °C (T1), 25/20 °C (T2), 30/25 °C (T3), and 35/30 °C (T4). Multispectral and chlorophyll fluorescence imaging, 3D multispectral scanning, and gas exchange analysis were used to study the effect of moderate heat stress on potato morphology and physiology and select phenotypic traits most responsive to increased temperatures. The most responsive morphological traits to increased temperatures are related to decreased leaf area, which were detected already at T2. Increased temperatures (already T2) also changed leaf spectral characteristics, indicated by increased red, green, and blue reflectance and decreased far-red reflectance and anthocyanin index (ARI). Regarding chlorophyll fluorescence, increasing temperatures (T2) caused an increase in minimal fluorescence of both dark-adapted (F₀) and light-adapted (F₀') plants. Stomatal conductance, transpiration rate, photosynthetic rate, instantaneous water use efficiency (WUE), and intrinsic water use efficiency increased from T1 to T3 and decreased again in T4. Using recursive partitioning analysis, the most responsive potato phenotypic traits to increased temperature were leaf area projected (LAP), ARI, F₀, and WUE. These traits could be considered marker traits for further studying potato responses to increased temperatures.

Crop breeding for a changing climate in the Pannonian region: towards integration of modern phenotyping tools

The Pannonian Plain, as the most productive region of Southeast Europe, has a long tradition of agronomic production as well as agronomic research and plant breeding. Many research institutions from the agri-food sector of this region have a significant impact on agriculture. Their well-developed and fruitful breeding programmes resulted in productive crop varieties highly adapted to the specific regional environmental conditions. Rapid climatic changes that occurred during the last decades led to even more investigations of complex interactions between plants and their environments and the creation of climate-smart and resilient crops. Plant phenotyping is an essential part of botanical, biological, agronomic, physiological, biochemical, genetic, and other omics approaches. Phenotyping tools and applied methods differ among these disciplines, but all of them are used to evaluate and measure complex traits related to growth, yield, quality, and adaptation to different environmental stresses (biotic and abiotic). During almost a century-long period of plant breeding in the Pannonian region, plant phenotyping methods have changed, from simple measurements in the field to modern plant phenotyping and high-throughput non-invasive and digital technologies. In this review, we present a short historical background and the most recent developments in the field of plant phenotyping, as well as the results accomplished so far in Croatia, Hungary, and Serbia. Current status and perspectives for further simultaneous regional development and modernization of plant phenotyping are also discussed.

Classification of high-throughput phenotyping data for differentiation among nutrient deficiency in common bean

The development of automated, image-based, high-throughput plant phenotyping enabled the simultaneous measurement of many plant traits. Big and complex phenotypic datasets require advanced statistical methods which enable the extraction of the most valuable traits when combined with other measurements, interpretation, and understanding of their (eco)physiological background. Nutrient deficiency in plants causes specific symptoms that can be easily detected by multispectral imaging, 3D scanning, and chlorophyll fluorescence measurements. Screening of numerous image-based phenotypic traits of common bean plants grown in nutrient-deficient solutions was conducted to optimize phenotyping and select the most valuable phenotypic traits related to the specific nutrient deficit. Discriminant analysis was used to compare the efficiency of groups of traits obtained by high-throughput phenotyping techniques (chlorophyll fluorescence, multispectral traits, and morphological traits) in discrimination between nutrients [nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), and iron (Fe)] at early and prolonged deficiency. Furthermore, a recursive partitioning analysis was used to select variables within each group of traits that show the highest accuracy for assigning plants to the respective nutrient deficit treatment. Using the entire set of measured traits, the highest classification success by discriminant function was achieved using multispectral traits. In the subsequent measurements, chlorophyll fluorescence and multispectral traits achieved comparably high classification success. Recursive partitioning analysis was able to intrinsically identify variables within each group of traits and their threshold values that best separate the observations from different nutrient deficiency groups. Again, the highest success in assigning plants into their respective groups was achieved based on selected multispectral traits. Selected chlorophyll fluorescence traits also showed high accuracy for assigning plants into control, Fe, Mg, and P deficit but could not correctly assign K and N deficit plants. This study has shown the usefulness of combining high-throughput phenotyping techniques with advanced data analysis to determine and differentiate nutrient deficiency stress.

Capturing crop adaptation to abiotic stress using image-based technologies

Farmers and breeders aim to improve crop responses to abiotic stresses and secure yield under adverse environmental conditions. To achieve this goal and select the most resilient genotypes, plant breeders and researchers rely on phenotyping to quantify crop responses to abiotic stress. Recent advances in imaging technologies allow researchers to collect physiological data non-destructively and throughout time, making it possible to dissect complex plant responses into quantifiable traits. The use of image-based technologies enables the quantification of crop responses to stress in both controlled environmental conditions and field trials. This paper summarizes phenotyping imaging technologies (RGB, multispectral and hyperspectral sensors, among others) that have been used to assess different abiotic stresses including salinity, drought and nitrogen deficiency, while discussing their advantages and drawbacks. We present a detailed review of traits involved in abiotic tolerance, which have been quantified by a range of imaging sensors under high-throughput phenotyping facilities or using unmanned aerial vehicles in the field. We also provide an up-to-date compilation of spectral tolerance indices and discuss the progress and challenges in machine learning, including supervised and unsupervised models as well as deep learning.

The Effect of Antagonist Abiotic Stress on Bioactive Compounds from Basil (Ocimum basilicum)

Drought and flooding are some of the most common stressful conditions for plants. Due to the recent climate changes, they can occur one after another. This study is focused on the effect of antagonistic abiotic stress such as drought and flooding on the different metabolites from Ocimum basilicum leaves. Six-week-old plants of Ocimum basilicum were exposed to drought or flooding stress for 15 days, followed by antagonist stress for 14 days. The assimilation rates decrease drastically for plants under consecutive stresses from 18.9 to 0.25 µmol m−2 s−1 starting at day 3 of treatment. The stomatal conductance to water vapor gs was also reduced from 86 to 29 mmol m−2 s−1. The emission of green leaf volatiles compounds increases from 0.14 to 2.48 nmol m−2 s−1, and the emission of monoterpenes increased from 2.00 to 7.37 nmol m−2 s−1. The photosynthetic pigment concentration (chlorophyll a and b, and β-carotene), the flavonoid content, and total phenolic content decrease for all stressed plants. The results obtained in this study could indicate that the water status (drought and/or flooding) directly impacts basil plants’ physiological parameters and secondary metabolites.

The OsERF115/AP2EREBP110 Transcription Factor Is Involved in the Multiple Stress Tolerance to Heat and Drought in Rice Plants

The AP2/EREBP family transcription factors play important roles in a wide range of stress tolerance and hormone signaling. In this study, a heat-inducible rice ERF gene was isolated and functionally characterized. The OsERF115/AP2EREBP110 was categorized to Group-IIIc of the rice AP2/EREBP family and strongly induced by heat and drought treatment. The OsERF115/AP2EREBP110 protein targeted to nuclei and suppressed the ABA-induced transcriptional activation of Rab16A promoter in rice protoplasts. Overexpression of OsERF115/AP2EREBP110 enhanced thermotolerance of seeds and vegetative growth stage plants. The OsERF115/AP2EREBP110 overexpressing (OE) plants exhibited higher proline level and increased expression of a proline biosynthesis P5CS1 gene. Phenotyping of water use dynamics of the individual plant indicates that the OsERF115/AP2EREBP110-OE plant exhibited better water saving traits under heat and drought combined stress. Our combined results suggest the potential use of OsERF115/AP2EREBP110 as a candidate gene for genetic engineering approaches to develop heat and drought stress-tolerant crops.

Multispectral Assessment of Sweet Pepper (Capsicum annuum L.) Fruit Quality Affected by Calcite Nanoparticles

Sweet pepper (Capsicum annuum L.) is one of the most important vegetable crops in the world because of the nutritional value of its fruits and its economic importance. Calcium (Ca) improves the quality of sweet pepper fruits, and the application of calcite nanoparticles in agricultural practice has a positive effect on the morphological, physiological, and physicochemical properties of the whole plant. The objectives of this study were to investigate the effect of commercial calcite nanoparticles on yield, chemical, physical, morphological, and multispectral properties of sweet pepper fruits using a combination of conventional and novel image-based nondestructive methods of fruit quality analysis. In the field trial, two sweet pepper cultivars, i.e., Šorokšari and Kurtovska kapija, were treated with commercial calcite nanoparticles (at a concentration of 3% and 5%, calcite-based foliar fertilizer (positive control), and water (negative control) three times during vegetation). Sweet pepper fruits were harvested at the time of technological and physiological maturity. Significant differences were observed between pepper cultivars as well as between harvests times. In general, application of calcite nanoparticles reduced yield and increased fruit firmness. However, different effects of calcite nanoparticles were observed on almost all properties depending on the cultivar. In Šorokšari, calcite nanoparticles and calcite-based foliar fertilizers significantly increased N, P, K, Mg, Fe, Zn, Mn, and Cu at technological maturity, as well as P, Ca, Mg, Fe, Zn, Mn, Cu, and N at physiological maturity. However, in Kurtovska kapija, the treatments increased only Ca at technological maturity and only P at physiological maturity. The effect of treatments on fruit morphological properties was observed only at the second harvest. In Šorokšari, calcite nanoparticles (3% and 5%) increased the fruit length, minimal circle area, and minimal circle radius, and it decreased the fruit width and convex hull compared to the positive and negative controls, respectively. In Kurtovska kapija, calcite nanoparticles increased the fruit width and convex hull compared to the controls. At physiological maturity, lower anthocyanin and chlorophyll indices were found in Kurtovska kapija in both treatments with calcite nanoparticles, while in Šorokšari, the opposite effects were observed.

Application of Trehalose and Salicylic Acid Mitigates Drought Stress in Sweet Basil and Improves Plant Growth

Trehalose (Tre) and salicylic acid (SA) are increasingly used to mitigate drought stress in crop plants. In this study, a pot experiment was performed to study the influence of Tre and SA applied individually or in combination on the growth, photosynthesis, and antioxidant responses of sweet basil (Ocimum basilicum L.) exposed to drought stress. Basil plants were watered to 60% or 100% field capacity with or without treatment with 30 mM Tre and/or 1 mM SA. Drought negatively affected growth, physiological parameters, and antioxidant responses. Application of Tre and/or SA resulted in growth recovery, increased photosynthesis, and reduced oxidative stress. Application of Tre mitigated the detrimental effects of drought more than SA. Furthermore, co-application of Tre and SA largely eliminated the negative impact of drought by reducing oxidative stress through increased activities of antioxidant enzymes superoxide dismutase, peroxidase, and catalase, as well as the accumulation of the protective osmolytes proline and glycine betaine. Combined Tre and SA application improved water use efficiency and reduced the amount of malondialdehyde in drought-stressed plants. Our results suggested that combined application of Tre and SA may trigger defense mechanisms of sweet basil to better mitigate oxidative stress induced by drought stress, thereby improving plant growth.