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Abstract Drought stress poses a significant risk to soybean production, as it relies on optimum rainfall under rainfed conditions. Exposure to brief dry periods during early vegetative growth impacts soybean growth and development. Choosing a genotype that can withstand stress with minimal impact on physiology and growth might help sustain biomass or yields under low rainfall conditions. Therefore, this study characterized 64 soybean genotypes for traits associated with drought tolerance during the early vegetative stage under two soil moisture treatments, 100% evapotranspiration (well-watered) and 50% evapotranspiration (drought), using the Soil–Plant–Atmosphere Research (SPAR) units. Eighteen morpho-physiological traits responses were assessed, and their relationship with the early vegetative drought tolerance was investigated. Drought stress significantly increased root weight, root volume, and root-to-shoot ratio but reduced shoot weight. Drought-stressed plants increased the canopy temperature by 3.1 °C. Shoot weight positively correlated with root surface area (r = 0.52, P

IntroductionEnvironmental conditions play a prime role in the growth and development of plant species, exerting a significant influence on their reproductive capacity. Soybean is sensitive to high temperatures during flowering and seed developmental stages. Little is known about the combined environmental effect of temperature and CO2 on seed yield and quality and its future generation.MethodsA study was conducted to examine the effect of temperature (22/14°C (low), 30/22°C (optimum), and 38/30°C (high)), and CO2 (420 ppm (ambient; aCO2) and 720 ppm (elevated; eCO2)) on seed yield, quality, and transgenerational seedling vigor traits of soybean cultivars (DS25-1 and DS31-243) using Soil-Plant-Atmospheric-Research facility.ResultsA significant temperature effect was recorded among yield and quality attributes. At high-temperature, the 100-seed weights of DS25-1 and DS31-243 declined by 40% and 24%, respectively, over the optimum temperature at aCO2. The harvest index of varieties reduced by 70% when exposed to high temperature under both aCO2 and eCO2, compared to the optimum temperature at aCO2. The seed oil (- 2%) and protein (8%) content altered when developed under high temperature under aCO2. Maximum sucrose (7.5%) and stachyose (3.8%) accumulation in seeds were observed when developed under low temperatures and eCO2. When the growing temperature increased from optimum to high, the seed oleic acids increased (63%), while linoleic and linolenic acids decreased (- 28% and - 43%, respectively). Significant temperature and CO2 effects were observed in progenies with the highest maximum seedling emergence (80%), lesser time to 50% emergence (5.5 days), and higher seedling vigor from parents grown at low-temperature treatment under eCO2.DiscussionExposure of plants to 38/30°C was detrimental to soybean seed yield, and eCO2 levels did not compensate for this yield loss. The high temperature during seed developmental stages altered the chemical composition of the seed, leading to an increased content of monounsaturated fatty acids. The findings suggest that parental stress can significantly impact the development of offspring, indicating that epigenetic regulation or memory repose may be at play.

Salt stress is a major environmental factor that affects maize production. The impact of salt stress during the early vegetative stage inhibits growth and development. In this study, two maize hybrids, A6659 and P1316, were subjected to five salinity treatments with electrical conductivity 0, 3, 6, 9, and 12 dS m−1 for 28 days. A total of 26 traits were evaluated, including morpho-physiological, biomass, leaf reflectance, and mineral composition in two independent studies. Under salt stress, stomatal conductance and transpiration were reduced, resulting in a canopy temperature rise of 4 °C. A higher salinity level (12 dS m−1) reduced plant height (47%) and total leaf area (44%), consequently reducing total shoot dry weight (37%) and total root dry weight (24%). Leaf minerals such as potassium, magnesium, and phosphorous declined with increasing salt concentrations. The elevated salt concentration in the rhizosphere caused an increase in leaf reflectance at the near-infrared (NIR) region, which is attributed to macronutrient deficiency under stress conditions. The results demonstrated that maize could withstand salt stress up to 3 dS m−1, beyond which plant performance declines depending on the genetics. This study provides insights into key traits that can be used for screening or breeding maize for early-season salt stress tolerance.

Abstract Fourier transform mid infrared (FT-MIR) spectroscopy combined with modeling techniques has been studied as a useful tool for multivariate chemical analysis in agricultural research. A drawback of this method is the sample preparation requirement, in which samples must be dried and fine ground for accurate model calibrations. For research involving large sample sets, this may dramatically increase the time and cost of analysis. This study investigates the effect of fine grinding on model performance using leaf tissue from a variety of crop species. Dried leaf samples (N = 300) from various environmental conditions were obtained with data on 11 nutrients measured using chemical methods. The samples were scanned with attenuated total reflectance (ATR) and diffuse reflectance (DRIFT) FT-MIR techniques. Scanning was repeated after fine grinding for 2, 5, and 10 min. The spectra were analyzed for the 11 nutrients using partial least squares regression with a 75%/25% split for calibration and validation and repeated for 50 iterations. All analytes except for boron, iron, and zinc were well-modeled (average R2 > 0.7), with higher R2 values on ATR spectra. The 5 min level of fine grinding was found to be most optimal considering overall model performance and sample preparation time.

Abstract Drought stress during the reproductive stage and declining soybean yield potential raise concerns about yield loss and economic return. In this study, ten cultivars were characterized for 20 traits to identify reproductive stage (R1–R6) drought-tolerant soybean. Drought stress resulted in a marked reduction (17%) in pollen germination. The reduced stomatal conductance coupled with high canopy temperature resulted in reduced seed number (45%) and seed weight (35%). Drought stress followed by rehydration increased the hundred seed weight at the compensation of seed number. Further, soybean oil decreased, protein increased, and cultivars responded differently under drought compared to control. In general, cultivars with high tolerance scores for yield displayed lower tolerance scores for quality content and vice versa. Among ten cultivars, LS5009XS and G4620RX showed maximum stress tolerance scores for seed number and seed weight. The observed variability in leaf reflectance properties and their relationship with physiological or yield components suggested that leaf-level sensing information can be used for differentiating drought-sensitive soybean cultivars from tolerant ones. The study led to the identification of drought-resilient cultivars/promising traits which can be exploited in breeding to develop multi-stress tolerant cultivars.

Climate change is causing an increase in air temperature during the reproductive and grain-filling stages, which is detrimental to soybean production and quality. Assessing the variability induced by heat stress in morpho-physiological, yield, and quality traits is an effective strategy for identifying heat-tolerant cultivars. In this study, ten soybean cultivars were exposed to temperatures 4.6 °C above the optimum (32 °C) from the R1 to R6 stages to investigate the heat stress-induced variability in morpho-physiological, yield, and quality traits. On average, stomatal conductance decreased by 11% under heat stress compared to the control. However, the cultivar R01–416F had the maximum increase in stomatal conductance (34%), and the least increase in canopy temperature ( + 2 °C) under the heat stress as compared to the control. Heat-stressed plants recorded a 3% reduction in chlorophyll content, with the cultivar DM45X61 experiencing the greatest decline of 22%. Across cultivars, specific leaf area decreased by 17% under heat stress, with G4620RX recording the highest reduction (28%). The results revealed a significant reduction in pod number (3.8%), pod weight (4%), seed number (4.2%), seed weight (5%), and hundred-seed weight (1.1%) per °C increase in temperature over the control. However, among the ten cultivars, R15–2422 and LS5009XS displayed relatively less reduction in seed number under heat stress. In comparison to the control, the cultivar R01–416F had the highest reduction in seed protein (4.4%) under heat stress, while it recorded a 16.6% increase in oil. Based on the phenotypic plasticity index, the cultivars R15–2422, and LS5009XS demonstrated the potential of maintaining higher yields under hot conditions. These findings highlight the significant impact of heat stress on soybean plasticity. The knowledge generated in this study helps in selecting and developing cultivars that can withstand heat stress, thus maintaining productivity and quality in warmer climates.

Uncrewed aerial systems (UASs) provide high temporal and spatial resolution information for crop health monitoring and informed management decisions to improve yields. However, traditional in-season yield prediction methodologies are often inconsistent and inaccurate due to variations in soil types and environmental factors. This study aimed to identify the best phenological stage and vegetation index (VI) for estimating corn yield under rainfed conditions. Multispectral images were collected over three years (2020-2022) during the corn growing season and over fifty VIs were analyzed. In the three-year period, thirty-one VIs exhibited significant correlations (r ≥ 0.7) with yield. Sixteen VIs were significantly correlated with the yield at least for two years, and five VIs had a significant correlation with the yield for all three years. A strong correlation with yield was achieved by combining red, red edge, and near infrared-based indices. Further, combined correlation and random forest an alyses between yield and VIs led to the identification of consistent and highest predictive power VIs for corn yield prediction. Among them, leaf chlorophyll index, Medium Resolution Imaging Spectrometer (MERIS) terrestrial chlorophyll index and modified normalized difference at 705 were the most consistent predictors of corn yield when recorded around the reproductive stage (R1). This study demonstrated the dynamic nature of canopy reflectance and the importance of considering growth stages, and environmental conditions for accurate corn yield prediction.

The underlying principle of this current research was to characterize the cellulosic fibers that were retted from the roots of Acalypha indica L. plant to find their aptness for making green composites. Physical characterization tests were conducted and reported proving the reinforcing capability of these fibers which has a density of 1.356 g/cm3. Chemical composition tests conducted on these fibers showed the weight % of cellulose as 67.86. Amorphous constituents such as hemicellulose and lignin were present as 0.24 and 18.75 weight %, respectively. Wax, ash, and moisture were respectively present as 0.86, 2.13, and 10.16 weight % of fibers. X-ray diffraction (XRD) studies purported the presence of both amorphous and crystalline contents of cellulose confirming the peaks of Fourier-transform infrared spectroscopy (FTIR) studies. The fibers possessed a crystallinity index of 46.62% and their crystallite size was computed as 3.68 nm from XRD, with a good temperature bearing capacity of 225°C as ascertained from the thermo-gravimetric analysis. Conglomeration of fibrils and the roughness characteristics were evident from the scanning electron microscopic images and atomic force microscopic observations, respectively. Thus, it can be seen that this newly identified fiber are apposite reinforcements and can be explored further by infusing them in polymer matrices for making sustainable products.

The purpose of this investigation is to characterize the fibers extorted from the bark of Vacheilla nilotica ssp indica tree. Physical studies conducted on the fibers showed that the density of the fibers was 1.375 gm/cm3 with their chemical composition containing 60.3% cellulose, 5.76% hemicellulose and 25.24% lignin. Wax, moisture and ash content present in the fibers were 0.63%, 6.95% and 1.12% respectively. FTIR spectrum proved the presence of functional groups pertaining to biopolymers. X-ray diffraction studies on the fibers showed crystalline index, degree of crystallinity and crystallite size as 57.66%, 70.26% and 2.27 nm respectively. Apparent activation energy of the fibers was 59.17 kJ/mol as derived from Broido’s plot and the fibers subsist 225°C without degradation. Tensile strength, percent elongation and Young’s modulus of the fibers were found as 242 ± 19MPa, 2.06 ± 0.07% and 11.76 ± 0.58GPa respectively. SEM images ascertained the rough fiber surface and the roughness parameters such as average roughness, root mean square roughness, skewness and kurtosis of the fibers were observed as 56.9668 nm, 78.5079 nm, 0.45906 and 3.57799 respectively from the atomic force microscope images. The study culminates that the physical, chemical, thermal and surface characteristics are comparable with other cellulose fibers.

In-Text Mining, Information Retrieval (IR), and Natural Language Processing (NLP) dig out the important text or word from an unstructured document is coined by the technique called Keyword extraction. It helps to identify the core information about the document in specific. Instead of going through the entire document, this method helps to retrieve sufficient information instantly in a short span of time. It is essential to mine the meaningful word from the document in text analytics. The proposed system has been based on semantic relation to extracts the keyword from unstructured text documents by means of practice like Latent Semantic Analysis (LSA). In view of this method, there exists a semantic relation between the sentences available in the document and the words. Extracted text permits to signify text in a strong way and has a high preference to carry more important information about the sentences. In this regard, LSA has produced better outcomes when compared with the TF-IDF, RAKE, YAKE, and Text Rank algorithm. Consequently, the keyword extraction has been occupied in Automatic Question Generation (ACQ) to generate the Fill up the blank (FB) and Multiple Choice Questions (MCQ) with distractor set. The top five, ten keywords are involved in questionable generation. The proposed system could be implemented in the question generation system to assess the skill level of the learner.

Plants are sensitive to changes projected in climates, such as elevated carbon dioxide (eCO2), high temperature (T), and drought stress (DS), which affect crop growth, development, and yield. These stresses, either alone or in combination, affect all aspects of sweetpotato plant growth and development, including storage root development and yield. We tested three sweetpotato cultivars (Beauregard, Hatteras, and LA1188) responses to eight treatments (Control, DS, T, eCO2, DS + T, T + eCO2, DS + eCO2, DS + T + eCO2). All treatments were imposed 36 days after transplanting (DAP) and continued for 47 days. Treatments substantially affected gas exchange, photosynthetic pigments, growth, and storage root components. Cultivars differed considerably for many of the measured parameters. The most significant negative impact of DS was recorded for the shoot and root weights. The combination of DS + T had a significant negative effect on storage root parameters. eCO2 alleviated some of the damaging effects of DS and high T in sweetpotato. For instance, eCO2 alone or combined with DS increased the storage root weights by 22% or 42% across all three cultivars, respectively. Based on the stress response index, cultivar “Hatteras” was most tolerant to individual and interactive stresses, and “LA 1188” was sensitive. Our findings suggest that eCO2 negates the negative impact of T or DS on the growth and yield of sweetpotato. We identified a set of individual and interactive stress-tolerant traits that can help select stress cultivars or breed new lines for future environments.

Green material consciousness has enthused to introduce natural fiber alternative to man-made fiber as reinforcement in polymer composites. The presence of surface impurities and non-cellulosic component in the natural fibers are the major limitations to form effective polymer composite due to lack of interfacial bonding. This can be prevailed by various physical and chemical treatments. The present work reports the effect of chemical treatment on physical, chemical, mechanical, and thermal properties of Sesbania rostrata fibers (SRFs) by commercial sodium bicarbonate (NaHCO3), commonly known as ‘baking soda.’ The SRFs are treated with 10%w/w of NaHCO3 for the different duration (1, 3 and 5 days) at room temperature. The treated fiber shows high and improved mechanical strength and cellulose fraction. The results of X-ray diffraction and thermogravimetric analysis revealed that the crystallinity index and thermal stability are increased for the treated fiber. The significant removal of hemicellulose in the treated fiber is also observed from the FT-IR characteristic curve. The scanning electron microscopy images exposed the presence of rough surface on the treated fibers. Further, the comparison of treatment results showed that 3 days duration is the optimum period for treating the SRFs.

The present investigation is mainly aimed to characterize the cellulosic fibers extracted from the stem of Shwetark plant to test its possibility to be used as polymeric reinforcement. Chemical analysis conducted on the Shwetark fibers shows the presence of cellulose (69.65 wt. %), lignin (16.82 wt. %), wax (0.53 wt. %), ash (3.4 wt. %) and wetness content (8.8 wt. %). The density of the fibers is found as 1.364 g/cm3. Crystallinity index and the crystallite size of the fibers are calculated as 72.06% and 3nm, respectively, from X-ray diffraction analysis while the presence of functional groups is ascertained from Fourier transform infrared analysis. Thermogravimetric analysis shows that the fibers are thermally stable till 225°C, and the fiber morphology seen through scanning electron microscopic shows that the fibers are composed of densely and uniformly packed cellulose microfibrils. Atomic force microscopic studies exemplify that Shwetark fibers can be used for tribological applications. The mean tensile strength and percentage elongation of the Shwetark fibers are found as 309.68 MPa and 1.092%, respectively. Thus, the studies show the possibility of Shwetark fibers as prospective candidates to replace harmful synthetic man-made fibers.

Drought-induced reduction in crop growth and productivity can be compensated by increasing atmospheric carbon dioxide (CO2), a significant contributor to climate change. Drought stress (DS) affects crops worldwide due to dwindling water resources and irregular rainfall patterns. The experiment was set up under a randomized complete block design within a three-by-two factorial arrangement. Six SPAR chambers represent three blocks (10 replications each), where each chamber has 30 pots in three rows. Each chamber was maintained with 30/22 (day/night) °C temperature, with either ambient (aCO2; 420 ppm) or elevated CO2 (eCO2; 720 ppm) concentrations. This experiment was designed to address the impact of DS on the physiological and biochemical attributes and study how the eCO2 helps alleviate the adversity of DS in basil. The study demonstrated that DS + eCO2 application highly accelerated the decrease in all forms of carotene and xanthophylls. eCO2 positively influenced and increased anthocyanin (Antho) and chlorophyll (LChl). eCO2 supplementation increased LChl content in basil under DS. Furthermore, DS significantly impeded the photosynthetic system in plants by decreasing CO2 availability and causing stomatal closure. Although eCO2 did not increase net photosynthesis (Pn) activity, it decreased stomatal conductance (gs) and leaf transpiration rate (E) under DS, showing that eCO2 can improve plant water use efficiency by lowering E and gs. Peroxidase and ascorbate activity were higher due to the eCO2 supply to acclimate the basil under the DS condition. This study suggests that the combination of eCO2 during DS positively impacts basil’s photosynthetic parameters and biochemical traits than aCO2.

Agriculture isn't just a profession for public yet in adding up a method of life. Most Customs and Cultures in the World spin around Agriculture. Advanced agriculture can possibly make agriculture more gainful, more reliable and to utilize time and assets all the more productively. This brings basic favorable circumstances for farmers and more extensive social advantages far and wide. Identification of plant infection is troublesome for farmers. In the event that identified infection is inaccurate, at that point there is an immense misfortune on the creation of crops and efficient estimation of market. This work introduces new software to help the farmers to identify the infection automatically and offer solutions to the identified problems through expert database. It identifies infected spots of leaf using Fuzzy C-means clustering (FCM) algorithm. Features are extracted using Scale Invariant Feature Transform (SIFT). Long Short Term Memory Networks (LSTM) is used to classify the extracted features. The investigational results are performed on Kaggle Dataset. The projected work is tested for some fungi and bacteria affected leaf of disease classes including Leaf Rust, Blights, Powderly Mildew, Mealy bugs, Downy Angular leaf spot, Mildew, and healthy leaves. The disease classification results illustrate that the projected work outperforms with enhanced accuracy, precision, Recall and F1-Score when compared existing methods. The proposed work tested for around 8000 images, which contains 5278 healthy leaf images and 2725 diseased leaf images achieved up to 96% of accuracy.

Low rainfall combined with heat stress during grain filling can cause a severe threat to maize production. Compared to individual stress, the impact of combined stressors on plant performance during the grain filling remains less explored. In this study, two maize genotypes, ‘B73’ and ‘Mo17’, were subjected to four treatments (control, drought stress, heat stress, and combined drought and heat stress) to understand how maize genotypes respond to stressors during grain filling. Stomatal conductance displayed an opposite response between drought and heat or combined stresses during the mid-grain filling stage. Averaged over genotypes, decreased stomatal conductance (67.4%) and increased leaf temperature (5.6 °C) under combined stress treatments resulted in a significant yield reduction (78.9%) compared to control. Drought or combined stressors during the grain filling stage had a predominant effect on sink potential (kernel weight) than heat stress. Reduction in kernel size of genotype ‘B73’ was associated with a 5.5% decline in starch under heat stress. Analysis of individual and interactive stressors effects on maize showed that trait responses could vary with stresses during grain filling. The present study showed that the maize phenotypic responses differ between individual and interactive stresses. The genotype ‘Mo17’ exhibited relatively higher tolerance to both individual and combined drought and heat stresses than ‘B73’. The present study highlighted the maize plant responses to individual and combined stresses, which is essential for improving maize tolerance to drought and heat stress conditions.

Worker's safety and water quality maintenance are the two predominant process that is followed inside the Mines. Many models had been proposed in the past to enhance the whole process but they failed to do so due to the practical limitations in the deployment in terms of cost. Though technology had improved much, human intervention is still unavoidable in mines. Considering the practical issues, in this article, a novel methodology using the Internet of Things (IoT) is proposed. This study is mainly focused on the change in the geometry/structure of the coal mining field due to pressure and water contamination that occurs in the region during coal extraction. Several sensors are adopted to measure the water quality and computational technique is used to analyze roof pressure variation in the coalfield. The roof pressure experienced by the nascent structure is compared with a structure that is roof bonded with a glass fiber composite layer. The significance of nanofiber technology is analyzed and reported. To ensure water quality, Harmonic Water Optimization (HWO) Algorithm is developed, here 10 different water flow areas are chosen and their corresponding data is gathered using IoT sensors. Harmony Management Preprocessing (HMP) Algorithm is developed to preprocess the redundant and ambiguous data. Heuristic Fusion Clustering (HFC)algorithm is developed for the data fusion, which can cluster and improve the data quality. The analysis of the proposed work reveals that it would greatly improve the sustainable development of mining safety and water quality which is the most vital factor.

Abstract Background Brassica carinata (A) Braun has recently gained increased attention across the world as a sustainable biofuel crop. B. carinata is grown as a summer crop in many regions where high temperature is a significant stress during the growing season. However, little research has been conducted to understand the mechanisms through which this crop responds to high temperatures. Understanding traits that improve the high-temperature adaption of this crop is essential for developing heat-tolerant varieties. This study investigated lipid remodeling in B. carinata in response to high-temperature stress. A commercial cultivar, Avanza 641, was grown under sunlit-controlled environmental conditions in Soil-Plant-Atmosphere-Research (SPAR) chambers under optimal temperature (OT; 23/15°C) conditions. At eight days after sowing, plants were exposed to one of the three temperature treatments [OT, high-temperature treatment-1 (HT-1; 33/25°C), and high-temperature treatment-2 (HT-2; 38/30°C)]. The temperature treatment period lasted until the final harvest at 84 days after sowing. Leaf samples were collected at 74 days after sowing to profile lipids using electrospray-ionization triple quadrupole mass spectrometry. Results Temperature treatment significantly affected the growth and development of Avanza 641. Both high-temperature treatments caused alterations in the leaf lipidome. The alterations were primarily manifested in terms of decreases in unsaturation levels of membrane lipids, which was a cumulative effect of lipid remodeling. The decline in unsaturation index was driven by (a) decreases in lipids that contain the highly unsaturated linolenic (18:3) acid and (b) increases in lipids containing less unsaturated fatty acids such as oleic (18:1) and linoleic (18:2) acids and/or saturated fatty acids such as palmitic (16:0) acid. A third mechanism that likely contributed to lowering unsaturation levels, particularly for chloroplast membrane lipids, is a shift toward lipids made by the eukaryotic pathway and the channeling of eukaryotic pathway-derived glycerolipids that are composed of less unsaturated fatty acids into chloroplasts. Conclusions The lipid alterations appear to be acclimation mechanisms to maintain optimal membrane fluidity under high-temperature conditions. The lipid-related mechanisms contributing to heat stress response as identified in this study could be utilized to develop biomarkers for heat tolerance and ultimately heat-tolerant varieties.

Rice (Oryza sativa) is a human staple food and serves as a model organism for genetic and molecular studies. Few studies have been conducted to determine the effects of ultraviolet-B (UV-B) stress on rice. UV-B stress triggers morphological and physiological changes in plants. However, the underlying mechanisms governing these integrated responses are unknown. In this study, we conducted a proteomic response of rice leaves to UV-B stress using two-dimensional gel electrophoresis and identified the selected proteins by mass spectrometry analysis. Four levels of daily biologically effective UV-B radiation intensities were imposed to determine changes in protein accumulation in response to UV-B stress: 0 (control), 5, 10, and 15 kJ m−2 d−1in two cultivars, i.e., IR6 and REX. To mimic the natural environment, we conducted this experiment in Sunlit Soil-Plant-Atmosphere-Research (SPAR) chambers. Among the identified proteins, 11% of differentially expressed proteins were found in both cultivars. In the Rex cultivar, only 45% of proteins are differentially expressed, while only 27.5% were expressed in IR6. The results indicate that REX is more affected by UV-B stress than IR6 cultivars. The identified protein TSJT1 (spot 16) in both cultivars plays a crucial role in plant growth and development during stress treatment. Additionally, we found that UV-B stress altered many antioxidant enzymes associated with redox homeostasis and cell defense response. Another enzyme, the glyceraldehyde-3-phosphate dehydrogenase (GAPDH), has been identified as spot 15, which plays an essential role in glycolysis and cellular energy production. Another vital protein identified is glycosyl hydrolase (GH) as spot 9, which catalyzes the hydrolysis of glycosidic bonds in cell wall polymers and significantly affects cell wall architecture. Some identified proteins are related to photosynthesis, protein biosynthesis, signal transduction, and stress response. The findings of our study provide new insights into understanding how rice plants are tailored to UV-B stress via modulating the expression of UV-B responsive proteins, which will help develop superior rice breeds in the future to combat UV-B stress. Data are available via ProteomeXchange with identifier PXD032163.

Abstract Drought and heat stresses are the major abiotic stress factors detrimental to maize (Zea mays L.) production. Much attention has been directed toward plant responses to heat or drought stress. However, maize reproductive stage responses to combined heat and drought remain less explored. Therefore, this study aimed to quantify the impact of optimum daytime (30°C, control) and warmer daytime temperatures (35°C, heat stress) on pollen germination, morpho‐physiology, and yield potential using two maize genotypes (“Mo17” and “B73”) under contrasting soil moisture content, that is, 100% and 40% irrigation during flowering. Pollen germination of both genotypes decreased under combined stresses (42%), followed by heat stress (30%) and drought stress (19%). Stomatal conductance and transpiration were comparable between control and heat stress but significantly decreased under combined stresses (83% and 72%) and drought stress (52% and 47%) compared with the control. Genotype “Mo17” reduced its green leaf area to minimize the water loss, which appears to be one of the adaptive strategies of “Mo17” under stress conditions. The leaf reflectance of both genotypes varied across treatments. Vegetation indices associated with pigments (chlorophyll index of green, chlorophyll index of red edge, and carotenoid index) and plant health (normalized difference red‐edge index) were found to be highly sensitive to drought and combined stressors than heat stress. Combined drought and heat stresses caused a significant reduction in yield and yield components in both Mo17 (49%) and B73 (86%) genotypes. The harvest index of genotype “B73” was extremely low, indicating poor partitioning efficiency. At least when it comes to “B73,” the cause of yield reduction appears to be the result of reduced sink number rather than the pollen and source size. To the best of our awareness, this is the first study that showed how the leaf‐level spectra, yield, and quality parameters respond to the short duration of independent and combined stresses during flowering in inbred maize. Further studies are required to validate the responses of potential traits involving diverse maize genotypes under field conditions. This study suggests the need to develop maize with improved tolerance to combined stresses to sustain production under increasing temperatures and low rainfall conditions.

In humid climates, waterlogging from excessive rainfalls can be a major limiting factor for soybean production, particularly during the reproductive stage. However, there is a limited understanding of how soybean growth and physiology respond to waterlogging during this critical stage. Here, we investigated the effects of waterlogging and subsequent reoxygenation on the growth, physiology, yields, and leaf hyperspectral reflectance traits of the soybean cultivar ‘Asgrow AG5332’. The crop was grown to stage R1 (initial flowering) in outdoor pot culture conditions, and then waterlogged for 16 days. The flooded pots were drained and continuously monitored for recovery for an additional 16 days. The results showed that soil oxygen levels declined rapidly to zero in about 5 days after waterlogging, and slowly recovered in about 5–16 days. However, it did not reach the same level as the control plants, which maintained an oxygen concentration of 18%. Increasing waterlogging duration negatively affected leaf chlorophyll index, water potential, and stomatal conductance, with a consequent decline in the photosynthetic rate. Further, decreased photosynthetic rate, leaf area, and mineral nutrients resulted in lower biomass and seed yield. Pod dry weight and leaf number were the most and least sensitive parameters, respectively, decreasing by 81% and 15% after 16 days of waterlogging. Waterlogged plants also had higher reflectance in the PAR, blue, green, and red regions, and lower reflectance in the near-infrared, tissue, and water band regions, indicating changes in chemistry and pigment content. The current study reveals that the soybean crop is susceptible to waterlogging during the reproductive stage, due to poor recovery of soil oxygen levels and physiological parameters. Understanding and integrating the growth, physiology, and hyperspectral reflectance data from this study could be used to develop improved cultivars to ensure the stability of soybean production in waterlogging-prone areas.

Temperature is a major abiotic stress factor limiting plant growth and development during the early developmental stage. Information on carinata (Brassica carinata A. Braun) traits response to low and high temperatures is necessary for breeding or selecting genotypes suited for specific ecoregions, which is limited. In the present study, 12 carinata genotypes were evaluated under low (17/09°C), optimum (22/14°C), and high (27/19°C) day/night temperatures at the early developmental stage. This study quantified temperature effects on several physiological and morphological characteristics of 12-advanced carinata lines. High-temperature plants decreased (15%) the accumulation of flavonoids and increased the nitrogen balance index by 25%. Low-temperature treatment significantly inhibited the aboveground (plant height, leaf area, number, and shoot weight) and root (length, surface area, and weight) traits. Across all genotypes, the shoot weight decreased by 55% and the root weight by 49% under low temperature. On the other hand, the maximum proportion of biomass was partitioned to roots under low temperature than at the high temperature. A poor relationship (r2 = 0.09) was found between low- and high-temperature indices, indicating differences in trait responses and tolerance mechanisms. AX17004 and AX17009 with higher root to shoot ratios might be suitable for late planting windows or regions with low-temperature spells. The two genotypes (AX17015 and AX17005) accumulated higher biomass under low- and high-temperature treatments can be used for planting in later summer or early winter. The identified low- and high-temperature stress-tolerant carinata genotypes could be a valuable resource for increasing stress tolerance during the early developmental stage.

The aim of the present work is to estimate the accumulation of various elements related to the core sediment belong to the Krishna-Godavari marginal area with a nuclear analytical technique. Hence, a 4.12 m long marine sediment gravity core was collected from near to Nizampatnam Bay that related to Bay of Bengal and by using particle induced X-ray emission (PIXE) elemental concentrations have been determined. The concentrations of major elements like Fe, Ca, K, Ti, Mn and minor (trace) elements such as Sr, Co, V, Zn, Ni, Cu, Rb, Sc and Cr have been evaluated with the obtained PIXE spectra. These values are interpreted based on the monsoonal runoff coming from the rivers causing to play an important role for bring lot of sedimentary material of the coastal waters to the Bay of Bengal. Further results are interpreted to understand biological and anthropogenic activities, chemical reactions etc during Holocene and Pleistocene periods.

This study aims to characterize and find the suitability of Calotropis procera fibers to reinforce polymer matrices from Fourier-transform infrared spectroscopy and X-ray diffraction studies. Composite samples are prepared using varying weight % of Calotropis procera fibers with epoxy resin as matrix and the effect of fiber loading on the tensile, flexural, impact and water absorption properties are conducted and reported. It is found that fiber loading improves the mechanical strength of the composites and it is attributed to the strong bonding that exists between the fiber reinforcement and the matrix polymer. Fiber loading in excess of 40 weight % leads to decrease in the mechanical strength, while no significant difference in water absorption is noticed when the fiber loading exceeds 30 weight %. The study suggests that Calotropis procera fibers are promising candidates to reinforce polymers and can be used for the fabrication of composites.

Temperature is the primary factor affecting the morpho-physiological, developmental, and yield attributes of soybean. Despite several temperature and soybean studies, functional relationships between temperature and soybean physiology and yield components are limited. An experiment was conducted to determine the optimum temperature for soybean gas exchange and yield components using indeterminate (Asgrow AG5332, AG) and determinate (Progeny P5333 RY, PR) growth habit cultivars. Plants grown outdoors were exposed to 5 day/night temperature treatments, 21/13, 25/17, 29/21, 33/25, and 37°C/29°C, from flowering to maturity using the sunlit plant growth chambers. Significant temperature and cultivar differences were recorded among all measured parameters. Gas exchange parameters declined with increasing temperature treatments during the mid-pod filling stage, and quadratic functions best described the response. The optimum temperature for soybean pod weight, number, and seed number was higher for AG than PR, indicating greater high-temperature tolerance. Soybean exposed to warmer parental temperature (37°C/29°C) during pod filling decreased significantly the transgenerational seed germination when incubated at 18, 28, and 38°C. Our findings suggest that the impact of temperature during soybean development is transferable. The warmer temperature has adverse transgenerational effects on seed germination ability. Thus, developing soybean genotypes tolerant to high temperatures will help growers to produce high-yielding and quality beans. The quantified temperature, soybean physiology, and yield components-dependent functional algorithms would be helpful to develop adaptation strategies to offset the impacts of extreme temperature events associated with future climate change.

The thermal properties of polymer fibers namely polyvinyl alcohol fiber (PVA) and polypropylene fiber (PP) have been taken for study to carry out this present work. Simulated pore solution (SPS) is prepared by using the combination of chemicals NaOH, KOH, and Ca(OH)2 with distilled water to study the effect of C-S-H gel formation on fibers. The fibers are dipped in the solution for 35 days. The thermal properties of raw and SPS-dipped fibers are fetched out by performing various tests such as Fourier transform infrared (FTIR) analysis, thermo gravimetric analysis (TGA), differential scanning calorimetry analysis, and scanning electron microscopy (SEM). On analysis, the thermal properties of SPS-dipped fiber have better properties when compared with raw fiber. In FTIR analysis the first broad peak of both raw and SPS-dipped fibers are observed between 3000 cm−1 to 2800 cm−1 indicating that fibers have strong bond. In TGA analysis noted that the residual mass of raw fiber (77.19%) is higher than SPS-dipped fiber (52.33%) due to the formation of C-S-H gel formation. DSC analysis showed both endothermic and exothermic reaction under N2 atmosphere.

One of the main sources of dangerous chemicals that are dumped untreated into land and water bodies and have a negative influence on the ecosystem are industrial effluents. Seaweeds are currently used for treating industrial effluent effectively. The technology is at a maturing stage. This paper reviews the characterization and cultivation of seaweeds for wastewater treatment. In this present study, different extracts of four seaweeds such as Gracilaria edulis, Sargassum wightii, Turbinaria ornata, and Kappaphycus alvarezii, from the Mandapam coastal regions were analyzed. The seaweeds are used to treat the leather industry effluents collected from EKM leather processing company, Erode, Tamil Nadu, India. Among all, extracts of Gracilaria edulis survived at different concentrations of TDS: 15,000, 25000, and 35000 mg/l. Out of these different ranges, TDS of about 25000 mg/l seaweed named Gracilaria edulis reduced more amounts of chemicals present in the effluent like TDS (93.90%), phosphates (72.71%), nitrate (75.08%), nitrite (76.92%), and turbidity (99.01%) content. Additionally, we produce the quality and strength of agar gel from the cultivation of Gracilaria edulis by the Nikansui method. Finally, we got the extraction procedure to obtain a higher yield of about 10.26% and a maximum gel strength of 92.06 g·cm−2 while maintaining the melting point at 78°C.

The outer surface of the building is the same size as its premises, with greater heat loss. Therefore, when building, renovating, or expanding apartment, if possible, avoid all kinds of spaces, ledges, and lodges in the walls. It makes sense to build unheated exterior buildings on the north side of the apartment. The storage rooms for garden tools and bicycles, technical buildings protect the warm part of the house from wind and cold. In the most common design of a private apartment, the energy consumption for heating is 110-130 kW per 1 m2 per year. In this paper, an energy distribution model was proposed to estimate the photo energy with the help of deep learning model. A small apartment not only uses less energy but also requires lower construction costs. An energy-efficient apartment is a building with a low-energy consumption and comfortable microclimate. Energy savings in such homes can be up to 90%. Annual heat demand can be less than 15 kWh per square meter of energy-efficient home.

This paper aims to identify the optimum level of factors or parameters that affect the energy absorption of conoidal structures by grey relational examination. To optimize crashworthiness parameters of conical structures, the L9 orthogonal array has been adopted to design the experiments. The tailor-made thin-walled conical structures were fabricated by three most important factors, such as base diameter, height, and thickness, as design variables, and they were subjected to axial compression in a quasi-static method. The important responses of crashworthiness indicators such as the mean crushing force and specific energy absorption (SEA) were calculated with the help of a load-displacement curve. Experimental results showed that the crushing behaviours of conical structures were fairly significant. Grey relational analysis (GRA) and analysis of variance are used toobtain the optimal levels of parameters. From the results, the optimum levels of parameters are found to be a base diameter of 180 mm, a height of 120 mm, and a thickness of 1.5 mm.

Polyethylene and ferric oxide microparticles were mixed in this work to generate a new polymer composite. Weight fraction and microparticle size were studied experimentally to discover how they influenced the tensile strength and Young’s modulus. A response surface methodology was employed in the design of the research. The increased weight fraction of reinforcement results in the increase in Young’s modulus and lowers the elongation percentage. As the microparticles expanded in size, so did their effect on the composite’s mechanical characteristics. The tensile strength of specimens containing 20% ferric oxide and particle size of more than 91 µm was dropped by 18 percent due to the agglomeration of microparticles. The addition of 24% Fe2O3 microparticles smaller than 33 μm raised Young’s modulus and tensile strength by 340 percent and 65 percent, respectively.

Alternative methods for dissimilar metal joining particularly aluminium and copper have gain interest in manufacturing sectors. Friction stir spot welding was carried out on the AA6061 and C11000 wires of 2 mm diameter. This research paper reported the results on microstructures and mechanical properties of the spot-welded joints, and also special attention is provided for electrical resistivity of the welds. The microstructures reveal the information of grain structure and bonding. The width of diffusion layer significantly reduced with low dwell times. For a plunge depth of 1 mm, the maximum tensile strength (294 MPa) is achieved during the higher rotational speed (1400 rpm). For the same plunge depth, lower tensile strength values are exhibited by the joint produced using the lower rotational speed (800 rpm). Hardness of the weld region recorded 70 HV which is less than Cu (115 HV) and greater than Al (40 HV). FSSW joints (0.30 to 0.34 μΩ) offered higher range of electrical resistivity than that of base metal (0.02 μΩ). The results highlighted in this paper might be helpful for both academic researchers and industrialists.

In this paper, functions of BMS in elections vehicles are explained. The BMS consists of number of electronics components for monitoring and controlling the functions of batteries in electrical vehicles (EVs). Nowadays, the EV has more concentrations because it has number of merits like compact in size, does not require fossil fuel so it is environment friendly, and cost-saving. The main components in EV are batteries because batteries decide the performance and efficiency of EV. So, we should give more importance to batteries. Battery is controlled and monitored with the help of BMS. The BMS protects the battery and increases life time and efficiency due to charging discharging process.

Upland cotton encounters biotic and abiotic stresses during the growing season, which significantly affects the genetic potential of stress tolerance and productivity. The root-knot nematode (RKN) (Meloidogyne incognita) is a soilborne roundworm affecting cotton production. The occurrence of abiotic stress (drought stress, DS) can alter the plant–disease (RKN) interactions by enhancing host plant sensitivity. Experiments were conducted for two years under greenhouse conditions to investigate the effect of RKN and DS and their combination using nematode-resistant (Rk-Rn-1) and nematode susceptible (M8) cotton genotypes. These genotypes were subjected to four treatments: control (100% irrigation with no nematodes), RKN (100% irrigation with nematodes), DS (50% irrigation with no nematodes), and DS + RKN (50% irrigation with nematodes). We measured treatments-induced changes in cotton (i) leaf reflectance between 350 and 2500 nm; and (ii) physiology and biomass-related traits for diagnosing plant health under combined biotic and abiotic stresses. We used a maximum likelihood classification model of hyperspectral data with different dimensionality reduction techniques to learn RKN and DS stressors on two cotton genotypes. The results indicate (i) the RKN stress can be detected at an early stage of 10 days after infestation; (ii) RKN, DS, and DS + RKN can be detected with an accuracy of over 98% using bands from 350–1000 nm and 350–2500 nm. The genotypes ‘Rk-Rn-1’and ‘M8’ showed differential responses to DS, RKN, and DS + RKN. With a few exceptions, all three stressors reduced the pigments, physiology, and biomass traits and the magnitude of reduction was higher in ‘M8’ than ‘Rk-Rn-1’. Observed impact of stressors on plant growth followed DS + RKN > DS > RKN. Similarly, leaf reflectance properties exhibited a significant difference between individual stress treatments indicating that the hyperspectral sensor data can be used to discriminate RKN-infected plants from drought-stressed plants. Thus, our study reveals that hyperspectral and physiological changes in response to RKN and DS could help diagnose plant health before visual symptoms.

Abstract Background Rice (Oryza sativa L.) is one of the major staple food crops consumed globally. However, rice production is severely affected by high salinity levels, particularly at the seedling stage. A good solution would be the development of an efficient screening methodology to identify genotypes possessing genes for salt tolerance. Result A new salinity tolerance screening technique using rice seedlings in pot-culture was tested. This method controls soil heterogeneity by using pure sand as a growth medium and minimizes unexpected extreme weather conditions with a movable shelter. Seventy-four rice genotypes were screened at three salinity treatments including high salt stress (electrical conductivity (EC) 12 dSm− 1), moderate salt stress (EC 6 dSm− 1), and control (no salt stress), imposed 1 week after emergence. Several shoot and root morpho-physiological traits were measured at 37 days after sowing. A wide range of variability was observed among genotypes for measured traits with root traits being identified as the best descriptors for tolerance to salt stress conditions. Salt stress response indices (SSRI) were used to classify the 74 rice genotypes; 7 genotypes (9.46%) were identified as salt sensitive, 27 (36.48%) each as low and moderately salt tolerant, and 13 (17.57%) as highly salt tolerant. Genotypes FED 473 and IR85427 were identified as the most salt tolerant and salt sensitive, respectively. These results were further confirmed by principal component analysis (PCA) for accuracy and reliability. Conclusion Although tolerant genotypes still need to be confirmed in field studies and tolerance mechanisms identified at the molecular level, information gained from this study could help rice breeders and other scientists to accelerate breeding by selecting appropriate donor parents, progenies and potential genotypes at early growth stages necessary for salinity tolerance research.

Drought is one of the major abiotic stresses that limit soybean production worldwide. This study was conducted to determine whether soybean cultivars with divergent growth habits respond differently to drought stress at the vegetative growth stage regarding canopy reflectance, physiological, and gas exchange traits under controlled conditions. Soil moisture content was positively correlated with mid-day leaf water potential. Pooled over cultivar, photosynthesis and stomatal conductance were highly correlated with mid-day leaf water potential, while Ci/Ca exhibited a weak positive correlation. These data indicate that, regardless of cultivar, the decrease in net photosynthesis is mainly due to stomatal closure. For both cultivars, drought stress increased soybean canopy reflectance in the visible range of the spectrum but decreased reflectance in the near-infrared region. The quantified physiological traits would be useful to understand plant water relations and canopy structure to help soybean growers to make field management decisions during the growing season.

The nanoparticles are incorporated into the composite to mark their unique properties. This work investigates the hybrid epoxy nanocomposite and the impact of nanographite reinforcement. The composite was prepared by using a mechanical stirring technique. The amount of nanographite was added in different volumes, i.e., 1.0, 1.5, and 2.0 wt.%. Results of mechanical and dynamic loading properties were analyzed in accordance to the quantity of nano-G. The fiber and matrix interfacial bonding enrichments were evident in high-resolution SEM images-tensile fracture surface. Finally, the optimum content of nanoparticle which impacts the sample greatly was found to be 1.5 wt.%.

Let \(G\) be a graph with the vertex set \(V(G)\). A subset \(S\) of \(V(G)\) is an open packing set of \(G\) if every pair of vertices in \(S\) has no common neighbor in \(G.\) The maximum cardinality of an open packing set of \(G\) is the open packing number of \(G\) and it is denoted by \(\rho^o(G)\). In this paper, the exact values of the open packing numbers for some classes of perfect graphs, such as split graphs, \(\{P_4, C_4\}\)-free graphs, the complement of a bipartite graph, the trestled graph of a perfect graph are obtained.

Abstract Curcumin is a medicinal agent that exhibits anti-cancer properties and bioactive pigment in Turmeric has a huge therapeutic value. It has a keto-enol moiety that gives rise to many of its chemical properties. A recent study has shown that keto-enol tautomerisation at this moiety is implicated the effect of curcumin. The tautomerisation of curcumin in methanol, acetone and acetonitrile are used in nuclear magnetic resonance (1H, 13C) spectroscopy. It was characterized using UV, IR and Raman spectral values. The molecular electrostatic potential surface of the Curcumin has been visualized in electropositive potential in the region of the CH3+ group and most electronegative potential in the two oxygen atom has very strong binding group. In the following, the modality of structural and thermo dynamical parameters, electrophilicity (ω), chemical potential (μ), chemical hardness (η) and electronic charge transfer confirms the local reactivity. The rate constant of tautomerisation of curcumin shows strong temperature dependence. Molecular electrostatic potential and Temperature dependence of various thermodynamic properties like $$ \left( {{\hbox{C}}_{\rm{p,m}}^{0},\;{\hbox{S}}_{\rm{m}}^{0},\;{\hbox{and}}\;{\hbox{H}}_{\rm{m}}^{0} } \right) $$ Cp,m0,Sm0,andHm0 is increase with increase in temperature for monomer and dimer of various electrical fields.

Prosopis julifera is a non-edible feedstock found in the arid and semi-arid regions was used for the production of biodiesel. Solvent extraction technique was used for oil extraction from Prosopis julifera .The present work mainly concentrates on the three step process of biodiesel production from Prosopis julifera oil .The acid value of Prosopis julifera oil was reduced below 1% using acid catalyst 1% v/v H2SO4 followed by esterification process using alkaline catalyst (KOH).Transesterification reaction is found to be affected by the reaction variables namely methanol to oil molar ratio, amount of catalyst used, reaction time and reaction temperature. Gas chromatography was used to analyse the Fatty acid methyl esters. The methyl ester obtained from the previous step was refined to produce biodiesel. The fuel properties of Prosopis julifera methyl ester (PJME) such as viscosity, cetane number, flash point, acid value, etc were determined and compared according to the ASTM standards. The optimum reaction conditions of Methanol/oil molar ratio of 9:1v/v, reaction temperature of 550C, reaction time of 2 hrs and 0.75% w/v of KOH usage were determined. Response surface Methodology (RSM) technique was used to optimize the maximum yield of Prosopis julifera methyl ester.

Temporal and spatial variations in ozone levels and temporal changes in solar radiation greatly influence ultraviolet radiation incidence to crops throughout their growth, yet the interactive effects of CO2 and UV-B radiation on Basil production under sunlight environmental conditions has not been studied. Basil ‘Genovese’ plants grown under sunlit plant growth chambers were subjected to a combination of supplemental UV-B (0 and 10 kJ m−2d−1) and ambient (420 ppm) and elevated (720 ppm) CO2 treatments for 38 days after 14 days of germination. UV-B radiation treatments caused a decrease in basil stem branching, fresh mass, and stem dry mass under both CO2 treatments when harvested after 17 and 38 days of treatment. There was also an increase in basil leaf surface wax under UV-B (10 kJ m−2d−1) treatment compared to controls (0 kJ m−2d−1). Elevated CO2 treatments caused a decrease in morphological features, including specific leaf area and fresh mass. Interactive effects between UV-B and CO2 treatments existed for some morphological features, including plant height, root surface area, and average root diameter. Understanding the impacts that CO2 and UV-B radiation treatments have on basilcan improve existing varieties for increased tolerance while simultaneously improving yield, plant morphology, and physiology.

Short- and long-term waterlogging conditions impact crop growth and development, preventing crops from reaching their true genetic potential. Two experiments were conducted using a pot-culture facility to better understand soil waterlogging impacts on corn growth and development. Two corn hybrids were grown in 2017 and 2018 under ambient sunlight and temperature conditions. Waterlogging durations of 0, 2, 4, 6, 8, 10, 12, and 14 days were imposed at the V2 growth stage. Morphological (growth and development) and pigment estimation data were collected 15 days after treatments were imposed, 23 days after sowing. As waterlogging was imposed, soil oxygen rapidly decreased until reaching zero in about 8–10 days; upon the termination of the treatments, the oxygen levels recovered to the level of the 0 days treatment within 2 days. Whole-plant dry weight declined as the waterlogging duration increased, and after 2 days of waterlogging, a 44% and 27% decline was observed in experiments 1 and 2, respectively. Leaf area and root volume showed an exponential decay similar to the leaf and root dry weight. Leaf number and plant height were the least sensitive measured parameters and decreased linearly in both experiments. Root forks were the most sensitive parameter after 14 days of waterlogging in both experiments, declining by 83% and 80% in experiments 1 and 2, respectively. The data from this study improve our understanding of how corn plants react to increasing durations of waterlogging. In addition, the functional relationships generated from this study could enhance current corn simulation models for field applications.

Recent evidence suggests that the effects of temperature significantly affect the growth and development of basil plants with detrimental impacts on yield. The current research investigated the interactive effects of varying temperature and CO2 levels on the shoot and root morphology and growth of early and late-season basil plants. Basil plants were subjected to control (30/22 °C), low (20/12 °C), and high (38/30 °C) temperature under ambient (420 μL L−1) and elevated (720 μL L−1) CO2 concentrations. Decreasing the temperature to 20/12 °C caused more adverse effects on the morphological traits of the early-season basil. Relative to the control treatments, low- and high-temperature stresses decreased 71 and 14% in marketable fresh mass, respectively. Basil exhibited an increase in plant height, node and branch numbers, specific leaf area, anthocyanin and nitrogen balance index, root tips, and root crossings when subjected to high-temperature stress. Furthermore, elevated CO2 affected many morphological features compared to ambient CO2 concentrations. The findings of this study suggest that varying the growth temperature of basil plants would more significantly impact the shoot and root morphologies and growth rates of basil than increasing the CO2 concentrations, which ameliorated the adverse impacts of temperature stress.

Early season sowing is one of the methods for avoiding yield loss for basil due to high temperatures. However, basil could be exposed to sub-optimal temperatures by planting it earlier in the season. Thus, an experiment was conducted that examines how temperature changes and carbon dioxide (CO2) levels affect basil growth, development, and phytonutrient concentrations in a controlled environment. The experiment simulated temperature stress, low (20/12 °C), and high (38/30 °C), under ambient (420 ppm) and elevated (720 ppm) CO2 concentrations. Low-temperature stress prompted the rapid closure of stomata resulting in a 21% decline in net photosynthesis. Chlorophylls and carotenoids decreased when elevated CO2 interacted with low-temperature stress. Basil exhibited an increase in stomatal conductance, intercellular CO2 concentration, apparent quantum yield, maximum photosystem II efficiency, and maximum net photosynthesis rate when subjected to high-temperature stress. Under elevated CO2, increasing the growth temperature from 30/22 °C to 38/30 °C markedly increased the antioxidants content of basil. Taken together, the evidence from this research recommends that varying the growth temperature of basil plants can significantly affect the growth and development rates compared to increasing the CO2 concentrations, which mitigates the adverse effects of temperature stress.

Managing grasslands for forage and ground-nesting bird habitat requires appropriate defoliation strategies. Subsequent early-summer species composition in mixed stands of native warm-season grasses (Indiangrass (IG, Sorghastrum nutans), big bluestem (BB, Andropogon gerardii) and little bluestem (LB, Schizachyrium scoparium)) responding to harvest intervals (treatments, 30, 40, 60, 90 or 120 d) and durations (years in production) was assessed. Over three years, phased May harvestings were initiated on sets of randomized plots, ≥90 cm apart, in five replications (blocks) to produce one-, two- and three-year-old stands. Two weeks after harvest, the frequencies of occurrence of plant species, litter and bare ground, diagonally across each plot (line intercept), were compared. Harvest intervals did not influence proportions of dominant plant species, occurrence of major plant types or litter, but increased that of bare ground patches. Harvest duration increased the occurrence of herbaceous forbs and bare ground patches, decreased that of tall-growing forbs and litter, but without affecting that of perennial grasses, following a year with more September rainfall. Data suggest that one- or two-year full-season forage harvesting may not compromise subsequent breeding habitat for bobwhites and other ground-nesting birds in similar stands. It may take longer than a year’s rest for similar stands to recover from such changes in species composition.

Multiple-input Multiple-output (MIMO) radars benefit from spatial and waveform diversities to improve the performance potential. Phased array radars transmit scaled versions of a single waveform thereby limiting the transmit degrees of freedom to one. However MIMO radars transmit diverse waveforms from different transmit array elements thereby increasing the degrees of freedom to form flexible transmit beampatterns. The transmit beampattern of a colocated MIMO radar depends on the zero-lag correlation matrix of different transmit waveforms. Many solutions have been developed for designing the signal correlation matrix to achieve a desired transmit beampattern based on optimization algorithms in the literature. In this paper, a fast algorithm for designing the correlation matrix of the transmit waveforms is developed that allows the next generation radars to form flexible beampatterns in real-time. An efficient method for sidelobe control with negligible increase in mainlobe width is also presented.

Stainless steel (SS) is used for many commercial and industrial applications owing to its high resistance to corrosion. It is too hard to machine due to its high strength and high work hardening property. A surface property such as surface roughness (SR) is critical to the function-ability of machined components. SS is generally regarded as more difficult to machine material and poor SR is obtained during machining. In this paper an attempt has been made to investigate the SR produced by CNC turning on austenitic stainless steel (AISI316) and martensitic stainless steel (AISI410) by different cases of coated cutting tool used at dry conditions. Multilayered coated with TiCN/Al2O3, multilayered coated with Ti(C, N, B) and single layered coated with TiAlN coated cutting tools are used. Experiments were carried out by using Taguchi’s L27 orthogonal array. The effect of cutting parameters on SR is evaluated and optimum cutting conditions for minimizing the SR are determined. Analysis of variance (ANOVA) is used for identifying the significant parameters affecting the responses. Confirmation experiments are conducted to validate the results obtained from optimization.