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Developing new bread wheat varieties that can be successfully grown in saline conditions has become a pressing task for plant breeders. High-throughput phenotyping tools are crucial for this task. Proximal remote sensing is gaining popularity in breeding programs as a quick, cost-effective, and non-invasive tool to assess canopy structure and physiological traits in large genetic pools. Limited research has been conducted on the effectiveness of combining RGB and thermal imaging to assess the salt tolerance of different wheat genotypes. This study aimed to evaluate the effectiveness of combining several indices derived from thermal infrared and RGB images with artificial neural networks (ANNs) for assessing relative water content (RWC), chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophyll (Chlt), and plant dry weight (PDW) of 18 recombinant inbred lines (RILs) and their 3 parents irrigated with saline water (150 mM NaCl). The results showed significant differences in various traits and indices among the tested genotypes. The normalized relative canopy temperature (NRCT) index exhibited strong correlations with RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.50 to 0.73, 0.53 to 0.76, 0.68 to 0.84, 0.68 to 0.84, and 0.52 to 0.76, respectively. Additionally, there was a strong relationship between several RGB indices and measured traits, with the highest R2 values reaching up to 0.70. The visible atmospherically resistant index (VARI), a popular index derived from RGB imaging, showed significant correlations with NRCT, RWC, Chla, Chlb, Chlt, and PDW, with R2 values ranging from 0.49 to 0.62 across two seasons. The different ANNs models demonstrated high predictive accuracy for NRCT and other measured traits, with R2 values ranging from 0.62 to 0.90 in the training dataset and from 0.46 to 0.68 in the cross-validation dataset. Thus, our study shows that integrating high-throughput digital image tools with ANN models can efficiently and non-invasively assess the salt tolerance of a large number of wheat genotypes in breeding programs. [ABSTRACT FROM AUTHOR]

Assessment of the salt tolerance of a large genotype collection at the early growth stages may assist in the fast-tracking improvement of salt-tolerant barley genotypes in breeding programs. This study aimed to investigate the ability of traits related to seed germination ability and seedling growth performance with helping of nine sequence-related amplified polymorphism (SRAP) markers to detect the salt tolerance of 70 barley genotypes during the early growth stages. The different genotypes were exposed to three salt concentrations (0, 100, and 200 mM NaCl) and evaluated for salt tolerance by looking at germination percentage, germination index, and mean germination time during eight days as well as the lengths and weights of seedling shoot and root after 21 days from sowing. The results showed that genotypic variations in germination ability and seedling growth performance obviously appeared under 200 and 100 mM NaCl, respectively. The germination traits exhibited a strong correlation among themselves, whereas they had a poor correlation with seedling traits. A strong and positive correlation was only observed for shoot fresh weight with shoot length and root fresh weight under salinity conditions. Principal component analysis revealed that the first two components, which explained 53% of the total variability, succeeded to identify the genotypes with high salt tolerance during only one stage (germination or seedling stage) and both stages. Cluster analysis based on the stress tolerance index of germination and seedling traits grouped 70 genotypes into four key clusters, with genotypes grouped in cluster 1 and cluster 2 being salt tolerant during the germination stage and moderately tolerant during the seedling stage; the opposite was found with the genotypes grouped in cluster 4. According to Ward's method, the salt tolerance of genotypes that ranked as most salt-tolerant (T) or salt-sensitive (S) remained almost unchanged during germination and seedling stages. In contrast, a change in salt tolerance with both stages was found for the genotypes that ranked as moderately salt-tolerant (MT) and salt-sensitive (MS) genotypes. The nine SRAP markers divided the tested genotypes into two distinct clusters, with clusters B had the most T and MT genotypes. Finally, using appropriate statistical methods presented in this study with SRAP markers will be useful for assessing the salt tolerance of a large number of barley genotypes and selecting the genotypes tolerant of and sensitive to salinity at the early growth stage. [ABSTRACT FROM AUTHOR]

Successfully evaluating and improving the salt tolerance of genotypes requires an appropriate analysis tool to allow simultaneous analysis of multiple traits and to facilitate the ranking of genotypes across different growth stages and salinity levels. In this study, we evaluate the salt tolerance of 56 recombinant inbred lines (RILs) in the presence of salt-tolerant and salt-sensitive control genotypes using multivariate analysis of plant dry weight, measured at 75 (PDW-75) and 90 (PDW-90) days from sowing, biological yield (BY), grain yield (GY), and their salt tolerance indices (STIs). All RILs and genotypes were evaluated under the control and 15 dS m−1 for two consecutive years (2019/2020 and 2020/2021). Results showed significant main effects of salinity and genotype as well as their interactions on four plant traits. Significant genotypic differences were also found for all calculated STIs. STIs exhibited moderate to strong relationships with the four plant traits when measured under either the control or salinity conditions and between each other. The principal component analysis (PCA) showed that the most variation among all analyzed variables was explained by the first two PCs, with the PC1 and PC2 explained at 61.8–71.8% and at 28.0–38.2% of the total variation, respectively. The PC1 had positive and strong correlations with the four plant traits measured under salinity conditions and STI, YI, REI, SWPI, MRPI, MPI, GMPI, and HMPI. The PC2 had strong correlations with BY and GY measured under the control conditions and SSI, TOL, RSE, and YSI. The PC1 was able to identify the salt-tolerant genotypes, while the PC2 was able to isolate the salt-sensitive ones. Cluster analysis based on multiple traits organized 64 genotypes into four groups varied from salt-tolerant to salt-sensitive genotypes, with the salt-tolerant group attaining higher value for plant traits under salinity conditions and the STIs related to the PC1. In conclusion, the use of multivariate analysis together with the STIs that evaluated the performance of genotypes under contrasting environmental conditions will help breeders to distinguish salt-tolerant genotypes from salt-sensitive ones, even at the early growth stages of plant development. [ABSTRACT FROM AUTHOR]

A 1 × 4 planar fractal array antenna is designed and presented for millimeter-wave 5G applications. The array's top side is made up of a rhombus-inscribed circular ring fractal patch radiator, while the backside is made up of a square notch-loaded partial ground plane. To achieve high gain, a 1 × 4 corporate feeding network is used to excite the array elements. The designed array has an overall size of 28 × 17.75 mm2. From simulations as well as experimental results, it is observed that the designed array offers a wide impedance bandwidth in the frequency range of 22.8–29.2 GHz. Furthermore, a peak gain of 10.7 dBi with a radiation efficiency of > 95% is observed in the operating bandwidth. [ABSTRACT FROM AUTHOR]

An area of growing interest in wheat-breeding programs for abiotic stresses is the accurate and expeditious phenotyping of large genotype collections using nondestructive hyperspectral sensing tools. The main goal of this study was to use data from canopy spectral signatures (CSS) in the full-spectrum range (400–2500 nm) to estimate and predict the plant biomass dry weight at booting (BDW-BT) and anthesis (BDW-AN) growth stages, and biological yield (BY) of 64 spring wheat germplasms exposed to 150 mM NaCl using 13 spectral reflectance indices (SRIs, consisting of seven vegetation-related SRIs and six water-related SRIs) and partial least squares regression (PLSR). SRI and PLSR performance in estimating plant traits was evaluated during two years at BT, AN, and early milk grain (EMG) growth stages. Results showed significant genotypic differences between the three traits and SRIs, with highly significant two-way and three-way interactions between genotypes, years, and growth stages for all SRIs. Genotypic differences in CSS and the relationships between the three traits and a single wavelength over the full-spectrum range depended on the growth stage. Water-related SRIs were more strongly correlated with the three traits compared with vegetation-related SRIs at the BT stage; the opposite was found at the EMG stage. Both types of SRIs exhibited comparable associations with the three traits at the AN stage. Principal component analysis indicated that it is possible to assess plant biomass variations at an early stage (BT) through published and modified SRIs. SRIs coupled with PLSR models at the BT stage exhibited good prediction capacity of BDW-BT (57%), BDW-AN (82%), and BY (55%). Overall, results demonstrated that the integration of SRIs and multivariate models may present a feasible tool for plant breeders to increase the efficiency of the evaluation process and to improve the genetics for salt tolerance in wheat-breeding programs. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19), also known as Severe acute respiratory syndrome (SARS-COV2) and it has imposed deep concern on public health globally. Based on its fast-spreading breakout among the people exposed to the wet animal market in Wuhan city of China, the city was indicated as its origin. The symptoms, reactions, and the rate of recovery shown in the coronavirus cases worldwide have been varied . The number of patients is still rising exponentially, and some countries are now battling the third wave. Since the most effective treatment of this disease has not been discovered so far, early detection of potential COVID-19 patients can help isolate them socially to decrease the spread and flatten the curve. In this study, we explore state-of-the-art research on coronavirus disease to determine the impact of this illness among various age groups. Moreover, we analyze the performance of the Decision tree (DT), K-nearest neighbors (KNN), Naïve bayes (NB), Support vector machine (SVM), and Logistic regression (LR) to determine COVID-19 in the patients based on their symptoms. A dataset obtained from a public repository was collected and pre-processed, before applying the selected Machine learning (ML) algorithms on them. The results demonstrate that all the ML algorithms incorporated perform well in determining COVID-19 in potential patients. NB and DT classifiers show the best performance with an accuracy of 93.70%, whereas other algorithms, such as SVM, KNN, and LR, demonstrate an accuracy of 93.60%, 93.50%, and 92.80% respectively. Hence, we determine that ML models have a significant role in detecting COVID-19 in patients based on their symptoms. [ABSTRACT FROM AUTHOR]

In this work, peels of citrus mandarin cultivars, that is, Kinnow and Feutrell's Early were studied and compared for their nutritional composition. The impact of microwave treatment was investigated on selected minerals, vitamins, sugars, and amino acids of the citrus peels. The results showed a great variation in the nutrients of both citrus mandarin cultivar peels. With few exceptions, the mineral content of citrus peels was increased after microwave heating. Calcium was increased by 5.9% and 24.2% of its original content in the peels of Kinnow and Feutrell's Early, respectively. Sodium was increased in Kinnow peels, but it decreased by about 25.4% in Feutrell's Early peels after microwave treatment. With few exemptions, in general, the vitamin, sugar, and amino acid contents were decreased in microwave-treated samples. The exploration of the exact mechanism of nutrient changes in citrus peels on microwave heating can serve the basis for further research. [ABSTRACT FROM AUTHOR]

The phenolic constituents usually exist in free and covalently bound forms in the plant materials. This study reports the impact of microwave heating on certain phenolic compounds and antioxidant potential assessed by free radical‐scavenging and reducing power of citrus peels. Different levels of microwave power (125, 250, 500 W) and heating times (5, 10, 15 min) were applied. The phenolic acids were fractionated into three forms namely; free, glycoside‐bound, and ester‐bound. Microwave power and heating time significantly increased the content of free phenolic fraction while the content of bound fractions decreased. Increasing microwave power significantly increased the antioxidant activity of heated samples. The microwave heating up to 10 min at 250 W increased the antioxidant activity of the samples but further heating to 15 min exerted an adverse effect. A moderate microwave power and heating time was helpful for improving the antioxidant potential of citrus peels. Practical applications: A very simple method is used in this study to release the bound phenolics and to improve the antioxidant potential of citrus peels, thereby, maximizing the use of fruit byproducts in general and citrus peels in particular. By this way, it can be helpful to decrease the environmental pollution caused by citrus fruit waste products. The use of microwave heating might be helpful for the citrus processing industry to minimize the loss in terms of effluent management. It might be an economical processing technique for the pharmaceutical and functional food sector. [ABSTRACT FROM AUTHOR]

In the petroleum industry, the researchers have developed a new technique called enhanced oil recovery to recover the remaining oil in reservoirs. Some reservoirs are very complex and require advanced enhanced oil recovery (EOR) techniques containing new materials and additives in order to produce maximum oil in economic and environmental friendly manners. In this work, the effects of nanosuspensions (KY-200) and polymer gel HPAM (854) on oil recovery and water cut were studied in the view of EOR techniques and their results were compared. The mechanism of nanosuspensions transportation through the sand pack was also discussed. The adopted methodology involved the preparation of gel, viscosity test, and core flooding experiments. The optimum concentration of nanosuspensions after viscosity tests was used for displacement experiments and 3 wt % concentration of nanosuspensions amplified the oil recovery. In addition, high concentration leads to more agglomeration; thus, high core plugging takes place and diverts the fluid flow towards unswept zones to push more oil to produce and decrease the water cut. Experimental results indicate that nanosuspensions have the ability to plug the thief zones of water channeling and can divert the fluid flow towards unswept zones to recover the remaining oil from the reservoir excessively rather than the normal polymer gel flooding. The injection pressure was observed higher during nanosuspension injection than polymer gel injection. The oil recovery was achieved by about 41.04% from nanosuspensions, that is, 14.09% higher than polymer gel. Further investigations are required in the field of nanoparticles applications in enhanced oil recovery to meet the world's energy demands. [ABSTRACT FROM AUTHOR]

Surfactant and polymer flooding are the vital techniques used in petroleum industry to enhance the oil recovery. Development and advancement in such techniques has occurred time by time to overcome the challenges of oil and gas recovery. However, micro-fluid chips and its development provide a new way to understand the real time behavior of fluid-flow in porous media. The essence of this study has been achieved by collecting the information from literature studies and sorted the useful information organize the pattern of micromodels chip revolution. In this study, first precise review is conducted by the innovations of micromodel chips into timescale from 1952 till date. Second, advancement in micromodel chip technology is included based on different periods of time where micromodel chips have evolved from chip design to nanoscale visualization of chips. Third, some recommendations are proposed based on evolution of micromodel chip technology that it not only requires less time but also minimizing the massive experimental set-up and complications. The overall finding of this research propose that in current times some micro-fluidic reforms made recently has played versatile role in improving injection chemical selection and similar improvements are expected to be developed in near future. [ABSTRACT FROM AUTHOR]

Many years have passed in oil field development but primary challenges faced by the X reservoir are the rapid decline of formation pressure and the significant solution gas released from the formation, which impairs production. Based on these challenges, a compositional simulation model of the X reservoir was constructed and run to establish the future development plans. The basic reservoir data collection and processing, quality assurance of the data, characteristic pressure-volume-temperature (PVT) matching by ECLIPSE PVTi, and simulation of various adjustment strategies to forecast development plans, as well as data sensitivity analysis and optimization has been included in this study. In addition, to establish a desirable development plan, the simulation model is set-up in great consistency with the geological model resulted from the seismic and logging interpretations. Also, emphases are paid on establishing matches with the reported lab data from production wells by PVTi. Results revealed that the specific reservoir development plan intends to reinstate or maintain formation pressure of the X reservoir. All design and optimization studies are set to comprehend the reservoir with the numerical model. [ABSTRACT FROM AUTHOR]

Maillard reaction intermediate (MGX) generated from glutathione and xylose in aqueous medium was prepared via the Maillard reaction performed under a two‐stage temperature increase process. The purified MGX was identified by Fourier‐transform infrared spectroscopy, mass spectrometry, and nuclear magnetic resonance as N‐(1‐deoxy‐d‐xylulos‐1‐yl)‐glutathione (Amadori compound, C15H25O10N3S) with five main isomers. The method of Maillard reaction performed under a two‐stage temperature increase process was further verified by high‐performance liquid chromatography. The optimal reaction time and temperature for the preparation of MGX was determined as 60 min at 90 °C. The yield of MGX was increased from 8.60% to 55.52% through thermal reaction coupled with vacuum dehydration. In addition, rapid and more Maillard‐type volatile compounds were formed in MGX during thermal treatment than that in Maillard reaction products or glutathione‐xylose mixture. Beside, MGX possessed more pleasing meat‐like volatile profile compared with the Amadori compound of glutamic acid‐xylose (AAX), cysteine‐xylose (ACX), and glycine‐xylose (AGX). Therefore, it suggested that the MGX had the potential to achieve a better flavor formation during thermal treatment. Practical Application: Maillard reaction intermediates, such as Amadori or Heyns rearrangement products (ARP or HRP), are important flavor precursors, which possess stable physicochemical properties, but tend to degrade into flavor compounds at high temperatures. Maillard reaction intermediate from glutathione and xylose acts as primary flavor enhancers to complete Maillard reaction to produce flavors in the subsequent thermal processing, which can significantly improve and stabilize the flavor quality of the meaty food, and deserves a very broad application prospects. The new developed method will be a significant theoretical basis on research preparation and properties of Maillard reaction intermediates in complex food systems. [ABSTRACT FROM AUTHOR]

Amadori rearrangement product (ARP) derived from glutamic acid (Glu) and xylose (Xyl) was prepared by aqueous Maillard reaction. Subsequently, ion exchange chromatography, MS, and NMR were used for purification and identification, confirming that the molecular formula of ARP was C10H17NO8, namely N‐(1‐deoxy‐α‐D‐xylulos‐1‐yl)‐glutamic acid, with a molecular mass of 279 Da. To improve the aqueous yield of ARP, a thermal reaction coupled with vacuum dehydration was used and the yield of ARP was increased from 2.07% to 75.11%. Furthermore, flavor formation capacity of ARP by a thermal treatment simulated to a baking process was compared with Maillard reaction products, Maillard‐dehydration reaction products, and Glu‐Xyl mixture. The results indicated that a larger amount of volatile flavor compounds and a biscuit‐like, burnt aroma was generated rapidly from the mixture of ARP and unreacted Glu‐Xyl, which could be a potential flavor enhancer for baked foods. Practical Application: Maillard reaction performed in aqueous medium through thermal reaction combined with vacuum dehydration is a novel and practical technology that could be widely used to produce Maillard reaction intermediates (MRIs), such as Amadori or Heyns rearrangement products, which are regarded as significant nonvolatile aroma precursors and have stable physical and chemical properties compared with Maillard reaction products (MRPs). MRI derived from glutamic acid and xylose is a potential substitute of MRPs for flavorings preparation and shows a great capacity to generate fresh flavors in a short time at high temperature, which meets the requirements of baking foods. Therefore, the new developed method could be a promising tool for MRI preparation and application in food and flavoring industries. [ABSTRACT FROM AUTHOR]

Although plant chlorophyll (Chl) is one of the important elements in monitoring plant stress and reflects the photosynthetic capacity of plants, their measurement in the lab is generally time- and cost-inefficient and based on a small part of the leaf. This study examines the ability of canopy spectral reflectance data for the accurate estimation of the Chl content of two wheat genotypes grown under three salinity levels. The Chl content was quantified as content per area (Chl area, μg cm−2), concentration per plant (Chl plant, mg plant−1), and SPAD value (Chl SPAD). The performance of spectral reflectance indices (SRIs) with different algorithm forms, partial least square regression (PLSR), and stepwise multiple linear regression (SMLR) in estimating the three units of Chl content was compared. Results show that most indices within each SRI form performed better with Chl area and Chl plant and performed poorly with Chl SPAD. The PLSR models, based on the four forms of SRIs individually or combined, still performed poorly in estimating Chl SPAD, while they exhibited a strong relationship with Chl plant followed by Chl area in both the calibration (Cal.) and validation (Val.) datasets. The SMLR models extracted three to four indices from each SRI form as the most effective indices and explained 73–79%, 80–84%, and 39–43% of the total variability in Chl area, Chl plant, and Chl SPAD, respectively. The performance of the various predictive models of SMLR for predicting Chl content depended on salinity level, genotype, season, and the units of Chl content. In summary, this study indicates that the Chl content measured in the lab and expressed on content (μg cm−2) or concentration (mg plant−1) can be accurately estimated at canopy level using spectral reflectance data. [ABSTRACT FROM AUTHOR]

Medicinal plants play a key role in preventing various diseases. Hyperlipidemia is a major contributor to the pathogenesis of cardiovascular diseases. The purpose of the present study was to assess the effect of aqueous extract of Carum carvi seeds in diet induced hyperlipidemia in rats. 2% cholesterol diet were given to rats for six weeks and rats showed high lipid levels were included in the study. Then all rats were divided into, normal control group (A), hyperlipidemia positive control group (B), and the remaining two groups (C and D) served as experimental groups. Group C hyperlipidemic experimental rats received aqueous dried extract of Carum carvi seeds at 60 mg/kg of body weight for eight weeks on daily basis. On the other hand group D rats received simvastatin at 1.0 mg/kg body weight for eight weeks. Blood samples were collected after eight weeks. The hyperlipidemic positive control group rats showed variable increase in serum triglycerides, LDL and total cholesterol levels. Serum HDL levels decreased in hyperlipidemic positive control groups. Carum carvi and simvastatin significantly decreased the levels of these parameters in rats. On comparison Carum carvi reduced lipid levels more, effectively than the simvastatin. Carum carvi constituents, especially flavonoids and carvone have strong anti-oxidant activity which might be involved in hypolipidemia. In conclusion, Carum carvi aqueous seeds extract decrease lipid levels in diet induced hyperlipidemic rats. [ABSTRACT FROM AUTHOR]

The incorporation of stress tolerance indices (STIs) with the early estimation of grain yield (GY) in an expeditious and nondestructive manner can enable breeders for ensuring the success of genotype development for a wide range of environmental conditions. In this study, the relative performance of GY for sixty-four spring wheat germplasm under the control and 15.0 dS m−1 NaCl were compared through different STIs, and the ability of a hyperspectral reflectance tool for the early estimation of GY and STIs was assessed using twenty spectral reflectance indices (SRIs; 10 vegetation SRIs and 10 water SRIs). The results showed that salinity treatments, genotypes, and their interactions had significant effects on the GY and nearly all SRIs. Significant genotypic variations were also observed for all STIs. Based on the GY under the control (GYc) and salinity (GYs) conditions and all STIs, the tested genotypes were classified into three salinity tolerance groups (salt-tolerant, salt-sensitive, and moderately salt-tolerant groups). Most vegetation and water SRIs showed strong relationships with the GYc, stress tolerance index (STI), and geometric mean productivity (GMP); moderate relationships with GYs and sometimes with the tolerance index (TOL); and weak relationships with the yield stability index (YSI) and stress susceptibility index (SSI). Obvious differences in the spectral reflectance curves were found among the three salinity tolerance groups under the control and salinity conditions. Stepwise multiple linear regressions identified three SRIs from each vegetation and water SRI as the most influential indices that contributed the most variation in the GY. These SRIs were much more effective in estimating the GYc (R2 = 0.64 − 0.79) than GYs (R2 = 0.38 − 0.47). They also provided a much accurate estimation of the GYc and GYs for the moderately salt-tolerant genotype group; YSI, SSI, and TOL for the salt-sensitive genotypes group; and STI and GMP for all the three salinity tolerance groups. Overall, the results of this study highlight the potential of using a hyperspectral reflectance tool in breeding programs for phenotyping a sufficient number of genotypes under a wide range of environmental conditions in a cost-effective, noninvasive, and expeditious manner. This will aid in accelerating the development of genotypes for salinity conditions in breeding programs. [ABSTRACT FROM AUTHOR]

Advances in proximal hyperspectral sensing tools, chemometric techniques, and data-driven modeling have enhanced precision irrigation management by facilitating the monitoring of several plant traits. This study investigated the performance of remote sensing indices derived from thermal and red-green-blue (RGB) images combined with stepwise multiple linear regression (SMLR) and an integrated adaptive neuro-fuzzy inference system with a genetic algorithm (ANFIS-GA) for monitoring the biomass fresh weight (BFW), biomass dry weight (BDW), biomass water content (BWC), and total tuber yield (TTY) of two potato varieties under 100%, 75%, and 50% of the estimated crop evapotranspiration (ETc). Results showed that the plant traits and indices varied significantly between the three irrigation regimes. Furthermore, all of the indices exhibited strong relationships with BFW, CWC, and TTY (R2 = 0.80–0.92) and moderate to weak relationships with BDW (R2 = 0.25–0.65) when considered for each variety across the irrigation regimes, for each season across the varieties and irrigation regimes, and across all data combined, but none of the indices successfully assessed any of the plant traits when considered for each irrigation regime across the two varieties. The SMLR and ANFIS-GA models gave the best predictions for the four plant traits in the calibration and testing stages, with the exception of the SMLR testing model for BDW. Thus, the use of thermal and RGB imaging indices with ANFIS-GA models could be a practical tool for managing the growth and production of potato crops under deficit irrigation regimes. [ABSTRACT FROM AUTHOR]

Simultaneous and timely assessment of growth and water status-related plant traits is critical for precision irrigation management in arid regions. Here, we used proximal hyperspectral sensing tools to estimate biomass fresh weight (BFW), biomass dry weight (BDW), canopy water content (CWC), and total tuber yield (TTY) of two potato varieties irrigated with 100%, 75%, and 50% of the estimated crop evapotranspiration (ETc). Plant traits were assessed remotely using published and newly constructed vegetation and water spectral reflectance indices (SRIs). We integrated genetic algorithm (GA) and adaptive neuro-fuzzy inference system (ANFIS) models to predict the measured traits based on all SRIs. The different plant traits and SRIs varied significantly (p < 0.05) between the three irrigation regimes for the two varieties. The values of plant traits and majority SRIs showed a continuous decrease from the 100% ETc to the 50% ETc. Water-SRIs performed better than vegetation-SRIs for estimating the four plant traits. Almost all indices of the two SRI types had a weak relationship with the four plant traits (R2 = 0.00–0.37) under each irrigation regime. However, the majority of vegetation-SRIs and all water-SRIs showed strong relationships with BFW, CWC, and TTY (R2 ≥ 0.65) and moderate relationships with BDW (R2 ≥ 0.40) when the data of all irrigation regimes and varieties were analyzed together for each growing season or the data of all irrigation regimes, varieties, and seasons were combined together. The ANFIS-GA model predicted plant traits with satisfactory accuracy in both calibration (R2 = 1.0) and testing (R2 = 0.72–0.97) modes. The results indicate that SRI-based ANFIS models can improve plant trait estimation. This analysis also confirmed the benefits of applying GA to ANFIS to estimate plant responses to different growth conditions. [ABSTRACT FROM AUTHOR]

Sustainable agriculture in arid regions necessitates that the quality of groundwater be carefully monitored; otherwise, low-quality irrigation water may cause soil degradation and negatively impact crop productivity. This study aimed to evaluate the quality of groundwater samples collected from the wells in the quaternary aquifer, which are located in the Western Desert (WD) and the Central Nile Delta (CND), by integrating a multivariate analysis, proximal remote sensing data, and data-driven modeling (adaptive neuro-fuzzy inference system (ANFIS) and support vector machine regression (SVMR)). Data on the physiochemical parameters were subjected to multivariate analysis to ease the interpretation of groundwater quality. Then, six irrigation water quality indices (IWQIs) were calculated, and the original spectral reflectance (OSR) of groundwater samples were collected in the 302–1148 nm range, with the optimal spectral wavelength intervals corresponding to each of the six IWQIs determined through correlation coefficients (r). Finally, the performance of both the ANFIS and SVMR models for evaluating the IWQIs was investigated based on effective spectral reflectance bands. From the multivariate analysis, it was concluded that the combination of factor analysis and principal component analysis was found to be advantageous to examining and interpreting the behavior of groundwater quality in both regions, as well as predicting the variables that may impact groundwater quality by illuminating the relationship between physiochemical parameters and the factors or components of both analyses. The analysis of the six IWQIs revealed that the majority of groundwater samples from the CND were highly suitable for irrigation purposes, whereas most of the groundwater from the WD can be used with some limitations to avoid salinity and alkalinity issues in the long term. The high r values between the six IWQIs and OSR were located at wavelength intervals of 302–318, 358–900, and 1074–1148 nm, and the peak value of r for these was relatively flat. Finally, the ANFIS and SVMR both obtained satisfactory degrees of model accuracy for evaluating the IWQIs, but the ANFIS model (R2 = 0.74–1.0) was superior to the SVMR (R2 = 0.01–0.88) in both the training and testing series. Finally, the multivariate analysis was able to easily interpret groundwater quality and ground-based remote sensing on the basis of spectral reflectance bands via the ANFIS model, which could be used as a fast and low-cost onsite tool to estimate the IWQIs of groundwater. [ABSTRACT FROM AUTHOR]

The application of proximal hyperspectral sensing, using simple vegetation indices, offers an easy, fast, and non-destructive approach for assessing various plant variables related to salinity tolerance. Because most existing indices are site- and species-specific, published indices must be further validated when they are applied to other conditions and abiotic stress. This study compared the performance of various published and newly constructed indices, which differ in algorithm forms and wavelength combinations, for remotely assessing the shoot dry weight (SDW) as well as chlorophyll a (Chla), chlorophyll b (Chlb), and chlorophyll a+b (Chlt) content of two wheat genotypes exposed to three salinity levels. Stepwise multiple linear regression (SMLR) was used to extract the most influential indices within each spectral reflectance index (SRI) type. Linear regression based on influential indices was applied to predict plant variables in distinct conditions (genotypes, salinity levels, and seasons). The results show that salinity levels, genotypes, and their interaction had significant effects (p ≤ 0.05 and 0.01) on all plant variables and nearly all indices. Almost all indices within each SRI type performed favorably in estimating the plant variables under both salinity levels (6.0 and 12.0 dS m−1) and for the salt-sensitive genotype Sakha 61. The most effective indices extracted from each SRI type by SMLR explained 60%–81% of the total variability in four plant variables. The various predictive models provided a more accurate estimation of Chla and Chlt content than of SDW and Chlb under both salinity levels. They also provided a more accurate estimation of SDW than of Chl content for salt-tolerant genotype Sakha 93, exhibited strong performance for predicting the four variables for Sakha 61, and failed to predict any variables under control and Chlb for Sakha 93. The overall results indicate that the simple form of indices can be used in practice to remotely assess the growth and chlorophyll content of distinct wheat genotypes under saline field conditions. [ABSTRACT FROM AUTHOR]

Proximal hyperspectral sensing tools could complement and perhaps replace destructive traditional methods for accurate estimation and monitoring of various morpho-physiological plant indicators. In this study, we assessed the potential of thermal imaging (TI) criteria and spectral reflectance indices (SRIs) to monitor different vegetative growth traits (biomass fresh weight, biomass dry weight, and canopy water mass) and seed yield (SY) of soybean exposed to 100%, 75%, and 50% of estimated crop evapotranspiration (ETc). These different plant traits were evaluated and related to TI criteria and SRIs at the beginning bloom (R1) and full seed (R6) growth stages. Results showed that all plant traits, TI criteria, and SRIs presented significant variations (p < 0.05) among irrigation regimes at both growth stages. The performance of TI criteria and SRIs for assessment of vegetative growth traits and SY fluctuated when relationships were analyzed for each irrigation regime or growth stage separately or when the data of both conditions were combined together. TI criteria and SRIs exhibited a moderate to strong relationship with vegetative growth traits when data from different irrigation regimes were pooled together at each growth stage or vice versa. The R6 and R1 growth stages are suitable for assessing SY under full (100% ETc) and severe (50% ETc) irrigation regimes, respectively, using SRIs. The overall results indicate that the usefulness of the TI and SRIs for assessment of growth, yield, and water status of soybean under arid conditions is limited to the growth stage, the irrigation level, and the combination between them. [ABSTRACT FROM AUTHOR]

Field-based trials and genotype evaluation until yielding stage are two important steps in improving the salt tolerance of crop genotypes and identifying what parameters can be strong candidates for the better understanding of salt tolerance mechanisms in different genotypes. In this study, the salt tolerance of 18 bread wheat genotypes was evaluated under natural saline field conditions and at three saline irrigation levels (5.25, 8.35, and 11.12 dS m−1) extracted from wells. Multidimensional evaluation for salt tolerance of these genotypes was done using a set of agronomic and physio-biochemical attributes. Based on yield index under three salinity levels, the genotypes were classified into four groups ranging from salt-tolerant to salt-sensitive genotypes. The salt-tolerant genotypes exhibited values of total chlorophyll, gas exchange (net photosynthetic rate, transpiration rate, and stomatal conductance), water relation (relative water content and membrane stability index), nonenzymatic osmolytes (soluble sugar, free proline, and ascorbic acid), antioxidant enzyme activities (superoxide dismutase, catalase, and peroxidase), K+ content, and K+/Na+ ratio that were greater than those of salt-sensitive genotypes. Additionally, the salt-tolerant genotypes consistently exhibited good control of Na+ and Cl− levels and maintained lower contents of malondialdehyde and electrolyte leakage under high salinity level, compared with the salt-sensitive genotypes. Several physio-biochemical parameters showed highly positive associations with grain yield and its components, whereas negative association was observed in other parameters. Accordingly, these physio-biochemical parameters can be used as individual or complementary screening criteria for evaluating salt tolerance and improvement of bread wheat genotypes under natural saline field conditions. [ABSTRACT FROM AUTHOR]

Hyperspectral reflectance sensing provides a rapid and cost-effective technique for assessing the suitability of groundwater for irrigation by monitoring real-time changes in its quality at a large scale. In this study, we assessed the quality of 15 groundwater samples from El Fayoum depression in the Western Desert (WD) and 25 groundwater samples from the Central Nile Delta (CND) in Egypt using a traditional approach of the physiochemical parameters, irrigation water quality indicators (IWQIs), and hydrochemical facies. The spectral reflectance data of the water surface was used to build new simple reflectance indices (SRIs), and the performance of these indices for assessing IWQIs was compared with those by partial least square regression (PLSR) that was based on all SRIs or the full-spectrum ranges. Generally, the groundwater of the CND was fresher and more suitable for irrigation purposes than those of the WD. Based on the six IWQIs, ~6.7–60.0% and 85.0–100.0% of the groundwater samples of the WD and CND, respectively, were categorized as highly suitable for irrigation purposes. Based on hydrochemical facies, Na-Cl and Ca-HCO3 were dominant in the WD and CND, respectively, as well as the alkali earth metals (Na+ + K+), which significantly exceeded the alkaline earth metals (Ca2+ + Mg2+) in the WD, with the reverse for the CND. Most developed SRIs had a moderate, weak, and moderate to strong relationship with physiochemical parameters and IWQIs in the WD, CND, and across both regions, respectively. The PLSR models based on all SRIs provided a more accurate estimation of IWQIs in calibration and validation datasets than those based on full-spectrum ranges, and both PLSR models provided better estimation than the individual SRIs. These findings support the feasibility of using ground reflectance measurements as a fast and low-cost tool for the assessment and management of groundwater for irrigation in arid and semiarid regions. [ABSTRACT FROM AUTHOR]

Progress in high-throughput tools has enabled plant breeders to increase the rate of genetic gain through multidimensional assessment of previously intractable traits in a fast and nondestructive manner. This study investigates the potential use of spectral reflectance indices (SRIs; 15 vegetation-SRIs; 15 water-SRIs) as alternative selection tools for destructively measured traits in wheat breeding programs. The genetic variability, heritability (h2), genetic gain (GG), and expected genetic advances (GA) of these indices were compared with those of destructively measured traits in 43 F7-8 recombinant inbred lines (RILs) grown under limited water conditions. The performance of SRIs to estimate the destructively measured traits directly was also evaluated using the partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) models. Most vegetation-SRIs exhibited high genotypic variation, similar to the measured traits, and phenotypic correlations with these traits, compared with the water-SRIs. Most vegetation-SRIs presented comparable values for h2 (>60%) and GG (>20%) as intermediate traits, while about half of water-SRIs exhibited a high h2 (>60%), but low GG (<20%). Principle component analysis revealed that most vegetation-SRIs and seven of 15 water-SRIs were grouped together in a positive direction, had a moderate to strong relationship with measured traits, and could identify the drought-tolerant parent Sakha 93 and several RILs. The PLSR model based on all SRIs as a single index showed moderate to high R2 in calibration (0.53–0.75) and validation (0.46–0.72) datasets, with strong relationships between observed and predicted values of measured traits. The SMLR models identified four and three SRIs from vegetation-SRIs and water-SRIs, respectively, to explain 63–86% of the total variability in measured traits among genotypes. These results demonstrated that vegetation-SRIs can be used individually or combined with water-SRIs as alternative breeding tools to increase genetic gains and selection accuracy in spring wheat breeding. [ABSTRACT FROM AUTHOR]

Bio-activated organic fertilizers (BOZ) were produced by enriching the zinc oxide (ZnO)-orange peel waste composite with Zn solubilizing bacteria (ZSB: Bacillus sp. AZ6) in various formulations (BOZ1 (9:1), BOZ2 (8:2), BOZ3 (7:3) and BOZ4 (6:4)). The produced BOZs, along with ZnO, ZnSO4, ZSB were applied to maize crop (Zea mays L.) under field conditions in two different cropping season and the growth, yield, physiology, plant Zn contents and quality of maize were investigated. Results revealed significant variation in the aforementioned parameters with the applied amendments. The BOZ4 performed outclass by exhibiting the highest plant growth, yield, physiology, Zn contents, and quality. On average, an increase of 53%, 49%, 19%, 22%, 10%, 4%, and 30% in plant height was noticed with BOZ4 application over control, ZnO, ZnSO4, BOZ1, BOZ2, BOZ3, and ZSB, respectively. BOZ4 enhanced the dry shoot-biomass 46% than control. Likewise, the photosynthetic rate, transpiration rate, stomatal conductance, chlorophyll contents, carotenoids, and carbonic anhydrase activity were increased by 47%, 42%, 45%, 57%, 17%, and 44%, respectively, under BOZ4 over control in both cropping seasons. However, BOZ4 reduced the electrolyte leakage by 38% as compared to control in both cropping seasons. BOZ4 increased the Zn contents of grain and shoot by 46% and 52%, respectively, while reduced the phytate contents by 73% as compared to control. Application of BOZ4 revealed highest average fat (4.79%), crude protein (12.86%), dry matter (92.03%), fiber (2.87%), gluten (11.925%) and mineral (1.53%) contents, as compared to control. In general, the impact of cropping seasons on maize growth, yield, physiology, Zn contents, and quality were non-significant (with few exceptions). Thus, bio-activation of ZnO with ZSB could serve as an efficient and economical strategy for boosting up the growth, yield, physiological, and quality parameters of maize under field conditions. [ABSTRACT FROM AUTHOR]

Hyperspectral sensing offers a quick and non-destructive alternative for assessing phenotypic parameters of plant physiological status and salt stress tolerance. This study compares the performance of published and modified spectral reflectance indices (SRIs) for estimating and predicting the growth and photosynthetic efficiency of two wheat cultivars exposed to three salinity levels (control, 6.0, and 12.0 dS m−1). Results show that individual SRIs based on visible- and near-infrared (VIS/VIS, NIR/VIS, and NIR/NIR) estimate and predict measured parameters considerably more efficiently than those based on shortwave-infrared (SWIR/VIS and SWIR/NIR), with the exception of some modified indices (the water balance index (WABI-1(1550, 482), WABI-2(1640, 482), and WABI-3(1650, 531)), normalized difference moisture index (NDMI(1660, 1742)), and dry matter content index (DMCI(1550, 2305)), which show moderate to strong relationships with measured parameters. Overall results indicate that modified SRIs can serve as rapid and non-destructive high-throughput alternative approaches for tracking growth and photosynthetic efficiency of wheat under salt stress field conditions. [ABSTRACT FROM AUTHOR]

The moisture stability of tobacco shred, a typical porous carbohydrate material, is very important during its processing, storage and smoking, moreover, it is sensitive to environmental conditions. Therefore, effect of sucrose esters (SEs) and sucrose ester/ Polygonatum sibiricum polysaccharide mixture (SPMs) on the moisture retention and moisture resistance of tobacco shred was assessed. When SEs were added to tobacco shred, moisture resistance was significantly enhanced, whereas moisture holding capacity was attenuated. Contrarily, the addition of SPMs made moisture retention index (MRI) and moisture proof index (MPI) increase from 1.8910 to 2.1612 and from 1.9489 to 2.0665, respectively, revealing that SPMs improved the moisture retention and moisture proof ability of tobacco shred simultaneously. The monolayer moisture content (M 0) was decreased by SEs and increased by SPMs. Low-field nuclear magnetic resonance (LF-NMR) analysis showed that during adsorption, SPMs reduced the interaction between tobacco shred and water via hydrophobic property of SEs; during desorption, SPMs promoted the interaction between tobacco shred and water through hydrophilic binding of polysaccharide, leading to the migration of immobilized water to bound state. The modeling of the isotherms and LF-NMR analysis clarified the mechanism why SPMs could improve moisture stability of tobacco. • Sucrose ester/ Polygonatum polysaccharide mixture increased tobacco monolayer water. • Sucrose ester reduced tobacco interaction with water via its hydrophobic property. • Polar binding of Polygonatum polysaccharide promoted tobacco interaction with water. [ABSTRACT FROM AUTHOR]

Whey protein isolate-dextran (WPI-dextran) conjugates were acquired via Maillard reaction for different durations (1–7 days) and their potential to govern the size and stability of colloidal nanoparticles formed from heating electrostatic complexes of WPI-dextran conjugates and chondroitin sulfates was assessed. The grafting degree and browning index gradually increased with the reaction time. The intensity of amide bands increased in the first 2 days and then declined. As the duration increased, the content of α-helix increased from 23.9% to 29.6%, while β-sheet and random coil decreased from 23.8% and 38.1% to 19.6% and 32.7%, respectively. Moreover, the surface hydrophobicity was reduced as the conjugation progressed, while surface and total sulfhydryl content gradually increased from 5.3 and 15.4 μmol/g to 11.0 and 17.9 μmol/g, respectively. Meanwhile, fluorescence intensity of conjugates decreased with prolonged durations. These changes with increasing grafting degree prompted greater steric hindrance, weakened hydrophobic interaction, and improved stability of protein during heating, thus facilitating the decreasing diameter of the corresponding heat-induced nanoparticles. In comparison with the nanoparticles derived from non-conjugated mixture of WPI and dextran, those from WPI-dextran conjugates showed an excellent stability to aggregation and dissociation upon synergistic influence of pH variation (1–10) and enhancing ionic strength (0–4 mol/L). • Conjugation degree of the conjugates depended on Maillard reaction time. • Conjugation induced conformational changes of protein. • Nanoparticles prepared from conjugates were insensitive to environmental changes. • Size of nanoparticles can be tuned by glycation of protein. • Steric hindrance promoted size control and stability of nanoparticles. [ABSTRACT FROM AUTHOR]