Cladosporium (60.2%), Aspergillus (10.4%), Fusarium (9.4%), Alternaria (8.5%), and Ganoderma spp. (2.3%). Temperature was negatively correlated with total colony count  or species richness , while wind speed was positively correlated with total colony count  or species richness . The highest dispersal of fungal spores was obtained at 18:00, whereas the lowest fungal spores release was recorded at 00:00 (midnight). There were no significant differences in species composition and richness of the airborne fungal population between two study sites, the Industrial area and Qatar University Campus. The count of Alternaria spp. and Fusarium spp. were significantly higher at the Industrial area site, which corresponds to a higher CO2 level than the Qatar University site. This study lays the foundation for future work to assess the implications of such aeromycological data on public health.This research was conducted to investigate the dynamics of airborne fungi using viable culture collection and in respect to different abiotic variables, including seasonal and intra-diurnal variations. A gravimetric method was used to sample airborne fungal deposition on potato dextrose agar plates on alternate days, for a year between April 2015 to March 2016. From 176 settle plate exposures, a total of 1197 mould and 283 yeast colony-forming units (CFU), 21 genera and 62 species were retrieved. The highest fungal spore count was recorded in February 2016, whereas the lowest count occurred in August 2015. The main constituents of the fungal airspora were attributed to  Aeromycology is the scientific study of airborne fungal spores, including their release, concentrations, composition and the parameters affecting their dynamics in the atmosphere . As a br2) could significantly affect airborne fungal growth and subsequently influence their dispersal rate [2, which often elevates the carbon-to-nitrogen ratio and plant biomass, the sporulation rate of Alternaria alternata was substantially increased [Airborne fungi cause negative effects on humans’, animals’ and plants’ health ,2. The asal rate . As a rencreased .Cladosporium, Alternaria and Ulocladium were the most abundant genera in the atmosphere of Doha [In Qatar, only one study was carried out on the dynamics of airspora of Doha for a whole year (1997–1998) . The aut of Doha . Qatar i of Doha . Doha is2 concentration.This study aims to: (1) provide baseline knowledge about density, diversity and dynamics of airborne fungal spores in the atmosphere of Doha using settle plate exposures, (2) investigate variations in seasonal and intra-diurnal patterns and to correlate variations with meteorological factors and (3) correlate the variations in species composition and abundance of airborne fungi with atmospheric CO2 and a coastline of 900 km in length. It lies in the Arabian Peninsula at 25°35′48″ N and 51°18′39″ E and is connected to Saudi Arabia in the south, bordered by a very shallow, semi-enclosed sea characterized by hyper-salinity (39–41) practical salinity unit (psu) for surface water) [Qatar is a peninsula occupying an area of more than 11,000 kme water) . Geogrape water) . Doha ise water) .Acacia spp., Prosopis juliflora, Ziziphus nummularia and Lycium shawii [The present study was carried out at Qatar University, which is located on the northern side of the capital Doha at 25°37′47″ N, 51°49′03″ E. The main habitat and associated vegetation in the northern part of Qatar is characterized by ‘rodat’ areas, in which compact soils are common. This type of soils usually supports more moisture and organic matter than other desert parts. Vegetation type ranges from trees and shrubs to grasses and herbs, and common species include m shawii . Becausem shawii . Within A gravimetric method (settle plate exposure) using a Petri dish was carried out directly on the roof of the building of Qatar University . One Petri dish (9 cm diameter) containing Potato Dextrose Agar (PDA)  amended with chloramphenicol (1 g/L), was exposed for 15 min, which resulted in more accurate colony counts, at 15:00 on each of 3 days per week , from the beginning of April 2015 to the end of March 2016. Total exposures of 176 plates were collected during the year of study. After sampling, the plates were incubated at 25 °C for 3–5 days.Daily meteorological data from Qatar University weather station were supplied by the Weather Record Department, Doha, Qatar. The meteorological data considered are minimum and maximum daily temperature, minimum and maximum relative humidity, daily rainfall, wind direction and wind speed.A period of two months, February and March (2016), was chosen to investigate intra-diurnal variations in fungal populations of Doha, mainly because this period was preliminarily explored as a period of greatest diversity in species composition in Doha’s atmosphere. One Petri dish (9 cm diameter) containing PDA was exposed to air for 15 min at 6-h intervals  during the period of 1 February to 31 March 2016. After sampling, the plates were incubated at 25 °C for 3–5 days. During the whole period, a data logger  was installed at the site of collection to monitor temperature and relative humidity at intervals of one hour.2 level on species composition and abundance of fungal spore populations. Qatar University is one of these locations, which is relatively far from industrial areas (~25 km), and the other is close to the central industrial area . Industrial area is a district of Doha, Qatar, with coordinates 25°10′3″ N and 51°26′22″ E.Two locations at Doha city were chosen to investigate the impact of CO2 data logger  was used to record CO2 concentration every minute during the collection period. The average of the 15 readings per sampling was recorded.During the period of 1 February to 31 March 2016, Petri dishes (9 cm diameter) containing PDA were exposed to the air for 15 min on alternate days. In respect to the two locations and during sampling, the plates were opened at the same time and for the same exposure period (15 min). After sampling, the plates were brought to the lab using an icebox and then incubated at 25 °C for 3–5 days. The grown fungal colonies for each species were counted and the total colony counts were recorded. A portable COThe fungal grown colonies for each species were counted and recorded. For classification, fungal colonies were isolated and purified on Potato Dextrose Agar (PDA) and other selective agars like Malt Extract Agar (MEA)  and Czapek’s/Rose-Bengal agar , then, they were incubated for 3–5 days at 25 °C. Identification was based on the macro- and micro-scopic features following the keys and description given by many authors ,37,38,392 on species composition and abundance. To compare the CO2 concentration in the two study sites and as normality failed, a Mann–Whitney test on rank was applied based on 22 sampling exposures from each site. Analysis of variance (ANOVA) was performed to study the significant effect of intra-diurnal periods on deposition densities and species richness. The Shapiro-Wilk test was used to test the normality of data and Tukey’s test was used to separate the means at p ≤ 0.05. Temperature and relative humidity data from the data logger were averaged for each sampling time  and Pearson’s correlation coefficient was performed to study the correlation between colony count of each sampling exposure with the average temperature or relative humidity. The Jaccard similarity coefficient was applied to compare the similarities in species composition (including species identified at the specific level and other taxa) among the four diurnal periods, as follows: Jaccard similarity coefficient = (c/(a + b) − c) × 100, c = number of common species between any two time periods (a and b). A T-test at significance level p = 0.05 was accomplished to study the significance in daily colony counts between the two study sites according to differences in CO2 concentrations.Statistical analyses were performed to correlate the mean daily fungal spore counts and species composition with the daily data of the meteorological parameter of the same day and for the whole year using Pearson’s correlation coefficient. Similar correlation analyses were performed to investigate the effect of COFrom the air of Doha, the total colony count number retrieved from 176 exposure samplings during the year of study (1 April 2015 to 31 March 2016) was 283 yeast and 1197 mould colony-forming units (CFU). The mould colonies belong to 21 genera and 62 species .Cladosporium (60.2%), Aspergillus (10.4%) Fusarium (9.4%), Alternaria (8.5%), Ganoderma spp. (2.3%) and Penicillium (2.0%)  .Cladosporium was the most common fungal taxa in the air of Doha, comprising around two thirds of the total colony counts representing five species. C. cladosporioides was the most dominant species, with 70.5% of the total of the genus Cladosporium, followed by C. macrocarpum with 9.2% and C. sphaerosprmum with 6.4%. Cladosporium had double peaks of occurrence (April and February) and the lowest occurrence in July , followed by A. chlamydospora (12.8%), then A. infectoria (11.9%)  . Both Alary 2016 . Interesole year .Cladosporium or Alternaria spores showed significant negative correlations (p ≤ 0.05) with daily maximum, minimum and mean temperatures. While the correlations of Cladosporium colony count with both daily or monthly relative humidity and rainfall were not significant, the monthly rainfall data showed a highly significant correlation (p ≤ 0.01) with Alternaria colony counts. A high significant (p ≤ 0.01) positive correlation occurred between daily counts of Cladosporium and Alternaria and wind speed (Aspergillus deposition density showed non-significant correlations with any of the studied weather parameters (. Fusarium daily colony counts had the only significant correlation (p ≤ 0.01) with the daily wind speed data (p ≤ 0.05) with all daily temperature parameters. A high significant positive correlation (p ≤ 0.01) was also observed between the total daily or monthly colony count and daily or monthly wind velocity (p ≤ 0.01) with species diversity  in colony count and species diversity were found among the four studied periods. The highest colony count and species diversity were recovered at 18:00, while the lowest were reported at 00:00 (midnight). No significant differences in colony counts as well as species diversity between 12:00 and 18:00 were observed (During the two months of study (1 February to 31 March 2016), the mean daily maximum temperature ranged from 24.6 to 27.3 °C, the mean daily minimum temperature ranged between 15.0 and 18.7 °C. The daily relative humidity varied from 39% to 84%. Significant differences (observed . The higobserved .p ≤ 0.05) with mean daily relative humidity and positively correlated (p ≤ 0.05) with mean daily temperature (Alternaria and Ganoderma have shown significant positive correlations (p ≤ 0.05) with the mean daily temperature. The most abundant fungal taxa retrieved throughout the two months at the four periods were Cladosporium cladosporioides, Alternaria spp., Fusarium spp., Ganoderma, Ulocladium botrytis and Aspergillus (The mean daily colony count was negatively correlated (perature . Howeverergillus .Cladosporium cladosporioides represented a mid-day (12:00) peak and had a minor peak at 18:00, while its deposition density significantly declined (p ≤ 0.05) at midnight (00:00) and in the early morning hours (06:00). Ganoderma spp. significantly peaked (p ≤ 0.05) at 18:00 and showed similar abundance among the other three periods. Alternaria had a significant mid-day (12:00) peak pattern, while the colony count significantly declined in the other three periods. No significant differences in Fusarium colony count were reported among the four studied periods, while Aspergillus had a major peak pattern at 18:00 and Ulocladium botrytis at midnight (00:00) ( (00:00) .2 was higher  at the Industrial area site (average = 513 ± 167 ppm) than Qatar University Campus (average = 335 ± 92). Applying the non-parametric Mann–Whitney test on rank indicated a significant difference  in CO2 concentrations between the two sites. The common and most abundant fungal taxa recorded in the two study sites were Cladosporium, Ganoderma, Fusarium and Alternaria. Corresponding to CO2 concentrations, the daily colony count of Cladosporium was significantly higher at Qatar University Campus than the Industrial area (p ≤ 0.05)  at the Industrial area site (The two-month study (1 February to 31 March 2016) revealed that 12 fungal genera and 31 fungal species were collected from the Qatar University Campus site, while 16 fungi genera and 35 species were collected from the Industrial Area site. No significant differences were observed in the total number of colonies and fungal species between the two study sites, although daily concentration of CO ≤ 0.05) . Contrarrea site .Cladosporium was prominently higher in relative abundance (67%) at the University campus, constituting about two thirds of fungal composition. Other fungi like Ganoderma, Fusarium and Alternaria were also part of the main composition, with relative abundances of 11%, 7% and 6%, respectively. Other taxa at the University Campus had 10% abundance  was very low compared to the University site (67%) (Ganoderma showed similar relative abundances (11%) in the two sites  . Intereswo sites . The fund by 23% .Cladosporium, Aspergillus Fusarium, Alternaria, Ganoderma spp. and Penicillium were the main components of the air mycoflora of the Doha area. Several studies demonstrated the presence of the above-mentioned fungal taxa as part of the main aeromycota composition in different Middle Eastern countries [Cladosporium, Alternaria and Ulocladium. Although the method of collection used in Al-Subai’s study is similar to the one used in the present study, there exist some differences in the experimental setup and design. For instance, the collection height used by Al-Subai was 1.5 m, but in the present study, a height of 12 m above the ground level was used, which is considered more realistic in such aerobiological studies [During the year of study, a total of 1197 colony counts and 21 genera assigned to 62 species were retrieved. ountries ,19. Accoountries , the maj studies . Another studies ,42,43,44Cladosporium was the most common fungal genus and commonly occurred throughout the study periods with double peaks, one in April and another in February. Many authors presented Cladosporium as the main air mycoflora in different countries [Cladosporium throughout the year. It has been demonstrated that the structural features of Cladosporium conidia, such as a chlamydospore-like structure, make them more resistant to solar radiation and physicochemical agents [Cladosporium spores, which helps in the dissemination of conidia [Our study showed that ountries ,26,45. Ml agents ; however conidia ,48.Aspergillus sp. was the second predominant fungal genera, with ten species recorded. Aspergillus presented a seasonal pattern: the highest deposition density was in August and the lowest in January. Aspergillus sp. was the predominant taxa in many countries’ outdoor environments, like Kuwait [e Kuwait  and Saude Kuwait ,49.Aspergillus sp. in the atmosphere of Doha and other Gulf regions is consistent with the findings of Christensen and Tuthill, who found that the tropical/subtropical habitats accommodated higher numbers of Aspergillus species in comparison to temperate regions [Aspergillus genus is highly abundant in the tropics/subtropics, especially in the saline and cultivated soils.The abundance of  regions . AccordiFusarium was ranked as the third airborne fungi. Fusarium is a cosmopolitan fungus, which is a well-known plant/animal pathogen [Fusariun hardly germinates in low water activity environments [Fusarium macrocnidia was found to follow a rain or irrigation event [Fusarium was abundant in the atmosphere of the Zarqa area, Jordan, and this abundance correlated with the continuous drip irrigation of olive plantations in the study site, and the existence of many farms [Fusarium in the atmosphere of Doha, since Qatar University campus receives extensive and frequent irrigations to accommodate the need of the vegetation cover (turfgrass areas and others) and the high evaporation rate. However, rainfall might interact with density of Fusarium, but it is difficult to achieve any significant correlation trends since the rainfall in Qatar is very low and limited to a few days of the year.Additionally, pathogen . Fusariuronments . The dison event . Indeed,ny farms . This maAlternaria represented the fourth most prevalent fungal taxa in the air of Doha, with seven species identified. Alternaria represented a seasonal trend, with high colony count in May and July, while the colony count declined a little and maintained all over the year with almost minor fluctuations. Similar to Cladosporium spores, the conidia of Alternaria are of dry spore’s type and dark colour, which tolerate the solar radiation and survive the whole year [Alternaria spp. was reported in July and August, following wet weather [ole year . Other s weather ,55.Ganoderma spp. was one of the major constituents of air mycoflora of Doha (2.4%), but it was exclusively retrieved in February and March. In the present study, Ganoderma spp. has been identified for the first time in the atmosphere of Doha. A similar study in Jizan, Saudi Arabia, also found a considerable concentration of Ganoderma basidiospores within the airspora [Ganoderma spp. was not frequently detected in many countries with similar ecological features in the Gulf region. Ganoderma was first suggested to be associated with respiratory allergy in 1952 by Gregory and Hirst [Ganoderma basidiospores was significantly correlated with the high incidence of asthma in Jizan [Ganoderma widely varies worldwide. For example, in Jizan region of Saudi Arabia, the seasonal trend of Ganoderma is from October to March, with a peak in December and January when the temperature is moderate and the humidity is relatively high [Ganoderma were reported on more than 95% of the days, of June through October, and reaching a maximum concentration in late August until mid-October, with a positive correlation with temperature and precipitation [Ganoderma had a seasonal pattern from July to September [Ganoderma basidiospores is determined by the abundance of vegetation coverage [Ganoderma basidiospores seems to be more correlated with warm and high moisture or rainfall. Together, these studies corroborate our findings as recorded in February (10%) and March (90%) respectively  in the atmosphere of Doha, and this could be linked to the relatively moderate temperature and high rainfall . August p ≤ 0.01) positive correlation was obtained between the total daily fungal counts and fungal taxa recorded, which might indicate that similar interactions of weather conditions may determine the dynamics and fluctuation of both parameters. Both daily and monthly counts of either Cladosporium or Alternaria spores showed significant negative correlations (p ≤ 0.05) with daily maximum, minimum and mean temperatures. While the correlations of Cladosporium colony count with daily or monthly relative humidity and rainfall were not significant, the monthly rainfall data showed high significant correlation (p ≤ 0.01) with Alternaria colony counts. A high significant (p ≤ 0.01) positive correlation was also observed between daily counts of Cladosporium or Alternaria and daily wind speed data. Contrary to our results, in Poland, Grinn-Gofroń and Strzelczak found that the concentration of air spores of Cladosporium and Alternaria were significantly and positively correlated to temperature, but negatively to relative humidity, however the authors could not clearly rank which weather parameter is more important for the viability of those fungal spores in the air [Alternaria was significantly and positively correlated with temperature but negatively correlated to relative humidity, rainfall and wind speed [Alternaria and Cladosporium were significantly and positively correlated with temperature and humidity [Alternaria spores is negatively correlated to temperature [Cladosporium spores increased significantly as the temperature decreased, which is in support of our findings [Alternaria incidence [Alternaria spores was higher in August following a period of wet weather [Alternaria spores. Combined together, these studies are in agreement with our results, suggesting the significant positive correlation between monthly data of Alternaria and rainfall.Equally, an important, significant  with mean daily temperature. A highly significant positive correlation (p ≤ 0.01) was obtained between the total daily or monthly colony count and daily or monthly wind speed, and a negative but insignificant (p ≤ 0.05) correlation to the daily mean relative humidity and rainfall. However, no significant correlations were reported between total colony count and either relative humidity or rainfall. In agreement with our results, it has been found that the several fungal spore counts are negatively correlated with temperature, though a positive and insignificant correlation was detected with relative humidity [Total daily colony count of all encountered fungi had negative correlations . Indeed, Al-Suwaine et al. also found that the concentration of Ulocladium is negatively correlated to temperature [nd speed . Hameed at 20:00 . The higat 00:00 . In the perature .2 and other air pollutants increase with increased anthropogenic activities [2 was significantly higher  at the Industrial area site than at Qatar University Campus. In agreement with our results, in Taiwan, Chung et al. [2 levels [The concentrations of COtivities ,80. Therg et al. , and fro2 levels .Cladosporium, Ganoderma, Fusarium and Alternaria, their deposition densities and distribution rate in the atmosphere are significantly different. Cladosporium showed higher and significant deposition density at the Qatar University site in comparison to Fusarium and Alternaria, which were highly abundant in the Industrial area site; however, Ganoderma had a similar relative abundance rate. This might be explained by the fact that elevated concentration of atmospheric CO2 raises the sporulation rate in some fungal genera [2, other air pollutants, such as ozone (O3), nitrogen dioxide (NO2), sulphur dioxide (SO2) and particulate matter (PM10), might influence the availability and biological activities of airborne fungal taxa [Alternaria spp. and Fusarium spp. were significantly higher at the Industrial area site, which corresponds to a high CO2 level. Further agreement to our findings were the results of a study by Klironomos et al., suggesting that spore production levels of Fusarium spp. and Alternaria spp. were stimulated under elevated CO2 concentration levels [Alternaria alternata increased at elevated CO2 concentration [2 concentration provides plants with a higher carbon/nitrogen ratio; in this way, pathogenic plant fungi accelerate their growth and sporulation rate [2 and industrialization on dynamics of airspora, though a full year of monitoring is suggested for future research.Although the main constituents of the airspora in the two study sites were attributed to similar fungal taxa, l genera , and migl genera . Rather gal taxa ,83. Inden levels . Additiontration . Indeed,ion rate . Our resCladosporium, Aspergillus, Fusarium, Alternaria, Ganoderma spp. and Penicillium represented the major fungal airspora in the atmosphere of Doha, Qatar. Those fungi are frequently reported to have an association with allergy [Aspergillus flavus, where they found a huge quantity of allergic fungal mucin and dark crusts fully colonizing the sinuses, which required a course of systemic and topical corticosteroids [Ganoderma spp., Cladosporium, Alternaria and Aspergillus were believed to significantly contribute to causing allergic rhinitis and allergic asthma [In the present study,  allergy ,65. In tsteroids . In anotsteroids . The datsteroids . In Saudc asthma .A. alternata contributed to more than half of the total Alternaria spp. A. alternata is considered as one of the most significant aeroallergens [A. fumigatus, A. niger, A. flavus and A.oryzae were frequently correlated with the respiratory allergic cases, and particularly A. flavus due to its large spores, use to deposit in the upper respiratory tract and commonly cause fungal sinusitis [Cladosporium herbarum is an important and main cause of inhalant fungal allergens, among other Cladosporium species [C. herbarum showed a minor deposition compared with other Cladosporium species.In the present study, the deposition density of llergens . Speciesinusitis . Cladosp species . In the Cladosporium, Aspergillus, Fusarium and Alternaria. Among the meteorological parameters, temperature might be the main determinant of the fungal spore incidence and diversity in the atmosphere of Doha. Ganoderma spp. is an allergic fungus which was reported for the first time and found to be a major constituent of Doha airspora during February and March. The study also revealed the intra-diurnal pattern of the airborne fungi in the atmosphere of Doha, Qatar, which indicates significant differences in the total colony counts and fungal diversity as a function of time. Both temperature and relative humidity affect the deposition densities of airspora. While other unmonitored air pollutants may have played various roles, here, we demonstrated that increased concentrations of atmospheric CO2 influenced the occurrence of certain fungal taxa. Considering the potentials effects of other air pollutants’ influence, it will be of interest to investigate their specific roles in the occurrence, dynamics and diversity of fungal taxa in Doha’s atmosphere. The present study is useful for filling the gap of data shortage on the dynamics of fungal taxa in Doha’s atmosphere, as well as providing baseline information for allergists, plant pathologists, meteorologists and other scientists. However, two major limitations can be deduced and should be considered for future investigations. The first is the fact that airspora data based on day-to-day spore trapping are more precise and complementary to the gravimetric method used in this study. The second limitation is that a two-month study is not enough to investigate the influence of higher CO2 concentration in the atmosphere on dynamics of airspora, as well as considering the influence of other important air-pollutants is essential.In conclusion, our study demonstrated a seasonal pattern of airborne fungi in the atmosphere of Doha, Qatar. The main fungal airspora were attributed to


To manufacture custom medical parts or scaffolds with reduced defects and high mechanical characteristics, new research on optimizing the selective laser melting (SLM) parameters are needed. In this work, a biocompatible powder, 316L stainless steel, is characterized to understand the particle size, distribution, shape and flowability. Examination revealed that the 316L particles are smooth, nearly spherical, their mean diameter is 39.09 μm and just 10% of them hold a diameter less than 21.18 μm. SLM parameters under consideration include laser power up to 200 W, 250–1500 mm/s scanning speed, 80 μm hatch spacing, 35 μm layer thickness and a preheated platform. The effect of these on processability is evaluated. More than 100 samples are SLM-manufactured with different process parameters. The tensile results show that is possible to raise the ultimate tensile strength up to 840 MPa, adapting the SLM parameters for a stable processability, avoiding the technological defects caused by residual stress. Correlating with other recent studies on SLM technology, the tensile strength is 20% improved. To validate the SLM parameters and conditions established, complex bioengineering applications such as dental bridges and macro-porous grafts are SLM-processed, demonstrating the potential to manufacture medical products with increased mechanical resistance made of 316L. Nowadays, selective laser melting (SLM) is one of the most used additive manufacturing (AM) technologies applied to produce directly metallic prototypes from virtual models. Under an inert atmosphere, this process is capable to fabricate complex bioengineering applications or even cellular scaffolds made of various powders such as titanium alloys ,2,3, NiTDue to the low costs of 316L stainless steel compared to titanium or CoCr alloys, it is frequently applied to the manufacture of dental ramus blades, ramus frame implants , orthopeAt the international level, the highest-selling SLM machines to research institutes and companies are limited to 200 W laser power [Different companies are providing 316L powder but full details regarding the particle size, distribution, shape or flowability are not conferred. This information is essential in adequate preparation and controlling of SLM process because at high levels of irradiation energy, the fine particles of 316L can evaporate, generating porosity and decreasing the mechanical characteristics. Commonly, the information offered by powder providers is limited to the mean diameter of particles or the diameter range.The entire remarks exposed in this introduction motivate the present study. The purpose of this paper is to identify the SLM parameters able to manufacture, in a stable process, medical applications with high tensile strength made of 316L powder. In this work, a commercial powder is analyzed to understand the particle size, distribution, shape and flowability. Process parameters under consideration include laser power up to 200 W, laser scanning speed, hatch spacing and layer thickness. The effect of SLM parameters on processability is evaluated, being concentrated to obtain a stable fabrication and to limit the technological defects. The mechanical tests are developed without applying a stress-relief treatment on samples, only preheating the SLM platform (250 °C) during the fabrication. To validate the process parameters established, complex bioengineering applications such as dental bridges and macro-porous grafts are designed and SLM-manufactured. Due to extended processability investigation, the novelty of this research relates to an increased mechanical resistance of parts made of 316L powder, SLM-manufactured by common solid laser limited to 200 W.The examinations are carried out using commercially austenitic 316L steel powder. This gas-atomized stainless steel powder was purchased from MCP HEK Tooling . Its chemical composition is shown in 3, at 4-bar pressure using 10× optical system magnification (1.75 μm minimum particle size and 100 μm maximum). The particle size distribution was calculated based on two distinct techniques: number distribution of particles and volume or mass distribution. Laser diffraction results were reported on a volume basis, so the volume mean was used to define the central point [A typical instrument for particle characterization is Morphologi G3 system . Using this instrument, the powder was dispersed with an instantaneous pulse of compressed air and precise measurements were elaborated . The diaal point . The parThe particle shape was analyzed by circularity, convexity and elongation parameters. Each parameter is described below . In the A SLM Realizer 250 machine , equipped with a 200 W solid fiber laser (type Nd:YAG) was used to manufacture the samples. The laser scanning strategy adopted was X/Y which allows a scanning in X direction of “n” layer and in Y direction of “n + 1” layer (rotating each hatch scan 90°). The advantage of this hatch pattern is that it can contribute to a high build rate compared with stripe hatch or chessboard pattern see . On the E) was calculated by Equation (4):P is the laser power (W), v is the scan speed (mm/s), h is the hatch spacing (mm) and t is the layer thickness (mm).The 316L samples were SLM-manufactured, varying the processing parameters such as laser power (50–200 W) and scanning speed (250–1500 mm/s). The hatch space and layer thickness were 80 μm and 35 μm, in concordance with the literature . To progThe design of samples was done in concordance with ISO 6892  and is pThe SLM platform was uniformly preheated at 250 °C during the fabrication. Under a high-purity Ar-atmosphere and limited oxygen level (0.3–0.5%), the samples were manufactured with different SLM process parameters and the working conditions detailed above.Unstable processability (U): characterizes the impossibility of finalizing the process due to high residual stresses that severe warping the part, being necessary to interrupt its manufacturing. Major risk of failing.Relatively stable processability (R): characterizes a medium chance to succeed the process with continuous surveying until the last layer is deposed, being possible to observe some limited macro-cracks (0.1–1 mm length) or heat-affected zones.Stable processability (S): characterizes a successful SLM process, which does not need continuous surveillance. The parts obtained do not present the defects mentioned above.The SLM technology can produce a residual stress phenomenon caused by temperature gradients. In the laser beam spot, temperatures above the melting point prevail, while the rest of the part cools rapidly . Dependi3 as a reference value for 316L stainless steel.Tensile stress–strain behavior was measured using standard sheet specimens in a universal testing system type Zwick Z100 . The design of standard specimens is presented in To test the results on medical applications, some complex models were designed. The first model is a customized dental bridge, containing multiple anatomical shapes, sharp internal corners and uneven thicknesses . These gThe second and the third models were elaborated considering the state-of-the-art of SLM processing which suggests that lattice structures from 316L hold great promise for the fabrication of patient-specific implants via bone tissue engineering .In Chen et al. recently investigated the microstructure and mechanical properties of 316L samples and found that even if a fine powder (d50 = 8.2 μm) or a normal one (d50 = 20.3 μm) is used, the tensile strength will be closer after SLM manufacturing with 200 W laser power . This inTo provide a quick and easy comparability, the significance of shape parameters is illustrated As shown in Since the elongation parameter measures the length–width relationship, The hall flow rate of this 316L powder was 18.2 s per 50 g. This is a high flowability compared with other 316L powders . This cAnalyzing the literature recommendations regarding the SLM process parameters which could be proper for 316L powder ,15,33,363. For a stable processability, the variation of laser parameters is more restricted as can be seen in In the context of manufacturing evaluation, understanding the effect of laser parameters is a complex issue itself. An unstable process was observed in more than 30 sets of parameters. Some of them are marked in red areas from The scanning strategy configured also plays a significant role in limiting the internal stress. Because our study is focused on the effect of process parameters on SLM manufacturing, the scanning strategy adopted was X/Y alternating scanning at 90°. This hatch pattern contributes to a high build rate but it could cause a significant residual stress phenomenon ,28. NeveBesides providing a stable processability, investigating the effect of SLM parameters on mechanical characteristics is compulsory. The tensile tests were carried out on samples processed in relatively stable or stable processability and the SLM parameters are detailed in From our findings, the YS can vary between 590–780 MPa, the UTS from 640 MPa to 840 MPa and the Young modulus between 173–194 GPa (±3% standard deviations). The highest tensile strength was obtained on samples manufactured via process parameters with codes S1 and S3 shown in 3 can increase the tensile strength of 316L parts [3 belongs to S3, 3 can raise the UTS up to 700 MPa [Even if various studies suggest that a density energy of 104 J/mm6L parts ,34, we o 700 MPa .Additionally, a preheating over 200 °C during the SLM fabrication led to a dense homogeneous structure with low porosity, supporting moreover the growing of YS and UTS properties . As it wThe highest values of YS, UTS and elongation at fracture obtained in different studies published in the period of 2008–2019 are summarized in Correlating with other laser techniques with the same principles of operation, such as Laser Engineered Net Shaping (LENS) , the tenRegarding the elastic modulus, the values determined are in concordance with the literature ,12,13. TEven if pure titanium or its alloys are often practiced in medical sectors due to good integration into the human body, in particular cases, 316L stainless steel is used for certain applications such as in dental crowns, brides or implants, orthopaedic prostheses and bone tissue engineering scaffolds . This obA printed dental bridge is shown in A cavity associated with a binding defect is indicated by the blue arrow . RegardiThe macro-porous scaffolds were processed vertically as can be seen in Applying this new generation of grafts in medical applications, the osseointegration process could be improved due to their macro-porosity. The advantages of these 316L scaffolds include saving material consumption, reducing the energy used and diminishing the manufacturing time. From our perspective, the SLM process will completely change the biomedical manufacturing industry, making it much faster, more flexible and customized. Due to the high resistance of SLM parts, they will generate benefits in terms of total production cost, making this emerging technology more adopted by companies.The present examination of 316L stainless steel powder demonstrates that most of the particles are nearly spherical with a volume mean diameter of 39.09 μm, and 10% of them have a diameter less than 21 μm (d10). A high flowability of powder was measured, being a consequence of limited interparticle friction. The SLM process parameters identified to alternating melting strategies limit significantly the defects generated by internal stress, even if it is known that the 90° alternating laser scanning may increase the residual stress compared to the chessboard pattern strategy.The experimental results show that the processability of 316L powder can significantly influence the mechanical properties. A laser power up to 180 W and adaptation of the other SLM parameters can improve the tensile strength and a relative density above 99% can be reached. The SLM conditions and laser parameters established raise the yield strength to 780 MPa and the tensile strength to 840 MPa. Besides the laser parameters, cumulative factors contributed to this result such as: reduced percentage of fine or larger particles in powder feedstock, high flowability of powder, preheating of the SLM platform at 250 °C, pure argon as protective gas, low oxygen level on SLM chamber (< 0.5%), horizontal build-up of samples, and flexible recoater made of carbon fibers. In order to fully understand the mechanical behavior obtained, future metallographic and X-ray diffractions will be developed to analyze the crystal phase of 316L samples produced with these SLM parameters. The SLM parameters and process conditions could be suitable to produce medical parts and lattice structures, in a stable manufacturing environment and avoiding major solidification defects. The yield tensile strength obtained could provide new opportunities for biomedical scientists to reduce the weight of implants, prostheses or cellular grafts made of 316L, while maintaining the same safety factor.


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 . 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.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 ( The scarcity of freshwater in arid and semiarid countries requires the use of brackish water as an alternative source for irrigation in agriculture sectors, consuming approximately 75% of the available water supply in these countries . For exa2O2), hydroxyl radicals (OH), singlet oxygen (O2), and superoxide (O2−)  × RNIR) enables a highly accurate estimation for Chl content, because it ignores the differences in leaf structure in the leaves of various plant species [Chl content, the SRIs incorporating this wavelength in either SR (R750/R700) or ND type (R750 − R705)/(R750 + R705) are effective for estimating Chl content. However, the correlation between both indices and the Chl content becomes weaker when applied across a wide range of species. When these indices were modified in form and incorporated a third waveband (RNIR − R705)/(RNIR + R705 − 2R445), this modified index produced a substantially higher correlation with Chl content, because it eliminated the variability effects of surface reflectance between species [Until now, several types of SRI that include 2–3 wavelengths have been developed to assess the  regions ,39,40,41 regions . Formula regions ,44,45,46u et al.  found thu et al.  reportedChl content under a wide range of environmental conditions and for several plant species, developing a new lightweight proximal sensor for remote estimation of plant variables at the whole plant canopy level is possible. This new proximal sensor would enable faster estimation of plant variables in the field than existing heavy and costly devices (spectroradiometer) such as that used in this study. In addition, the limitations of the SPAD meter, which is based on single leaves, could be overcome.Therefore, the types of an SRI and the wavelengths incorporated play a key role in the efficiency of vegetation indices for accurate estimating plant variables. The most effective type should function to eliminate the effects of other factors on spectral reflectance rather than the target plant variables. Consequently, current work concerns the development of algorithms for SRIs that minimize their sensitivity to leaf structure and avoid the necessity for site- and species-specific calibration. Otherwise, most existing forms of SRI still need to be further validated regarding their ability for indirectly estimating plant variables under contrasting environmental conditions and for different plant species. If the simple forms of SRI that incorporate 2–3 wavelengths are proven to be effective in accurately estimating plant variables such as Most studies on the evaluation of salt tolerance of genotypes have been conducted under ideal controlled conditions (greenhouse or growth chamber) using homogenous growth media such as sand or hydroponic systems ,7. StudiChl contents  under various conditions ; (2) extract the most influential indices within each SRI type that explain most variability in each plant variables via stepwise multiple linear regression (SMLR); and (3) examine the performance of these influential indices in predicting the plant variables under various conditions.The primary objectives of this study were to (1) examine the potential of different types of published and newly constructed indices for remotely assessing growth and This study was conducted during the 2017/2018 and 2018/2019 growing seasons at the Experimental Research Station of the College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia  using two spring wheat genotypes with distinct salt tolerance: the salt-tolerant Sakha 93 and the salt-sensitive Sakha 61 ,53. Thes−1, 7.85, 0.46%, and 29.42%, respectively. The bulk density, field capacity, and wilting point were 1.48 g cm−3, 0.215 m3 m−3, and 0.101 m3 m−3, respectively. The available of N, P2O5 and K2O were 45.15 mg kg−1, 2.443 mg kg−1, and 186.91 mg kg−1, respectively.The open field condition was characterized by a typical arid climate. During the growing season of spring wheat (from November to April), the temperature, humidity, and rainfall were 12.9–32.2 °C, 10.7–47.5%, and 8.0–25.0 mm, respectively. The experimental soil texture was classified as sandy loam by electrical conductivity, pH (soil paste 1:5), organic matter, and calcium carbonate of 2.89 dS m−1), moderate salinity (6.0 dS m−1), and high salinity (12.0 dS m−1). The control treatment was irrigated with normal water during all life cycles of the wheat plants. The treatments of moderate and high salinity were irrigated with normal water for the first 2 weeks to ensure successful germination and complete seedling establishment. Subsequently, they were irrigated with artificial saline water containing 3.51 and 7.02 g NaCl L−1, respectively, until the final irrigation. In both salinity treatments, soil samples from the root zone were collected every 2 weeks to enable monitoring the increase of salt concentrations and ensure the application of salinity levels of each treatment. The irrigation water was applied using a low-pressure surface irrigation system. This system consists of a main line that is connected to the source of irrigation water and branches off to the sub-main hoses at each plot. The main line and sub-main hoses were equipped with manual control valves to enable controlling the amount of water delivered to each plot. In each growing season, the irrigation was applied six times for all treatments with the cumulative amount of irrigation water totaling approximately 5000 m3 ha−1, which equivalent to 500 mm.The two wheat genotypes were evaluated under three salinity levels, namely control , potassium chloride (50% K2O), and ammonium nitrate (33.5% N), respectively.The two genotypes were fertilized with 60, 60, and 180 kg ha4) and white paint. This calibration was repeated when required during the measurements. Because the optical fiber probe of the device had a 25° field of view, the probe could detect the spectral reflectance from a circular area of canopy with a 23.0 cm diameter when it was held vertically at approximately 0.8 m above the canopy in the nadir orientation. The average of five sequential measurements and 10 scans for each measurement was finally taken as the canopy spectrum for a subplot and used to calculate the different published SRIs as well as the newly constructed SRIs.Spectral reflectance from the wheat canopy was measured after 75 days (at the middle anthesis growth stage) from sowing from the internal rows in each subplot at five random places with excluding the first meter of these rows to avoid border effects. The measurements were taken under cloud-free conditions using a portable ASD spectroradiometer . This device is able to detect the canopy reflectance in the range between 350 to 2500 nm with a band interval of 1.4 nm for the 350–1000 nm region and 2.2 nm for the 1000–2500 nm region. However, the band interval was finally calculated automatically to 1.0 nm continuous bands for the entire spectral range (350–2500 nm). Before field canopy spectral reflectance measurements, the device was calibrated using a Spectralon reflectance panel  (40 cm × 40 cm) covered with a mixture of barium sulfate (BaSOChla), chlorophyll b (Chlb), and total chlorophyll (Chlt). The pigments were extracted from 0.2 g fresh weight using 80% acetone (v/v). The mixture was kept in the dark at room temperature until the leaf tissue was completely bleached. After complete extraction, the extract was centrifuged for 5 min at 5000× g and then brought up to a final volume of 15 mL using 80% acetone. The absorbance of the extracts was read spectrophotometrically at 645 and 663 nm using a spectrophotometer . Finally, the concentrations of each pigment in mg g−1 fresh weight (FW) were calculated according to the method previously described by Arnon [After the spectral reflectance of the wheat canopy was detected, all parts  of 20 plants from each subplot and within the spectral collection area were collected randomly, oven-dried at 75 °C for 72 h, and then weighed to determine the average of shoot dry weight (SDW) per plant. In addition, the three youngest fully expanded leaves were also excised randomly from the spectral collection area and used for the measurements of photosynthetic pigment contents: chlorophyll a (by Arnon  and LichChl content parameters. The newly constructed SRIs were used in the type of simple ratio indices (CSR), whereas the published SRIs were used in the type of published simple ratio (PSR), published modified simple ratio (PMSR), published normalized difference (PND), and published integrated forms (PIFs). The full names and formulas of all indices in each type are listed in In this study, 49 previously published and 11 newly constructed SRIs were applied to assess SDW and n = 36) (2) of the relationships between SRIs calculated from all possible combinations of dual wavelengths of binary wavelengths in the full spectral region (350–2500) and the values of each plant variable. The new SRIs were selected on the basis of the hotspot region of R2, which determines the most favorable relationships between plant variables and SRIs. The R package “lattice” from the software R statistics v.3.6.1  was used to establish the contour maps for each plant variable.The new SRIs were constructed on the basis of contour maps. The contour map was established for each plant variable using the pooled data of salinity levels, genotypes, replications, and seasons of the canopy spectral reflectance for each plant variable (n = 36) . These cChl contents) and SRIs were tested using the analysis of variance (ANOVA), which is appropriate for a randomized complete block split split-plot design, with the year, salinity level, and genotype considered as the main factor, sub-factor, and the sub sub-factor, respectively. Salinity level and genotype were considered fixed effects, whereas year and replicate were considered random effects. The differences between the mean values of plant variables and SRIs between salinity levels and genotypes were compared using Fisher’s least significant difference (LSD) test at a p ≤ 0.01 and 0.05 significance level. Relationships between plant variables and SRIs under specific conditions  were examined by means of a coefficient of correlation (r).The effects of year, salinity level, genotype, and their possible interaction on various plant variables (SDW and Chl content) of pooled data (n = 36) were applied to SMLR as independent and dependent variables, respectively. The different models of the best indices of each SRI type were used to predict distinct plant variables under specific conditions. The model with the highest values of R2 and the lowest values of root mean square error (RMSE) of the linear regression between the observed and predicted values of each plant variable was designated the model with the higher prediction accuracy. The different statistical analysis and plotting were performed using R software v. 3.6.1 (R Core Team 2017) and Sigma Plot for Windows .To identify the most influential indices accounting for the most variability in each plant variable, the indices of each SRI type and plant variables (SDW and p ≤ 0.05 and 0.01) for SDW, Chl content , and nearly all SRIs. The main effect of the years was also significantly different for SDW and Chl content variables, but not for almost all SRIs. The year by salinity level or by genotype interactions as well as the interaction between year, salinity level, and genotype had no significant effect on SDW, Chl content, and all SRIs, with a few exceptions  treatments, with Sakha 93 always exhibiting higher values for these SRIs than Sakha 61 does (Fisher’s protected LSD test at Sakha 61 . In addi 61 does .Chl content) with the 11 indices constructed in this study as SR as well as the four different types indices published in the literature  under each salinity level (n = 12) and genotype (n = 18) as well as for all the pooled data (n = 36) are presented in Chla and Chlt, with only very few SRIs (a maximum of three and four out of the 60 SRIs) exhibiting a moderate correlation with SDW and Chlb, respectively (−1), all indices within the CSR type exhibited strong correlation with Chla and Chlt (r = 0.72–0.93) and moderate to strong correlation with SDW and Chlb (r = 0.59–0.84). In addition, almost all indices within PSR, PMSR, and PND types exhibited strong correlations with all variables , whereas a sufficient number of indices within the PIF form  exhibited a weak and non-significant correlation with all variables (−1), all CSR indices exhibited highly significant correlations with the four variables . Almost all SRIs of the four published types exhibited strong significant correlation coefficients with the four variables, with only a few SRIs exhibiting weak to moderate correlations with the four variables . All indices within CSR, PSR (except BGI), PMSR, and PND types exhibited strong significant correlations  with the other three variables  for Sakha 61, whereas almost all of them exhibited moderate to strong correlations with the same three variables for Sakha 93. The indices within the PIF form that exhibited significant correlations with Chla and Chlt, exhibited a higher correlation for Sakha 61 than they did for Sakha 93  showed a weak and non-significant correlation with all variables , with the exception of BGI from PSR and Antariables .Chl content) across all data as a dependent variable and the SRI of each type of SRI as independent variables. The summary statistics and equations of the SMLR calibration for each variable and SRI type are presented in ) was determined the most effective CSR index and explained 80% of the variation in SDW. Whereas, the SRI based on red-edge/red-edge ) and red-edge/NIR ) accounted for 66%, 62%, and 67% of the variation in Chla, Chlb and Chlt, respectively , a combination of both OSAVI and REIP explained 69% of the variability in SDW or Chlt, whereas the combination of both TCARI and OSAVI, and EVI-1 and REIP explained 68% and 65% of the variability in Chlb and Chlt, respectively  was performed using the measured variables (SDW and ectively . For theectively . The NDVectively .n = 36) and used to predict the measured variables for each salinity level (2 ranged from 0.47 to 0.88) and high (R2 ranged from 0.53 to 0.71) salinity levels. In addition, the predictive models provided a more accurate estimation of Chla and Chlt than they did of SDW and Chlb  than they did for Chl content (R2 ranged from 0.30 to 0.37) for Sakha 93. They exhibited strong and comparable performance for predicting the three variables of Chl content (R2 ranged from 0.64 to 0.82) as did SDW (R2 ranged from 0.71 to 0.80) for Sakha 61 (2 ranged from 0.64 to 0.85) and second (R2 ranged from 0.71 to 0.84) seasons (The predictive models for each SRI type failed to predict only Sakha 61 . Similar seasons .+ and Cl−) interfering with the activity of numerous enzymes associated with chlorophyll biosynthesis and increasing the production of ROS, which ultimately leads to fast degradation of chlorophyll [Chl content and shoot biomass accumulation are a typical symptom of salinity stress on plants. This was also observed in this study with the two wheat genotypes and three salinity levels  and SDW gradually decreased with increasing salinity levels, with the reduction in these variables being higher in the salt-sensitive genotype Sakha 61 than in the salt-tolerant genotype Sakha 93 /(R719 − R743), correlated more favorably with the leaf chlorophyll content of white poplar and Chinese elm leaves than did SD, SR, and ND types, because it is insensitive to the effects of abaxial and adaxial leaf surface structures. However, Yue et al. [Chl content of soybean at canopy level than were the types of ND and SR indices. By contrast, Babar et al. [Chl content of wheat under irrigation conditions. Therefore, in this study, we compared the performance of distinct SRIs, differing in their formula forms and combination of wavelengths, to assess variation in SDW and Chl content variables of wheat under distinct growing conditions .Because the canopy spectral reflectance is affected by several factors such as growth conditions, growth stage, plant species, stress level, and soil background conditions, determining sensitive wavelengths incorporated in the SRIs and suitable types formulated from these wavelengths to make the SRIs more available for a range of conditions and sensors is challenging ,36,59,60r et al.  found thp ≤ 0.01 and 0.05) between salinity levels and wheat genotypes, with the exception of PIF-SRIs for which approximately half of the indices within this type exhibited non-significant differences between salinity levels  in the leaf tissue combined with deficits of essential ions (K+ and Mg2+) [In this study, the different indices within each type of SRI exhibited significant differences (y levels . In addiy levels . This rend Mg2+) ,56,62. IChl content (low chlorophyll absorption in the VIS region) and plant biomass (multiple scattering of NIR region by different leaf tissues) because of salinity stress. Previous studies have reported that when the Chl content decreases, the spectral reflectance in the VIS region increases especially in the main absorption bands of chlorophyll (blue: 400–500 nm and red: 660–690 nm) of the VIS spectrum [Chl content with increasing salinity , could be sufficient enough to make most vegetation indices unsuitable to assess biomass and Chl content under control conditions. In general, most vegetation indices within each SRI type are usually saturated when the values of LAI are larger than 3 in wheat crops [Chl content, necrosis, and senescence of photosynthetic organs, which are natural phenomena on canopies attributable to the ionic and osmotic stresses of salinity, may explain why the correlations between indices and four variables become stronger under moderate and high salinity levels. Furthermore, certain vegetation indices are saturated also at low Chl content [Chla and Chlt was generally high under moderate salinity level, when compared to their association under a high salinity level.The accuracy of distinct indices in different types of SRI in estimating SDW and ariables . In genety level . All theat crops ,67. Howe content ,68. ThisChl content variables than it was for SDW  under salinity stress. The results presented in Chl content under salinity stress. This is suggested by previous studies that have reported the significant variations in plant variables that occur between salinity levels and genotypes may also influence the efficiency of indices in estimating these variables, and this efficiency was improved significantly when the variation between plant variables was obvious between treatments [Regarding genotypes, the correlation between almost all indices and four variables was higher for the salt-sensitive genotype Sakha 61 than it was for the salt-tolerant genotype Sakha 93, and this was more evident for  for SDW . This fiy stress , which ieatments ,51,69,70Chl content of wheat crop under salinity stress. The primary reason for this may be that the indices within each SRI type use different robust wavelength combinations that are most closely associated with biomass and Chl content, such as a combination between wavelengths in the red, red-edge, and NIR regions. Similarly, previous studies have found that the indices based on the red- and NIR-bands performed most favorably for estimating above-ground biomass of winter wheat [Chl content compared to those in other regions, because they are most closely associated with chlorophyll content and are scarcely influenced by other leaf pigments. Main et al. [Chl content and showed that the indices containing off-chlorophyll absorption center wavebands (690–730 nm) exhibited a superior performance compared to those containing in-chlorophyll center wavebands (640–680 nm).Regarding the types of SRI, the results reveal that the simple type of indices  was slightly more effective than the integrated type (PIF) in estimating the four variables under distinct conditions . These fer wheat ,71. Simser wheat , Gitelsoer wheat , and Lu er wheat  reportedn et al.  assessedChl content especially Chla and Chlb [Chl content [Chl content variables in this study.The results presented in and Chlb . Becauseand Chlb ,65,74. I content ,60,75,76Chl content variables based on the influential indices extracted from each SRI type exhibited moderate to strong relationships with the observed values under moderate and high salinity levels, with the prediction of Chla and Chlt being more accurate than that of SDW and Chlb. However, these distinct predictive models failed to predict any variable under the control treatment  of two wheat genotypes differing in their salt tolerance and exposed to three salinity levels: control, 6 dS m−1, and 12 dS m−1. The indices were used in the types of CSR, PSR, PMSR, PND, and PIF. The results demonstrate significant differences (p < 0.01 and 0.05) in all plant variables and nearly all SRIs between salinity levels, genotypes, and their interaction. The distinct plant variables could be successfully assessed using several indices within each SRI type, but they were restricted to the moderate and high salinity levels, whereas these indices failed to do so under control conditions. The relationships between these indices and plant variables delivered closer fits for the salt-sensitive genotype Sakha 61 than they did for the salt-tolerant Sakha 93, and this was more evident for Chl content variables than for SDW. The most influential indices that were extracted by SMLR explained 60–81% of the variability in four plant variables. All predictive models based on influential indices within each SRI type exhibited moderate to strong relationships with the observed values under moderate and high salinity levels and for Sakha 61. Finally, the results of this study provide critical insights into the remote assessment of growth and Chl content under salinity stress and for distinct wheat genotypes. This information will be useful in the support of on-going efforts at developing lightweight proximal sensors for assessing key breeding plant variables at the whole plant canopy level for breeding purposes of wheat genotypes under salinity stress.This study evaluated the potential use of 60 spectral indices, including 49 published and 11 newly constructed indices, for assessing SDW and


Organic manure and biochar amendments have been used in agriculture to improve soil fertility and enhance crop productivity. Plant roots play an important role in the functionality of individual plants, and although the addition of organic manure and biochar reportedly affect roots, it remains unclear how root morphology and physiology respond. We conducted a field experiment to test the hypothesis that organic manure combined with biochar amendment could also enhance the productivity of continuous cropping systems in Xinjiang cotton plantations. Different levels of organic manure and biochar were applied. Organic manure and biochar significantly affected root morphology and physiology by improving soil nutrients. In the absence of biochar, organic manure amendment increased Root TTC reducing capacity, glutamine synthetase and nitrate reductase activity. Furthermore, morphological and physiological parameters peaked with 6% organic manure combined with 1% biochar. A significant increase in root physiology was recognized with an increase in soil nutrient content at the bud stage and a negative relationship between root physiology and soil total K content at the harvesting stage. Thus, our results indicate that organic manure combined with biochar positively influenced cotton roots, and therefore should be used to improve root health in continuous cropping systems. By 2016, the cotton planting area and cotton yield in Xinjiang accounted for 53.97% and 67.3% of the whole country, respectively. Owing to the slow process of agricultural industrialization, large area of the land involved, short period of contracts, and driven by economic interests, continuous cropping is widespread in Xinjiang2. 73.1% of cotton fields in Xinjiang have been continuously cropped for more than five years3.Xinjiang has abundant land resources, and its climate has low precipitation, high levels of sunshine and large temperature difference between day and night. When combined with the large-scale application of drip irrigation and mechanized cotton planting, this ensures the higher economic benefit of cotton in Xinjiang compared with other inland cotton producing areas. Compared with other crops such as safflower, maize, and wheat, cotton has outstanding advantages and stable benefits including high profit, advantage of planting technology and preferential policy4. Soil organic matter, available P, and available K, and trace elements, including available Mn, available Fe, and available Cu exhibit different trends and degrees of change, which leads to imbalances in soil nutrients in cotton fields5. In addition, the yield of cotton fields continuously cropped for the same number of years was correlated with soil nutrient content. Soil organic matter and available N content were higher in high-yielding fields. However, there was no significant difference between available P and available K6. In addition, owing to the deterioration of the soil environment, continuous cropping leads to the frequent occurrence of cotton pests and diseases, such as cotton aphids, cotton bollworms, Verticillium wilt, and cotton root rot8.In continuous cropping systems, demand for nutrients causes imbalances in soil nutrients in cotton fields, affects the growth, nutrient uptake, and utilization efficiency of roots, and ultimately reduces yield. Previous studies have reported a significant correlation between cotton yield and soil N, C, and P quality ratios during continuous cropping9. Organic matter is an important component of organic fertilizers, and organic acids contained in organic matter can acidify nutrients improving their effectiveness10. In addition to chemical fertilizers, manure is an important source of nutrients for agricultural production in China. Application of manure helps maintain soil nutrient balance, improves soil structure, and moisture-holding capacity, and is beneficial for environmental protection compared with the application of chemical fertilizers alone11. As a result of organic amendments, heterogeneity in resource distribution is likely to arise, and the subsequent microbial decomposition of both simple and complex organic materials will release organic and inorganic N for plant uptake. The spatial and temporal release of these nutrients will be more complex than when inorganic nutrients are applied directly12. Tian et al.13 reported that organic fertilizers significantly increased soil organic matter content and active components and promoted nutrient absorption based on 3-year cotton pot experiments. Manure incorporation into subsoil increased transpiration efficiency, and resulted in a doubling of root length density and root surface area in the manured layer14. Organic amendment (chicken manure) improved first order lateral root number, tap root length, fine root morphology  in seedlings, organic fertilizer treatments tended to increase soil ammonium, nitrate, available P, total P, and organic C content15. Similarly, owing to the high nutrient content, organic fertilizer cannot be fully absorbed and utilized by crops, resulting in nutrient leaching and rapid nutrient release, which cannot guarantee to meet the nutrient demands of crops throughout the growth period. In addition, feed additive use in livestock and poultry leads to excessive content of trace elements such as Cu, Fe, Zn, Mn, Co, Se, I, and As in livestock and poultry manure, as well as persistent organic pollutants such as polycyclic aromatic hydrocarbons and organochlorines16. Long-term application of this kind of organic fertilizer will lead to heavy metal pollution in soil and affect the growth and quality of crops.Animal manures have been widely used as fertilizers for centuries. Organic fertilizers contain not only the basic nutrients required by crops but also trace elements. Chicken manure is rich in mineral elements, essential nutrients N, P, and K, and other nutrients that can improve soil physical and chemical properties19. Biochar can improve soil physical and chemical properties, reduce nutrient leaching, optimize soil microbial population structure and richness, and promote the growth and function of crop roots20. Adding biochar reduced soil compactness and affected soil water holding capacity and microbial and root growth21. Plants grown in biochar-amended soil had greater root mass and root length densities, and total and individual root lengths for secondary and tertiary roots compared with plants grown in unamended soil22.As a soil amendment agent, biochar has unique physical and chemical characteristics. By improving soil physical structure, optimizing microbial growth and reproduction, reducing soil nutrient leaching, and reducing the occurrence of pests and diseases, biochar can promote crop growth, development, yield, and qualityet al.23 showed that the addition of corn straw biochar could promote the growth of the rice root system in sandy loam soil, increase root volume, total and active absorption area, and maintain high Root TTC reducing capacity. In addition, biochar indirectly improved soil fertility mainly by affecting the soil environment, and the main nutrients in biochar exist in the form of biological solids, and the effectiveness of nutrients depends on the biomineralization process, resulting in slow nutrient supply from biochar24. In addition, biochar has strong adsorption functions, which can effectively adsorb toxic substances produced by continuous cropping and heavy metals from organic fertilizer application25.The results of Zhang 26, improving the potential value of biochar as a soil amendment. In the present study, we focused on the effects of organic fertilizer with and without biochar addition on soil and cotton root system properties in a cotton field under continuous cropping in Xinjiang. Our aim was to provide a theoretical basis for further developing cotton continuous cropping in Xinjiang. Our hypothesis was that organic fertilizer both with and without biochar addition can improve soil nutrients, cotton root growth, and biomass accumulation but that the addition of biochar would results in more improved properties.Biochar combined with organic fertilizer not only effectively alleviates the problems of excessive fertilizer use such as environmental pollution but also activates soil microorganisms and soil enzymesThe total root length and root surface area were higher in the bud stage than the harvesting stage Fig. . In contOrganic manure combined with biochar significantly increased total root length compared with no biochar Fig. . SimilarThe application of organic fertilizer significantly increased the content of soil organic matter, total N, and total P in the bud and harvesting stages. The application of organic fertilizer significantly increased total K content of soil in the bud stage and decreased total K content of soil in the harvesting stage. The organic matter, total N, total P, and total K content of soils in the bud and harvesting stages were significantly increased by the combination of two levels of organic manure and biochar compared with those without biochar Table . The corThe highest Root TTC reducing capacity was in the bud stage except in M3B0, M6B0, and M6B3 Fig. . The higThe highest root, GS, and NR activity were observed under treatments with organic manure combined with 1% biochar in the bud stage but with 3% biochar in the harvesting stage Fig. . FurtherApplication of organic fertilizer significantly increased the underground and aboveground biomass of cotton in the bud and harvesting stages Table . In bud 27, and cotton in the bud stage needs a larger root system to absorb nutrients to maintain growth, and given the poor physical structure of the soil and frequent occurrence of sandstorms, to maintain the supporting functions of the cotton plant. In addition, the stimulating effect of high organic fertilizer (6%) on cotton rhizosphere microorganisms further promoted the effective growth of cotton roots and optimized root architecture28.The results showed that the application of organic fertilizer could improve soil enzyme activity, soil microbial population structure, root respiration rate, and total root length, root surface area, and root volume significantly increased. This may be due to the application of manure to soils providing additional nutrients that facilitate plant growth29. The total root length, total surface area, and Root TTC reducing capacity of cucumber significantly increased with corn straw biochar30. Our results showed that organic fertilizer combined with biochar could significantly promote cotton root growth, while maintaining cotton root growth in the later growth stage. Firstly, soil fertility is supplemented by biochar nutrients and trace elements, and secondly, biochar provides living and reproductive space for microorganisms, which improves the structure and abundance of the microbial community31. Microorganisms further promote nutrient release of organic fertilizer and biochar32. Nutrients mostly exist in organic form in biochar; therefore, the slow degradation process of microorganisms is required, which results in the nutrient release from biochar being slower than that of organic fertilizer, ensuring nutrient supply for the whole growth period. Organic fertilizer combined with low biochar (1%) resulted in the highest cotton root growth, while high biochar (3%) had a negative effect on cotton root growth. It seems that plants are able to take up nutrients with a smaller root system when supplies are optimal, so they have less need of a large root system33.Biochar has a large specific surface area and strong ionic functional groups due to its highly concentrated C and other nutrients, as well as its porous structure. Through improving soil nutrients, physical and chemical properties, crop root growth, and absorption, crop yield can also be increased34. Higher Root TTC reducing capacity indicated that the root system was in a healthy soil environment and had a higher metabolic level. Incorporation of organic sources into paddy soil could improve root morphological characteristics and Root TTC reducing capacity of rice plants by increasing root density, active adsorption area, and root surface phosphatase activity35. The present study showed that the application of organic fertilizer alone significantly enhanced cotton Root TTC reducing capacity, and owing to the poor nutrient content and physical and chemical properties of grey desert soil, more organic fertilizer was needed to improve the soil environment. Therefore, 6% organic fertilizer treatment resulted in the highest physiological activity of cotton roots.Soil fertility and crop nutrient uptake and utilization efficiency are the main factors restricting crop yield, and efficient nutrient uptake is inseparable from the healthy growth and development of crop roots36. However, in the present study, a high proportion of biochar (3%) could reduce or not affect Root TTC reducing capacity in the bud stage. On the one hand, the growth of cotton roots may be affected by the self-toxicity of aromatic and phenolic substances in high-concentration biochar37. On the other hand, biochar and soil have high C/N ratio under high-concentration biochar, which affects the transformation and availability of soil organic C and N, and reduces the availability of soil N38, affecting physiological activities such as root respiration.In addition, the Root TTC reducing capacity of cotton with biochar was higher than that with organic fertilizer alone. The slow release of nutrients from organic manure and biochar provides a healthy soil environment for root survival and activity. It not only provides sufficient raw materials and conditions for root redox reaction, but also adsorbs toxic substances produced in continuous cropping systems39.The results showed that organic fertilizer combined with 1% biochar significantly increased the content of total P and total K in cotton field in the harvesting stage. The correlation analysis showed that the Root TTC reducing capacity of cotton was positively correlated with total K in the bud stage and negatively correlated in the harvesting stage. K may be the key nutrient for physiological activity of cotton roots in this region. The growth and physiological activity of cotton roots peaked in bud stage, and higher K content promoted metabolic activity in this stage. Conversely, owing to the aging damage of cotton roots during harvesting, the roots were fragile. At the same time, the high concentration of K ions in soil destroyed the balance of internal and external ions, which affected the normal physiology of cotton roots and further affected the uptake of ions and nutrients in soil solutes41. NR and GS are the key enzymes for N uptake. The activity of NR and GS can reflect the efficiency of N uptake and utilization by crops43. The results showed that the application of organic fertilizer increased the activity of NR and GS in cotton roots. Owing to the different roles and functions of the two enzymes in the process of N uptake, there are differences in their performance in the different growth stages45. In the early stage of cotton growth, N and other nutrients are mainly absorbed, while in the late stage of cotton growth, efficient transformation and transport efficiency, as well as the efficient synthesis of amino acids, are needed to ensure the formation of cotton fibre47. At the same time, NR is an inducible enzyme, because the application frequency and amount of fertilizer in early growth stage of cotton are higher than that in late growth stage, the NR activity in the bud stage is higher than that in harvesting stage.The results showed that under the same soil fertility conditions, the roots of high nutrient uptake and utilization crops had root architecture and enzyme activity beneficial to nutrient uptake and transformationThe highest root GS activity was in treatments with 1% and 3% biochar in the bud and harvesting stages, respectively. The low amount of biochar added in the early growth stage was enough to meet the growth needs of cotton, while in the late growth stage, more nutrients are needed. The NR activity of cotton roots did not change significantly in the bud stage but was significantly higher in the harvesting stage, indicating that the application of organic fertilizer and biochar played an important role in the nutrient absorption of cotton in the later growth stage.et al.48 showed that when the C/N ratio of organic materials was between 20 and 40, the C/N cycle of flue-cured tobacco was more coordinated. Among them, the NR activity and free amino acid content of 20 treatment were significantly higher than those of other treatments in the middle and long term, which was conducive to the accumulation of dry matter. This study showed that the application of organic fertilizer combined with biochar could effectively improve the activity of NR in cotton roots, possibly due to the C/N ratio of organic fertilizer combined with biochar suitable for cotton growth, which could effectively improve the nutrient uptake and utilization efficiency of cotton roots49.In addition, the correlation analysis showed that the physiological activity of cotton roots was closely related to soil nutrient status caused by reduction. Yang 50. The compost added to the greenhouse medium stimulated the rooting of geranium cuttings significantly, increasing their root length by almost 80% and root biomass by over 40%. It also affected a 35% increase in shoot biomass51. Gou et al.52 showed that peanut shell biochar could significantly increase the main root length, diameter, total surface area, and total root density of tomato, and the main root diameter was the main factor causing the yield increase. The middle level of biochar addition(1%) was the most significant factor for yield improvement. In addition, the results showed that proper application of organic fertilizer could effectively improve the physiological activity of cotton root systems, promote N assimilation, and improve cotton yield and fibre quality53. The results showed that root architecture not only affected the absorption and utilization efficiency of N and K in soil but also affected the content of N and K in tobacco leaves, thus affecting the quality of tobacco leaves54. This study also showed that an increase in soil nutrient content, especially total N content, stimulated the activity of root-related enzymes, promoted the elongation of cotton roots, and established a fine-root architecture. Better root morphological characteristics or strong metabolic activity can affect soil microenvironment around roots by root exudates, which promote cotton roots adaptation to soil environment and effective absorption and utilization of soil nutrients. Cotton yield was positively correlated with the activity of N conversion and absorption enzymes in roots. Therefore, better root management is a fundamental measure to improve cotton yield.Previous studies have reported that organic manure increases plant crop growth and yield in cultivated fields by regulating root morphology and physiological plasticityet al.55 showed that rice yield increased with the increase in biochar application rate after the combination of biochar and N fertilizer. The rice yield of Qu et al.56 in Hunan and Jiangxi showed that there was no difference in rice yield when biochar was applied alone. The rice yield was significantly higher when biochar was combined with N fertilizer. However, the results of Steiner et al.57 showed that compared with the treatment without biochar, the dry matter weight of crops treated with biochar decreased by 31.2% and the yield by 56.3% after applying N fertilizer. From the above results, the key to whether biochar can promote crop growth and increase yield is the combination and proportion of fertilizer and biochar and, such as C/N ratio59. Therefore, when applying biochar, soil fertility should be fully considered, and an appropriate C/N ratio should be used60.The results of Asai 61, which is not conducive to the improvement of cotton yield. Moreover, there is a higher economic benefit from using organic fertilizers combined with 1% biochar.In this study, the application of organic fertilizer and biochar alone increased the C/N ratio of cotton field soil, promoted the increase in cotton biomass and cotton seed cotton yield. However, compared with 3% biochar, 1% biochar combined with organic fertilizer had the highest cotton yield. The C content of biochar is more than 50%; therefore, excessive addition (such as 3%) will affect the transformation and availability of organic C and N in soilIn the present study, the combination of organic fertilizer and biochar could alleviate the issues associated with of continuous cropping of cotton fields by improving soil nutrient status, improving cotton root physiology, and optimizing root morphology. The application of organic fertilizer had a significantly positive effect on the growth and yield of cotton, and the higher concentration of organic fertilizer (6%) had a more significant effect on the growth, physiological activity, and yield of cotton roots. Notably, the lower concentration of biochar (1%) promoted cotton root growth and improved root physiological activity. The physiological activity of cotton roots was inhibited when high concentrations of biochar (3%) were added. The results showed that the activity of cotton roots, GS, and NR decreased. In addition, compared with the application of organic fertilizer alone, the increase in cotton yield was more significant by applying biochar, but the amount of biochar should be appropriate.The experiment was conducted from April to October 2018 at Shihezi University Test Site , which is located in Xinjiang Province of Northwest China. The station belongs to temperate continental climate where 7.0 °C remains to be the average air temperature on yearly basis whereas in April to October, the mean maximum temperature is 26 °C, and the mean minimum temperature is 11 °C. The annual precipitation, annual evaporation, and annual sunshine duration are 210.6 mm, 1 664.1 mm, and 2 861.2 h, respectively. And the frost-free period usually lasts 170 d Fig. .Figure 5−1, 1.25 g kg−1, 1.56 g kg−1 and 44.80 g kg−1, respectively, and an available N, P, and K content of 45.97 mg kg−1, 46.77 mg kg−1and 649.16 mg kg−1.The tested soils were collected from cotton fields in Shihezi University Test Site, which had been cropped for 28 consecutive years and had serious continuous cropping obstacles. Soil samples were collected from the experiment field at 0–30 cm soil depth and were thoroughly mixed to make a representative composite soil sample. The soil used in this study was Grey desert soil that is loess-like diluvial-alluvial, partly Aeolian and slope sediments. It is a kind of soil type with less gravel and more fine grains in desert. The soil used in this study had a soil organic matter (SOM), total N, P, and K content of 28.57 g kg−1, 17.8 g kg−1, 13.7 g kg−1 and 21.8 g kg−1, respectively. The tested biochar produced from cotton straw collected from experimental field. The cotton straw was dried at room temperature, and crushed mechanically. Temperature achieved with biochar product at 450 °C with residence time of 6 h. Briefly, the biochar had a pH of 10.04 and contained 625 g kg−1 SOC, 0.89 g kg−1 TN, 6.9 g kg−1 TP, and 23.7 g kg−1 TK. The biochar was passed through a 2 mm sieve before experiment.The organic manure is chicken manure that had a SOM, total N, P, and K content of 235.2 g kgcv.Xinluzao 45 of cotton (Gossypium hirsutum L.), a widely planted cultivar in Xinjiang China, was used in the experiment. The field soil was amended with organic manure at 3 rate of 0%, 3%, 6% of the soil dry weight (DW) and combined with rate of 0%, 1%, 3% of biochar. Two growth periods (bud stage and harvesting stage) in the experiment and each treatment was replicated 4 times. Before experiment, the PVC pipe with a height of 40 cm and an inner diameter of 20 cm was buried vertically in the cotton field. The soil, organic manure, biochar and basic fertilizer should be fully mixed. According to the bulk density of 1.30 g cm−3, and per pipe with the air-dried soil 15 kg. Except for the difference of treatments, all fertilizers applied in cotton growth period were N 440 kg hm−2, P2O5 420 kg hm−2 and K2O 270 kg hm−2. Specially, 20% N, 70% P2O5 and 100% K2O of total fertilizers were applied once as a basal. The plants were watered by a drip irrigation system. Residual nitrogen fertilizer was used as topdressing fertilizer, and was applied with water drip in five times during cotton growth period, accounting for 15%, 15%, 20%, 20% and 10% of the total amount of fertilizer applied, respectively. During the whole growth period of cotton, 9 irrigation times were carried out, and the total amount of irrigation was 520 mm. Irrigation and fertilization by drip irrigation under mulch. Cotton was sown on April 30, 2018, with 10 seeds per pot. One seedling with healthy and similar growth were retained in each pot at the time of two leaves and one core. Standard cultural practices were performed during the experiment , in order to produce healthy cotton.62, respectively. The contents of TP, and TK of soil samples were measured by the molybdate colorimetric method after perchloric acid digestion, and the flame photometry method after melting with sodium hydroxide, respectively62.At bud stage  and harvesting stage  a mixed soil sample was taken from 5 randomly selected points within each pot. The soils were air-dried and ground to pass through a 1 mm sieve and stored for analyses. Soil organic matter and total N were determined by the dry combustion method at a temperature of 950 °C in the presence of pure oxygen and by the semimicro Kjeldahl method63.The bud and harvest stages are important periods in cotton planting. The bud stage is the transition period from vegetative to reproductive growth. The function of the root system plays an important role, which directly affects the later yield. The harvest stage is the overlapping time of vegetative and reproductive growth. It is the key period of cotton yield and fiber development. The growth strategy of the cotton aboveground part and root system is important for the formation of final yield. At bud stage (65 days) and harvesting stage (135 days), all plants in each pot were collected and separated into roots and culms. The root samples were shifted to the laboratory in an ice box within 4 hours. The individual samples were cleaned with de-ionized water (4 °C) to remove residual soil particles and stored in a refrigerator. Root TTC reducing capacity, glutamine synthetase activity (GS) and nirate reductase activity (NR) were determined as described by LiRoots were scanned by scanning (Epson Expression/STD 1600 Scanner) at 800 dpi, and analyzed by winRHIZO root analysis system (Canada Regent Company), in order to measure the Average Root Diameter (ARD), Root Surface Area (RSA), Total Root volume (TRV) and Total Root Length (TRL).Root dry mass (RDM) and shoot dry mass (SDM) were determined after drying at 105 °C for 30 min and residence temperature at 70 °C to constant weight. Root-shoot ratios were determined by dividing root biomass by shoot biomass. At harvest, 20 plants in the central row of each plot were harvested to measure seed cotton yield and yield components (number of bolls and seed cotton weight per plant). The seed cotton yield was calculated as the seed cotton weight per plant × number of bolls per plant × plant density.The experiment was conducted in a randomised complete block design, with split-plot arrangements so that the effects of biochar on physical and chemical properties of soil, root physiology, root morphology, and dry matter accumulation of cotton could be tested. The data collected was analyzed using two-way analysis of variance (ANOVA) with the software package SPSS 19.0 . Means were compared based on the least significant difference test (LSD) at the 0.05 probability level.