Stem Elongation Stage Research Articles

Effects of leaf and stem maturation on nutritional value in Megathyrsus maximus.

Megathyrsus maximus is a forage grass native to Africa but widely cultivated in tropical and subtropical regions of the world where it is part of the grazing food chain. This study aimed to evaluate five M. maximus genotypes for the effect of maturity on their morpho-agronomic traits, nutritional composition and digestibility, and to correlate their leaf blade and stem anatomy with their nutritional value. The proportion of sclerenchyma tissues increased as maturity was reached, while lignin accumulation was differentiated between genotypes. Gatton Panic, Green Panic and Mutale genotypes maintained their acid detergent lignin (ADL) values for leaf blades in the three cuts evaluated. In sacco ruminal dry matter disappearance was lower in Green Panic genotype at the vegetative stage for stems, but not for leaf blades. Significant positive correlations were found between dry matter disappearance and mesophyll tissues, and the latter were negatively correlated with neutral detergent fiber (NDF) and ADL. Our results strongly indicate that cutting age and genotype affected the nutritional value of M. maximus leaf blades and stems, with a more pronounced loss of quality in stems than in leaf blades. We recommend increasing the frequency of grazing at early stage or anticipating the stage of stem elongation in Green Panic to produce forage with better nutritional value. © 2023 Society of Chemical Industry.

Demonstration the effectiveness of NDVI with GGE biplot model in determination of high yielding durum wheat (Triticum durum Desf.) genotypes

The use of spectral indices such as normalised difference vegetation index (NDVI) is becoming an important element in the evaluation of physiological traits in cereal crops. Determining the correlation between spectral readings taken at different phenological stages of wheat plants and grain yield (GY) is crucial. This study aimed to demonstrate the effectiveness of NDVI in combination with the GGE biplot model in identifying high yielding durum wheat genotypes. Field experiments were conducted in multiple environments and growth stages to evaluate the relationship between NDVI and grain yield (GY). Twenty-five durum wheat genotypes were tested for two years under rainfed and supplementary irrigation conditions using a split plot experimental design. The results showed significant positive correlations between NDVI and GY, especially at the generative stages under rain-fed conditions. In contrast, NDVI at the grain-filling stage showed a weaker relationship with GY under supplemental irrigation. Genotypes exhibiting high NDVI values up to the stem elongation stage tended to have lower grain yields, emphasizing the importance of considering growth stage dynamics. GGE biplot analysis provided visual information on genotype-trait relationships, helping to identify genotypes with consistent performance in different environments. This study highlights that NDVI can be used to predict yield potential and guide selection in durum wheat breeding programs and the GGE biplot model serves as a valuable tool for genotype evaluation and selection.

NITROGEN FERTILIZER APPLICATION TIME EFFECT ON THE SENESCENCE AND GRAIN YIELD OF DURUM WHEAT (TRITICUM DURUM DESF.)

The experiment progressed to evaluate the effects of time nitrogen fertilizer application on the senescence of durum wheat and its association with grain yield and its components. The experimental treatments, set up in a split-plot design, used five durum wheat cultivars (Adnham, Grecale, Duma, Sardar, Svevo) as the main plots, and the time nitrogen fertilizer application (100% tillering, 100% stem elongation, and 50% tillering + 50% stem elongation stages) under two locations in Northern Iraqi conditions. The results of this study indicated that late senescence cultivars (Grecale and Svevo) produced the highest flowering date (123.89 and 123.61 days), number of spikes/m2 (267.2 and 265.6 spikes), number of grains/10 spikes (330.5 and 323.6 grains), grain yield g/m2 (532.2 and 511.6 g), and harvest index% (38.72% and 39.86%). Moreover, the time of nitrogen fertilizer application at the tillering stage (early application) influenced most of the studied traits. Finally, extending photosynthesis capacity during the grain-filling phases by delaying the rate of senescence could be a better approach to improving the grain yield of wheat cultivars.

Effect of scheduling of irrigation on yield and economics of safflower genotypesunder limited water availability conditions

A field experiment was carried out to find out the effect of irrigation schedules for a suitable variety of safflower (Carthamus tinctorius L.) using 3 genotypes and seven irrigation schedules.. The seed yield of safflowerwas significantly influenced by safflower genotypes. The seed yield of safflower was significantly higher in DSH 184 (1253 kg /ha) which was followed by TSF-1 (1123 kg /ha). While NARI-6 recorded the lowest yields (972 kg /ha). The seed yield of safflower differed significantly due to the application of irrigation at critical stages of the crop. The crop received 3 irrigations each at the Stem elongation stage + Early flowering stage + Seed filling stage resulting in significantly superior yields (1489 kg/ha) which was followed by 2 irrigations each at the Stem elongation stage + Early flowering stage (1408 kg/ha) and 2 irrigations each at the Stem elongation stage + Seed filling stage (1303 kg/ha). Crop grown completely under rainfed conditions recorded the lowest yield (776 kg/ha). The seed yield increased up to 47.88% by providing 3 irrigations each at Stem elongation, Early flowering and Seed filling stages as compared to rainfed conditions.

Response of Soft Wheat Varieties to Application Time of Nitrogen Fertilizer under Mediterranean Climate Conditions

Applying nitrogen fertilizer during the appropriate time is an opportunity to reduce the application amount and improve its availability in the plant, which reduces the costs of Agriculture and environmental pollution. The experiment was carried out in the winter agricultural season 2020-2021 at two sites (Nimrud and Bashiqa) to study the response of soft wheat varieties to different application time of Nitrogen fertilizer under the Mediterranean climate conditions. The experiment included four soft wheat varieties (Benghal, Ebaa-99, Rashida, Tal-Afar), three application time of Nitrogen fertilizer at tillering stage (early application), stem elongation stage (late application) as well as control treatment (no application). The results showed that the Bashiqa site excelled at grain filling stage duration, bio yield, spike number, grain yield, harvest index, while the Nimrod site excelled in the rest of the traits. The Benghal variety excelled in the majority of studied traits at both sites, while application time of Nitrogen fertilizer of stem elongation stage (late application) excelled of the majority studied traits.

Unrevalling phenotypic diversity of root system architecture in ancient wheat species versus modern wheat cultivars

Understanding the phenotypic variability in root system architecture and root-shoot relationships across different growth stages of wheat is of utmost importance for the improvement of genotypes with enhanced nutrient uptake and resource-use efficiency. This study focused on identifying variations and relationships in the root and shoot characteristics of seven modern cultivars and twelve ancient wheat accessions of different species, including T. monococcum, T. turanicum, T. polonicum, T. mirabile, T. durum, and T. aestivum, during the early vegetative growth and stem elongation stages. The results demonstrated significant phenotypic variation among the genotypes for shoot traits, root biomass, rooting depth, R/S ratio, and seminal and nodal root numbers. When considering both growth stages, the dry land-adapted cultivar ‘Taner’ and ancient wheat species, such as T. turanicum (2) and T. monococcum (1) accessions, exhibited deeper roots, which can enhance access to water in drought-prone areas. Furthermore, it was observed that modern wheat cultivars and T. turanicum accessions exhibited increased root biomass, suggesting a higher allocation of resources towards root growth, which could potentially enhance nutrient uptake. Conversely, T. monococcum accessions and T. mirabile revealed lower root biomass compared to other ancient species and modern cultivars. Additionally, the unrooted cluster analysis based on root biomass, rooting depth, and root to shoot ratio at both growth stages indicated a distinct separation of T. monococcum accessions and T. mirabile from other genotypes. Overall, these findings underscore the importance of phenotypic diversity in root traits for crop improvement and adaptation to varying environments. Identifying genotypes with desirable root characteristics can enhance nutrient and water uptake efficiencies, leading to increased crop productivity and sustainability.

Effect of Exogenous Calcium on Tolerance of Winter Wheat to Cold Stress during Stem Elongation Stage.

Low-temperature stress during stem elongation is a major factor limiting wheat yield. While calcium (Ca2+) is known to enhance stress tolerance, it's potential as an alternative to cold priming and the underlying mechanisms in wheat remains unclear. The current study assessed the effects of exogenous Ca2+ and calcium inhibitors on wheat growth and related physiology mechanisms under low-temperature stress. The results revealed that exogenous Ca2+ increased photosynthesis and antioxidant capacity, lowered cell membrane damage, and ultimately enhanced tolerance to low-temperature stress during the stem elongation stage, compared with the non-exogenous Ca2+ treatment. Moreover, exogenous Ca2+ induced endogenous Ca2+ content and triggered the upregulation of Ca2+ signaling and cold-responsive related genes. This study highlights the significance of exogenous Ca2+ in enhancing stress tolerance and contributing to wheat yield improvement under low-temperature stress.

Colonisation of spring wheat spikelets by soil phytopathogens in the Western Siberian forest-steppe

The research aimed to assess the influence of varieties and yearly conditions on phytopathogens' colonisation of spring wheat spikes. The study tasks included specifying the mechanisms and timing of colonisation by phytopathogens, determining the taxonomy of microfungi groups and species related to various generative organs, and identifying the impact of varieties and yearly conditions on microfungi colonisation of generative organs. The research was conducted in 2021-2022 in the northern forest steppe of the Ob region on ten spring wheat varieties from various areas of Russia and the world, using standard methodologies. Of the two experimental years, 2021 was relatively humid (GTU August 1.2), while 2022 was dry (GTU August 0.45). In the research years, the mycobiota of generative organs of spring wheat varieties consisted of Bipolaris sorokiniana Sacc. Shoem, fungi of the Fusarium Link genus, and Alternaria Nees. However, the taxon representation significantly differed between years, varieties, and spike organs. The dynamics of colonisation of generative organs of spring wheat varieties by microfungi suggest early infestation of spikelet peduncles by Fusarium fungi (tubular stage) and B. sorokiniana (stem elongation stage). It indicates the ability of these microfungi to infect spikes through vessels and by airborne-droplet transmission. The study of the collection did not reveal varieties resistant to the infestation of generative organs by B. sorokiniana and Fusarium and Alternaria fungi. B. sorokiniana preferred infesting spikelet peduncles over grains and increased spike colonisation in wetter conditions. B. sorokiniana dominated on spike peduncles in both years of the study and on grains in the wetter 2021. Fusarium fungi demonstrated lower colonisation activity of generative organs in dry and wet conditions, with a higher affinity for spikelet peduncles, which was less dependent on the yearly conditions. In contrast, the colonisation of grains depended on yearly conditions and was 1.9 times lower on average across varieties in dry conditions. Alternaria fungi preferred colonising grains over spikelet peduncles in spring wheat varieties. They were more successful in dry conditions, unfavourable for moisture-loving phytopathogens from the Fusarium and B. sorokiniana genera. They dominated on grains of all collection varieties in the dry 2022.

Effect Analysis of Hydrogen Peroxide Using Hyperspectral Reflectance in Sorghum [Sorghum bicolor (L.) Moench] under Drought Stress.

Due to global climate change, adverse environments like drought in agricultural production are occurring frequently, increasing the need for research to ensure stable crop production. This study was conducted to determine the effect of artificial hydrogen peroxide treatment on sorghum growth to induce stress resistance in drought conditions. Hyperspectral analysis was performed to rapidly find out the effects of drought and hydrogen peroxide treatment to estimate the physiological parameters of plants related to drought and calculate the vegetation indices through PLS analysis based on hyperspectral data. The partial least squares (PLS) analysis collected chlorophyll fluorescence variables, photosynthetic parameters, leaf water potential, and hyperspectral reflectance during the stem elongation and booting stage. To find out the effect of hydrogen peroxide treatment in sorghum plants grown under 90% and 60% of field capacity in greenhouses, growth and hyperspectral reflectance were measured on the 10th and 20th days after foliar application of H2O2 at 30 mM from 1st to 5th leaf stage. The PLS analysis shows that the maximum variable fluorescence of the dark-adapted leaves was the most predictable model with R2 = 0.76, and the estimation model suitability gradually increased with O (R2 = 0.51), J (R2 = 0.73), and P (R2 = 0.75) among OJIP parameters of chlorophyll fluorescence analysis. However, the estimation suitability of predictions for moisture-related traits, vapor pressure deficit (VPD, R2 = 0.18), and leaf water potential (R2 = 0.15) using hyperspectral data was low. The hyperspectral reflectance was 10% higher at 20 days after treatment (DAT) and 3% at 20 DAT than the non-treatment in the far red and infra-red light regions under drought conditions. Vogelmann red edge index (VOG REI) 1, chlorophyll index red edge (CIR), and red-edge normalized difference vegetation index (RE-NDVI) efficiently reflected moisture stress among the vegetation indices. Photochemical reflectance index (PRI) can be used as an indicator for early diagnosis of drought stress because hydrogen peroxide treatment showed higher values than untreated in the early stages of drought damage.

A Ground Point Fitting Method for Winter Wheat Height Estimation Using UAV-Based SfM Point Cloud Data

Height is a key factor in monitoring the growth status and rate of crops. Compared with large-scale satellite remote sensing images and high-cost LiDAR point cloud, the point cloud generated by the Structure from Motion (SfM) algorithm based on UAV images can quickly estimate crop height in the target area at a lower cost. However, crop leaves gradually start to cover the ground from the beginning of the stem elongation stage, making more and more ground points below the canopy disappear in the data. The terrain undulations and outliers will seriously affect the height estimation accuracy. This paper proposed a ground point fitting method to estimate the height of winter wheat based on the UAV SfM point cloud. A canopy slice filter was designed to reduce the interference of middle canopy points and outliers. Random Sample Consensus (RANSAC) was applied to obtain the ground points from the valid filtered point cloud. Then, the missing ground points were fitted according to the known ground points. Furthermore, we achieved crop height monitoring at the stem elongation stage with an R2 of 0.90. The relative root mean squared error (RRMSE) of height estimation was 5.9%, and the relative mean absolute error (RMAE) was 4.6% at the stem elongation stage. This paper proposed the canopy slice filter and fitting missing ground points. It was concluded that the canopy slice filter successfully optimized the extraction of ground points and removed outliers. Fitting the missing ground points simulated the terrain undulations effectively and improved the accuracy.

Foliar applied zinc on different growth stages to improves the growth, yield, quality and kernel bio-fortification of fine rice

Zinc (Zn) is an essential needed for the growth and development of plants, however, Zn is continuously increasing in our soils which is decreasing crop production. Further, the crops grown on Zn-deficient soils also contains a low amount of Zn which is also a major reason for Zn deficiency in humans. So, it is mandatory to supply the Zn to fulfil the crop needs with a corresponding increase in grain Zn. Therefore, the present study was performed to determine the impact of different rates of foliar applied Zn at different growth stages on the growth, yield, quality, and Zn bio-fortification of fine rice. The study comprised foliar application of distilled water (control), foliar applied Zn @ 0.5% at stem elongation stage + booting stage, foliar applied Zn @ 1.0% at stem elongation stage + booting stage, foliar applied Zn @ 0.5% at booting stage and milking stage, foliar applied Zn @ 1.0% at booting stage and milking stage, foliar applied Zn @ 0.5% at milking stage + dough stage and applied Zn @ 1.0% at milking stage + dough stage. The results indicated Zn applied different growth stages significantly improved, productivity and Zn bio-fortification of rice crop. The maximum LAI, LAD, CGR, fertile tillers, 1000 KW, kernel yield, biomass yield, HI, chlorophyll concentration, relative water content (RWC), and antioxidant activities were observed with foliar applied Zn (0.5%) at booting and milking stage and lowest values of all these traits were observed in control. Likewise, the maximum kernel protein, amylose, kernel length and width, and grain Zn concentration was Zn (0.5%) at the booting and milking stage, and minimum kernel protein, amylose, kernel length, and width, and grain Zn concentration was noted in control. The current study findings suggested that foliar-applied Zn (0.5%) at the booting and milking stage could be an important practice to get better productivity, quality, and grain Zn bio-fortification of rice in semi-arid conditions.

Impact of Two Phosphorus Fertilizer Formulations on Wheat Physiology, Rhizosphere, and Rhizoplane Microbiota.

Phosphorus (P) is the second most important macronutrient for crop growth and a limiting factor in food production. Choosing the right P fertilizer formulation is important for crop production systems because P is not mobile in soils, and placing phosphate fertilizers is a major management decision. In addition, root microorganisms play an important role in helping phosphorus fertilization management by regulating soil properties and fertility through different pathways. Our study evaluated the impact of two phosphorous formulations (polyphosphates and orthophosphates) on physiological traits of wheat related to yield (photosynthetic parameters, biomass, and root morphology) and its associated microbiota. A greenhouse experiment was conducted using agricultural soil deficient in P (1.49%). Phenotyping technologies were used at the tillering, stem elongation, heading, flowering, and grain-filling stages. The evaluation of wheat physiological traits revealed highly significant differences between treated and untreated plants but not between phosphorous fertilizers. High-throughput sequencing technologies were applied to analyse the wheat rhizosphere and rhizoplane microbiota at the tillering and the grain-filling growth stages. The alpha- and beta-diversity analyses of bacterial and fungal microbiota revealed differences between fertilized and non-fertilized wheat, rhizosphere, and rhizoplane, and the tillering and grain-filling growth stages. Our study provides new information on the composition of the wheat microbiota in the rhizosphere and rhizoplane during growth stages (Z39 and Z69) under polyphosphate and orthophosphate fertilization. Hence, a deeper understanding of this interaction could provide better insights into managing microbial communities to promote beneficial plant-microbiome interactions for P uptake.

Effect of fungicide treatment and nitrogen fertilisation on the yield of two breeding types of winter oilseed rape cultivars

The effect of three fungicide treatment programmes and the level of spring nitrogen fertilisation on the seed yield of two types ofcultivars of Brassica napus L. sown at two different seeding rates was studied in a field experiment. The subject of the study was anopen-pollinated cultivar ‘Casoar’ and a restored hybrid cultivar ‘Visby’. Three plant protection programmes, two levels of spring nitrogenfertilisation (160 and 220 kg N⋅ha1), and two different seeding rates for each cultivar (‘Visby’—50 and 70 seeds⋅⋅m2; ‘Casoar’—60 and 80 seeds⋅m2) were included. The most intensive protection programme comprised three fungicide treatments: first in autumn at the six-leaves-unfolded stage—BBCH 16, second in spring at the stem elongation stage—BBCH 33, and third at the full flowering stage—BBCH 65. One of two less intensive programmes of plant protection included fungicide application in autumn at the sixleaves-unfolded stage—BBCH 16 and at the full flowering stage—BBCH 65, while the second included fungicide application in spring at the stem elongation stage—BBCH 33 and at the full flowering stage—BBCH 65. The effectiveness of the protection programmes and nitrogen fertilisation was influenced by the intensity of abiotic stress factors. The average yield from the plots protected against pathogens was significantly higher than that from the untreated plots. The increase of nitrogen fertilisation from 160 to 220 kg⋅ha1 also caused a significant increase of average seed yield. The yield of cultivar ‘Visby’ was higher and less dependent on the seeding rate compared to cultivar ‘Casoar’.Keywords: Winter oilseed rape; Cultivars; Disease control; Nitrogen fertilisation; Seeding rate; Sclerotinia sclerotiorum; Leptosphaeria spp.; Alternaria spp. Botrytis cinerea.

Assessing the Role of Crop Rotation in Shaping Foliage Characteristics and Leaf Gas Exchange Parameters for Winter Wheat

Properly designed crop rotation enriches the diversity of the agroecosystem, which has a favorable effect on the environmental properties and crop yield. The experiment assessed winter wheat cultivated under the following crop rotations: A. winter rape + catch crop − spring barley − field pea − winter wheat; B. winter rape − winter wheat + catch crop − field pea − winter wheat; C. winter rape + catch crop − field pea − winter wheat − winter wheat; D. winter rape − winter wheat + catch crop − spring barley − winter wheat. The aim of the study was to investigate: (i) whether the cultivation of wheat in crop rotations following forecrops of rape, pea, barley, and wheat will affect its foliage and photosynthesis; (ii) how the photosynthetic process will affect the wheat yield. At the stem elongation stage (BBCH 36) and at the heading stage (BBCH 58), the following were investigated: foliage features, photosynthetic parameters, and the above-ground biomass; while at the BBCH 89 stage, the grain yield was investigated. It was demonstrated that photosynthesis was most intense under crop rotation A (the highest stomatal conductance, transpiration, intercellular CO2 concentration, and net assimilation rate ranged from 13.1–29.7 μmol CO2∙m−2·s−1). This was reflected in the above-ground biomass volume (1245–1634 g m−2) and grain yield (4.58–7.65 t ha−1). The cultivation of wheat following wheat under crop rotation C and following barley under D had a negative effect on both the foliage and photosynthetic parameters.

Developing machine learning models for wheat yield prediction using ground-based data, satellite-based actual evapotranspiration and vegetation indices

Timely and accurate crop yield estimation is important for adjusting agronomic management and enseuring agricultural sustainability. Machine learning (ML) algorithms provide new opportunities to integrate agronomic information with ground-based and satellite data and develop flexible yield predictive models. In particular, satellite-based vegetation indices and evapotranspiration provide robust proxies for crop yield estimations in the absence of measurements; nevertheless, most prior model development efforts have focused on using only vegetation indices due to the simplicity of the process. Additionally, the contribution of input categories (i.e., field, meteorological, and satellite data) and the use of appropriate proxies, aligned with the crop growth stages, in developing yield predictive models have not been adequately investigated. To address these challenges, we employed two ML techniques, Random Forest (RF) and extreme gradient boosting algorithm (XGB), to estimate wheat yield using meteorological variables, satellite-driven actual evapotranspiration (ETa), and vegetation indices (VIs). ETa was separately computed using the surface energy balance concept and the METRIC model. The models were first trained and tested in the study area using three input combinations: i) meteorological variables, ii) satellite data, and iii) an ensemble of meteorological and satellite data. Then, the best-performing model was further evaluated using two independent datasets. We found ETa to be particularly important in improving the accuracy of the model predictions. Among the vegetation indices, EVI, EVI2, and NDVI during May, and among the meteorological data, growing degree days during the grain filling stage plus minimum temperature in the stem elongation stage had the highest contributions to yield predictions. Both ML algorithms generated relatively accurate results, where XGB was marginally more accurate than RF, considering an average mean absolute error of 0.39 t ha-1 for XGB and 0.50 t ha-1 for RF. Normalized root-mean-square errors of the ensemble, satellite-derived and meteorological-derived models in XGB were 0.05, 0.07, and 0.10, respectively. Nevertheless, both algorithms’ performances deteriorated in predicting the yield values beyond the range of the training set, though XGB could handle the extrapolation process more efficiently than RF.

Hyperspectral Non-Imaging Measurements and Perceptron Neural Network for Pre-Harvesting Assessment of Damage Degree Caused by Septoria/Stagonospora Blotch Diseases of Wheat

The detection and identification of plant diseases is a fundamental task for sustainable crop production. Septoria tritici and Stagonospora nodorum blotch (STB and SNB) are two of the most common diseases of cereal crops that cause significant economic damage. Both pathogens are difficult to identify at early stages of infection. Determining the degree of the disease at a late infection stage is useful for assessing cereal crops before harvesting, as it allows the assessment of potential yield losses. Hyperspectral sensing could allow for automatic recognition of Septoria harmfulness on wheat in field conditions. In this research, we aimed to collect information on the hyperspectral data on wheat plants with different lesion degrees of STB&SNB and to create and train a neural network for the detection of lesions on leaves and ears caused by STB&SNB infection at the late stage of disease development. Spring wheat was artificially infected twice with Septoria pathogens in the stem elongation stage and in the heading stage. Hyperspectral reflections and brightness measurements were collected in the field on wheat leaves and ears on the 37th day after STB and the 30th day after SNB pathogen inoculation using an Ocean Insight “Flame” VIS-NIR hyperspectrometer. Obtained non-imaging data were pre-treated, and the perceptron model neural network (PNN) was created and trained based on a pairwise comparison of datasets for healthy and diseased plants. Both statistical and neural network approaches showed the high quality of the differentiation between healthy and damaged wheat plants by the hyperspectral signature. A comparison of the results of visual recognition and automatic STB&SNB estimation showed that the neural network was equally effective in the quality of the disease definition. The PNN, based on a neuron model of hyperspectral signature with a spectral step of 6 nm and 2000–4000 value datasets, showed a high quality of detection of the STB&SNB severity. There were 0.99 accuracy, 0.94 precision, 0.89 recall and 0.91 F-score metrics of the PNN model after 10,000 learning epochs. The estimation accuracy of diseased/healthy leaves ranged from 88.1 to 97.7% for different datasets. The accuracy of detection of a light and medium degree of disease was lower (38–66%). This method of non-imaging hyperspectral signature classification could be useful for the identification of the STB and SNB lesion degree identification in field conditions for pre-harvesting crop estimation.

Sodium Nitroprusside Improves the Growth and Behavior of the Stomata of Silybum marianum L. Subjected to Different Degrees of Drought.

The use of growth-stimulating signals to increase the tolerance of plants to water deficits can be an important strategy in the production of plants in dry areas. Therefore, a split-plot experiment with three replications was conducted to evaluate the effects of sodium nitroprusside (SNP) application rate as an NO donor (0, 100, and 200 µM) on the growth and yield parameters of Silybum marianum L. (S. marianum) under different irrigation cut-off times (control, irrigation cut-off from stem elongation, and anthesis). The results of this study showed that with increasing drought severity, leaf RWC, proline content and capitula per plant, 1000 grain weight, plant height, branch per plant, capitula diameter, and the biological and grain yield of S. marianum decreased significantly, whereas the number of grains per capitula increased compared with the control. Also, by irrigation cut-off from the stem elongation stage, the density of leaf stomata at the bottom and top epidermis increased by 64% and 39%, respectively, and the length of the stomata at the bottom epidermis of the leaf decreased up to 28%. In contrast, the results of this experiment showed that the exogenous application of nitric oxide reduced the negative effects of irrigation cut-off, such that the application of 100 µM SNP enhanced RWC content (up to 9%), proline concentration (up to 40%), and grain (up to 34%) and biological (up to 44%) yields in plants under drought stress compared with non-application of SNP. The decrease in the number of capitula per plant and capitula diameter was also compensated by foliar application of 100 µM SNP under stress conditions. In addition, exogenous NO changed the behavior of the stomata during the period of dehydration, such that plants treated with SNP showed a decrease in the stomatal density of the leaf and an increase in the length of the stomata at the leaf bottom epidermis. These results indicate that SNP treatment, especially at 100 µM, was helpful in alleviating the deleterious effects of water deficiency and enhancing the tolerance of S. marianum to withholding irrigation times.

Dynamic Assessment of Drought Risk of Sugarcane in Guangxi, China Using Coupled Multi-Source Data

Globally, drought is an increasing threat to agricultural ecosystems, resulting in impaired crop yields, high food prices, and low incomes for farmers. Fluctuations in crop production and prices can exert a negative transboundary effect on food exporting and importing countries across the world through international trade. Therefore, it is important to regionally assess agricultural drought risk to reduce crop yield reduction by adapting existing systems. In this study, from the perspective of Chinese sugar security, a comprehensive assessment index of drought risk of sugarcane was constructed by considering the atmosphere–soil–crop continuum. Based on disaster-causing factors (hazards) and exposure, vulnerability, and mitigation capabilities of disaster subjects (disaster bearers), a risk assessment model of drought disaster of sugarcane in the growing season was established. Results of this study were three-fold. First, the maximum entropy model accurately reflected the reliability and relative importance of the disaster-causing factors of vegetation condition index (VCI), soil moisture condition index (SMCI), and standardized precipitation evapotranspiration index (SPEI), with the area under the curve value of the comprehensive drought risk of sugarcane being greater than 0.75. Second, the drought frequency and impact range in four growth stages of sugarcane significantly declined with the increasing drought severity. Light drought was prevalent in each growth stage, and the occurrence frequency of severe drought was relatively low. The drought frequency was significantly higher in the seedling and maturity stages than in the tillering and stem elongation stages, and the drought distribution was mainly concentrated in the southwest and central regions. Finally, the spatial distribution characteristics of drought risk significantly differed among the four growth stages of sugarcane. The risk level in the seedling stage declined from the southwest to the northeast. The high risk in the tillering stage was mainly concentrated in the southwest and northeast of the study region. In the stem elongation stage, the southwest became a low- risk area. In the maturity stage, the risk level was higher in the southeast than in the other areas. As sugarcane is majorly planted on dry slopes with uneven rainfall, a lack of good infrastructure, and the further intensification of global warming, sugarcane areas that were highly exposed to drought stress were highly vulnerable to drought risk, which in turn weakens farmers’ willingness to plant, thus threatening the security of sugar and biofuel production.

Histological changes at the seedling growth (Z12) and stem elongation (Z31) stages after Tilletia controversa infection

Tilletia controversa Kühn is the causal agent of dwarf bunt disease in wheat. Understanding the infection of T. controversa is of practical and scientific importance for disease management. Here, we used scanning electron microscopy to characterize the histological changes at the seedling (Z12) and stem elongation stages (Z31) in resistant and susceptible wheat cultivars after T. controversa infection. At the seedling stage (Z12), the structure of stem and mesophyll cells slightly deformed after pathogen infection, but this deformation was greater in the susceptible cultivar than in the resistant cultivar. At the stem elongation stage (Z31), the structures of root parenchyma and epidermal cells were deformed more than at the seedling stage (Z12) for both the resistant and susceptible cultivars.

Morpho-Physiological and Hormonal Response of Winter Wheat Varieties to Drought Stress at Stem Elongation and Anthesis Stages.

Drought stress can significantly reduce wheat growth and development as well as grain yield. This study investigated morpho-physiological and hormonal (abscisic (ABA) and salicylic (SA) acids) responses of six winter wheat varieties during stem elongation and anthesis stage as well grain yield-related traits were measured after harvest. To examine drought response, plants were exposed to moderate non-lethal drought stress by withholding watering for 45 and 65% of the volumetric soil moisture content (VSMC) for 14 days at separate experiments for each of those two growth stages. During the stem elongation phase, ABA was increased, confirming the stress status of plants, and SA showed a tendency to increase, suggesting their role as stress hormones in the regulation of stress response, such as the increase in the number of leaves and tillers in drought stress conditions, and further keeping turgor pressure and osmotic adjustment in leaves. At the anthesis stage, heavier drought stress resulted in ABA accumulation in flag leaves that generated an integrated response of maturation, where ABA was not positively correlated with any of investigated traits. After harvest, the variety Bubnjar, followed by Pepeljuga and Anđelka, did not significantly decrease the number of grains per ear and 1000 kernel weight (except Anđelka) in drought treatments, thus, declaring them more tolerant to drought. On the other hand, Rujana, Fifi, and particularly Silvija experienced the highest reduction in grain yield-related traits, considering them drought-sensitive varieties.