Effects of saline irrigation on soil salt accumulation and grain yield in the winter wheat-summer maize double cropping system in the low plain of North China

In the dominant winter wheat （WW）-summer maize （SM） double cropping system in the low plain located in the North China, limited access to fresh water, especially during dry season, constitutes a major obstacle to realize high crop productivity. Using the vast water resources of the saline upper aquifer for irrigation during WW jointing stage, may help to bridge the peak of dry season and relieve the tight water situation in the region. A field experiment was conducted during 2009-2012 to investigate the effects of saline irrigation during WW jointing stage on soil salt accumulation and productivity of WW and SM. The experiment treatments comprised no irrigation （T1）, fresh water irrigation （T2）, slightly saline water irrigation （T3：2.8 dS m-l）, and strongly saline water irrigation （T4：8.2 dS m-1） at WW jointing stage. With regard to WW yields and aggregated annual WW-SM yields, clear benefits of saline water irrigation （T3 ＆ T4） compared to no irrigation （T1）, as well as insignificant yield losses compared to fresh water irrigation （T2） occurred in all three experiment years. However, the increased soil salinity in eady SM season in consequence of saline irrigation exerted a negative effect on SM photosynthesis and final yield in two of three experiment years. To avoid the negative aftereffects of saline irrigation, sufficient fresh water irrigation during SM sowing phase （i.e., increase from 60 to 90 mm） is recommended to guarantee good growth conditions during the sensitive early growing period of SM. The risk of long-term accumulation of salts as a result of saline irrigation during the peak of dry season is considered low, due to deep leaching of salts during regularly occurring wet years, as demonstrated in the 2012 experiment year. Thus, applying saline water irrigation at jointing stage of WW and fresh water at sowing of SM is most promising to realize high yield and fresh irrigation water saving.

Integration of aspect and slope in snowmelt runoff modeling in a mountain watershed

This study assessed the performances of the traditional temperature-index snowmelt runoff model(SRM) and an SRM model with a finer zonation based on aspect and slope(SRM + AS model) in a data-scarce mountain watershed in the Urumqi River Basin,in Northwest China.The proposed SRM + AS model was used to estimate the melt rate with the degree-day factor(DDF) through the division of watershed elevation zones based on aspect and slope.The simulation results of the SRM + AS model were compared with those of the traditional SRM model to identify the improvements of the SRM + AS model's performance with consideration of topographic features of the watershed.The results show that the performance of the SRM + AS model has improved slightly compared to that of the SRM model.The coefficients of determination increased from 0.73,0.69,and 0.79 with the SRM model to 0.76,0.76,and 0.81 with the SRM + AS model during the simulation and validation periods in 2005,2006,and 2007,respectively.The proposed SRM + AS model that considers aspect and slope can improve the accuracy of snowmelt runoff simulation compared to the traditional SRM model in mountain watersheds in arid regions by proper parameterization,careful input data selection,and data preparation.

Shoot and root traits in drought tolerant maize(Zea mays L.) hybrids

This study aimed to investigate the differences in shoot and root traits, and water use and water use efficiency（WUE） in drought tolerant（DT） maize（Zea mays L.） hybrids under full and deficit irrigated conditions. A two-year greenhouse study was conducted with four hybrids（one conventional hybrid, 33D53AM, two commercial DT hybrids, P1151 AM, N75H, and an experimental hybrid, Exp HB） grown under two water regimes（I（100） and I（50）, referring to 100 and 50% of evapotranspiration requirements）. Under water stress, the hybids P1151 AM, N75, and Exp HB showed more drought tolerance and had either greater shoot dry weight or less dry weight reduction than the conventional hybrid（33 D53 AM）. However, these three hybrids responded to water stress using different mechanisms. Compared with the conventional hybrid, the two commercial DT hybrids（P1151 AM and N75H） had a smaller leaf area, shoot dry weight, and root system per plant. As a result, these hybrids used less water but had a higher WUE compared with the conventional hybrid. In contrast, the experimental hybrid（ExpHB） produced more shoot biomass by silking stage at both irrigation levels than all other hybrids, but it had relatively lower WUE. The hybrids demonstrated different drought response mechanisms that may require different irrigation management strategies. More investigation and validation are needed under field conditions and in different soil types.

Genetic Diversity and Population Structure of Tomato (<i>Solanum lycopersicum</i>) Germplasm Developed by Texas A&M Breeding Programs

Genetic variation developed in plant breeding programs is fundamental to creating new combinations that result in cultivars with enhanced characteristics. Over the years, tomato (Solanum lycopersicum) breeding programs associated with the Texas A&M University system have developed morphologically diverse lines of tomatoes selected for heat tolerance, fruit quality, and disease resistance to adapt them to Texas growing conditions. Here we explored the intraspecific genetic variations of 322 cultivated tomato genotypes, including 300 breeding lines developed by three Texas A&M breeding programs, as an initial step toward implementing molecular breeding approaches. Genotyping by sequencing using low coverage whole-genome sequencing (SkimGBS) identified 10,236 high-quality single-nucleotide polymorphisms (SNPs) that were used to assess genetic diversity, population structure, and phylogenetic relationship between genotypes and breeding programs. Model-based population structure analysis, phylogenetic tree construction, and principal component analysis indicated that the genotypes were grouped into two main clusters. Genetic distance analysis revealed greater genetic diversity? among the products of the three breeding programs. The germplasm developed at Texas A&M programs at Weslaco, College Station, and by Dr. Paul Leeper exhibited genetic diversity ranges of 0.175 - 0.434, 0.099 - 0.392, and 0.183 - 0.347, respectively, suggesting that there is enough variation within and between the lines from the three programs to perform selection for cultivar development. The SNPs identified here could be used to develop molecular tools for selecting various traits of interest and to select parents for future tomato breeding.

Comparative Assessment of Growth and Gene Regulation between 4 Serotypes of <i>Streptococcus pneumoniae</i>in Broth and Cell Culture

Streptococcus pneumoniae is a medically important pathogen capable of causing human infections of pneumonia, bacteremia, otitis media, and meningitis. Although there are vaccinations available, infections with S. pneumoniae still remains a global problem. S. pneumoniae is a highly adaptable bacterial species with numerous serotypes based on capsular polysaccharides. The different serotypes vary in their ability to colonize and causing pathology. Here we compared the regulation of five different virulence factors from four common serotypes of S. pneumoniae that vary in their carriage, morbidity, and mortality rates in the human population using two different in vitro methods, broth and cell culture. We determine that there is variation of virulence factor gene regulation within a serotype using two different culture methods, and variation between the serotypes in the same culture condition. The regulation of genes appeared to have a correlation with the ability of the various serotypes to grow in broth culture, adhere to cultured lung cells, and invade the cultured lung cells, as serotypes that shared similar regulation of virulence factors tended to behave similarly in culture. Many studies with S. pneumoniae rely on the use of one selected serotype, but since there is a wide variation in the growth and regulatory mechanisms of these bacteria. As demonstrated here, future studies should utilize more strains in models before concluding mechanisms of pathobiology.

Heterosis of Vine Decline Disease Resistance Caused by the Fungus Monosporascus cannonballus in Melons (Cucumis melo L)

Vine decline disease (VDD) constitutes a menace to melons worldwide. Especially, the one caused by the fungus Monosporascus cannonballus. Thus, resistant plant material must be released to help growers. Hence, our goal was to develop resistant plant material to VDD. More than 600 melon accessions are expected to be tested for disease resistance in M. cannonballus infested soil in Weslaco, Texas, USA, to identify resistance to VDD, and other important traits. So far, at most 7 lines were found to be resistant to VDD and some of them were used to develop elite, muskmelon inbred lines by pedigree breeding following single or double backcrosses. These elite parents were crossed to each other to develop the hybrids M3 and M4. They were also tested in the same infested field in Weslaco. The hybrids were grown using standard commercial practices followed by growers and when their fruits were ready, their roots were sampled as well as scored for disease severity to estimate high and mid-parent heterosis Our results indicate the existence of heterosis regarding resistance to VDD. Thus, resistant plant material can be developed and selection for resistance can be accomplished.

A New Technique for Use in Culturing Prokaryotes Comprising the Mouse Intestinal Microbiome

The microbiome has a profound impact on host fitness. pH, oxygen, nutrients, or other factors such as food or pharmaceuticals, subject the microbiome to variations in the gastrointestinal tract. This variation is a cause for concern given dysbiosis of the microbiome is correlated with various disease states. Currently, much research relies on model organisms to study microbial communities since intact microbiomes are challenging to utilize. The objective of this study is to culture an explanted colon microbiome of 4 Balb/c mice to develop an in vitro tool for future microbiome studies. We cultured homogenates of the distal colons of 4 mice in trans-well culture dishes. These dishes were incubated for 24 hours in two different oxygen concentration levels and the pH was compared before and after incubation of the cultures. To analyze the integrity of the microbiome, we utilized massively paralleled DNA sequencing with 16S metagenomics to characterize fecal and colon samples to speculate whether future studies may utilize feces in constructing an in vitro microbial community to spare animal lives. We found that pH and familial relationships had a profound impact on community structure while oxygen did not have a significant influence. The feces and the colon were similar in community profiles, which lends credence to utilizing feces in future studies. The gut microbiome is of great interest and great importance for studies in a variety of different diseases. Many laboratories do not have access to germ-free mice, which is one optimal way to study mammalian microbiomes, but this technique allowed for the in vitro culturing of a majority of the prokaryotes isolated from the colons of mice. This may allow an alternative to study the interactions of this very diverse population of microorganisms without the need for germ-free conditions.

基于中分辨卫星影像的农用航空喷药效果评估（英文）

遥感技术能被用于大尺度作物化学喷药效果检测,这为精准农业航空施药发展提供了重要的技术支撑。利用M-18B农用飞机在4米的飞行高度喷施化学农药混合剂(杀菌剂和植物生长调节剂),去控制水稻爆发性疾病--叶片纹枯病和促进水稻植株的生长。施药一周后,喷药区的卫星影像被获取并计算植被指数,同时采集了地面化学农药的药液沉积量。分析了药液雾滴沉积量和植被指数的关系,结果显示,单相光谱特征(NDVI)和液滴沉积点密度(DDPD点·cm^(-2))的相关系数是0.315,p-value为0.035;时间变化特征(MSAVI)和液滴沉积体积密度(DDVDμL·cm^(-2))之间的相关系数是0.312,p-value为0.038。另外,水稻生长活力最旺盛的范围都出现在喷洒区域内,植株活力随着药液漂移距离的增加逐步减少。同时,相同的变化趋势也出现在雾滴沉积量与光谱特征的空间变化插值图中。由此得知,从卫星图像中计算的植被指数NDVI和MSAVI,可以用来评估大尺度农田的农用航空药液喷洒效果。

低空遥感平台下可见光与多光谱传感器在水稻纹枯病病害评估中的效果对比研究

高效无损地评估农作物病害等级,对于实际农业生产和研究都具有重要意义。研究探讨了基于低空无人机遥感平台进行水稻纹枯病病害等级评估的可行性,分析可见光与多光谱传感器的光谱响应差异及其对感病水稻光谱反射率获取的影响,并定量对比两种传感器的病害监测效果。实验研究区由67个不同品种的水稻小区组成,每块小区均分为相接的纹枯病接种区和侵染区。以大疆精灵Phantom 3 Advanced小型消费级无人机作为搭载平台,分别搭载该无人机系统自带的可见光传感器和MicasenseRedEdge^(TM)多光谱传感器获取遥感影像。同时,通过植保专家现场调查的方式识别病害等级,并利用Trimble公司的手持式NDVI测量仪获取实测NDVI值。基于影像拼接、波段叠合、辐射校正后的预处理结果,对可见光图像的接种区和侵染区共134个小区计算七种可见光植被指数,即NDI(normalized difference index), ExG(excess green), ExR(excess red), ExG-ExR, B~*, G~*, R~*,多光谱图像除上述可见光指数外再计算NDVI(normalized difference vegetation index), RVI(ratio vegetation index)和NDWI(normalized difference water Index)三种多光谱植被指数。将计算得到的图像植被指数与地面实测NDVI进行相关性分析,以选取两种传感器的最优图像植被指数建立水稻纹枯病病害等级反演模型。相关性分析结果表明,基于多光谱传感器计算的图像NDVI与实测NDVI拟合度最高,接种区R^2为0.914, RMSE为0.024,侵染区R^2为0.863, RMSE为0.024。对于可见光传感器, NDI与实测NDVI的相关性最好,接种区R^2为0.875, RMSE为0.011,侵染区R^2为0.703, RMSE为0.014。比较两种传感器两种区域的同一图像植被指数与实测NDVI的一致性,除B~*外, NDI, ExR, ExG-ExR, G~*, ExG, R~*与实测NDVI基本属于高度相关,在病害严重的接种区,两种传感器对水稻纹枯病的监测效果相近,但在病害相对较轻的侵染区,多光谱传感器的监测更为精确灵敏。基于多光谱图像NDVI建立的病害等级反演模型,R^2达到0.624, RMSE为0.801,预测精度达到90.04%,模型效果良好。而基于可见光图像NDI建立的反演模型,R^2为0.580, RMSE为0.847,预测精度为89.45%,效果稍差。对比分析可见光与多光谱传感器的光谱响应曲线,可见光传感器可获取可见光范围的红、绿、蓝三个波段,波段范围互相重叠,多光谱传感器包含五个成像单元,可独立获取从可见光到近红外的五个窄波光谱波段,提供更加准确的光谱信息。比较传感器获取的接种区和侵染区水稻平均反射率曲线得出,多光谱传感器不仅在可见光波段反映了较可见光传感器更强的差异,在红边和近红外波段差异则更加明显,这说明专业窄波段传感器在病害监测方面较宽波段消费级传感器更有优势。综上所述,基于可见光与多光谱传感器的低空无人机遥感平台进行水稻纹枯病病害等级评估是可行的,多光谱传感器精确灵敏,可用于纹枯病的早期监测,可见光传感器效果稍差但经济易于推广。研究结果为病虫害防治提供决策支持,有助于推动实现精准农业,保障粮食安全。

A Proposed Systemic Modeling Software for Jujube Fruit Cracking

Jujube fruit cracking has become a major concern in jujube production. It can affect fruit quality and yield and crop productivity, resulting in significant economic loss. Recent advances in jujube fruit cracking research provide opportunities to improve our understanding of the impacts of environmental factors and plant physiological metabolism on jujube fruit cracking. In this article, we have developed a novel systemic modeling software for jujube fruit cracking. The potential function and value of this modeling software are presented. Current issues and future research directions in the modeling of jujube fruit cracking system are also discussed. To our knowledge, this is the first functional and/or integrated modeling software developed for the management of jujube fruit cracking.

High-throughput phenotyping in cotton:a review

Recent technological advances in cotton(Gossypium hirsutum L.) phenotyping have offered tools to improve the efficiency of data collection and analysis.High-throughput phenotyping(HTP) is a non-destructive and rapid approach of monitoring and measuring multiple phenotypic traits related to the growth,yield,and adaptation to biotic or abiotic stress.Researchers have conducted extensive experiments on HTP and developed techniques including spectral,fluorescence,thermal,and three-dimensional imaging to measure the morphological,physiological,and pathological resistance traits of cotton.In addition,ground-based and aerial-based platforms were also developed to aid in the implementation of these HTP systems.This review paper highlights the techniques and recent developments for HTP in cotton,reviews the potential applications according to morphological and physiological traits of cotton,and compares the advantages and limitations of these HTP systems when used in cotton cropping systems.Overall,the use of HTP has generated many opportunities to accurately and efficiently measure and analyze diverse traits of cotton.However,because of its relative novelty,HTP has some limitations that constrains the ability to take full advantage of what it can offer.These challenges need to be addressed to increase the accuracy and utility of HTP,which can be done by integrating analytical techniques for big data and continuous advances in imaging.

Parental Selection in Rice Cultivar Improvement

The evaluation of rice （Oryza safiva L.） cultivars assists breeders in identifying useful trait relationships and in selecting parents as donors of specific traits. This study was conducted to compare long-grain rice cultivars using genotype x trait （GT） biplot analysis and determine potential donors of traits related to grain yield and quality. Seventeen cultivars in the 2005 and 2006 Uniform Regional Rice Nursery in Beaumont, Texas, USA were analyzed for 20 traits using GT biplot analysis. The GT biplots showed the diversity among cultivars with regards to yield-related traits. Cultivars recommended as donor parents were： Trenasse, Spring, Presidio, and Cocodrie for high grain yield and head rice rate Trenasse and Presidio for semi-dwarfness; Banks for tall plant height; Wells for high flag leaf area, panicle weight, and number and mass of filled grains per panicle; Hidalgo for high tiller density; Francis for high number of spikelets per panicle; Spring and Trenasse for short flowering duration; Cheniere for more days to heading and maturity and Spring for less days; and Spring and Hidalgo for high grain weiqht. Breeders can use these cultivars with specific traits to increase qrain yield and quality.

Minor alleles are associated with white rust(Albugo occidentalis)susceptibility in spinach(Spinacia oleracea)

Minor alleles(MA)have been associated with disease incidence in human studies,enabling the identification of diagnostic risk factors for various diseases.However,allelic mapping has rarely been performed in plant systems.The goal of this study was to determine whether a difference in MA prevalence is a strong enough risk factor to indicate a likely significant difference in disease resistance against white rust(WR;Albugo occidentalis)in spinach(Spinacia oleracea).We used WR disease severity ratings(WR-DSRs)in a diversity panel of 267 spinach accessions to define resistant-and susceptibility-associated groups within the distribution scores and then tested the single-nucleotide polymorphism(SNP)variants to interrogate the MA prevalence in the most susceptible(MS)vs.most resistant(MR)individuals using permutation-based allelic association tests.A total of 448 minor alleles associated with WR severity were identified in the comparison between the 25%MS and the 25%MR accessions,while the MA were generally similar between the two halves of the interquartile range.The minor alleles in the MS group were distributed across all six chromosomes and made up~71%of the markers that were also strongly associated with WR in parallel performed genome-wide association study.These results indicate that susceptibility may be highly determined by the disproportionate overrepresentation of minor alleles,which could be used to select for resistant plants.Furthermore,by focusing on the distribution tails,allelic mapping could be used to identify plant markers associated with quantitative traits on the most informative segments of the phenotypic distribution.

Spectral Crop Coefficient Approach for Estimating Daily Crop Water Use

While the amount of water used by a crop can be measured using lysimeters or eddy covariance systems, it is more common to estimate this quantity based on weather data and crop-related factors. Among these approaches, the standard crop coefficient method has gained widespread use. A limitation of the standard crop coefficient approach is that it applies to “standard conditions” that are invariant from field to field. In this article, we describe a method for estimating daily crop water use (CWU) that is specific to individual fields. This method, the “spectral crop coefficient” approach, utilizes a crop coefficient numerically equivalent to the crop ground cover observed in a field using remote sensing. This “spectral crop coefficient” Ksp is multiplied by potential evapotranspiration determined from standard weather observations to estimate CWU. We present results from a study involving three farmers' fields in the Texas High Plains in which CWU estimated using the Ksp approach is compared to observed values obtained from eddy covariance measurements. Statistical analysis of the results suggests that the Ksp approach can produce reasonably accurate estimates of daily CWU under a variety of irrigation strategies from fully irrigated to dryland. These results suggest that the Ksp?approach could be effectively used in applications such as operational irrigation scheduling, where its field-specific nature could minimize over-irrigation and support water conservation.

Detecting Musk Thistle (Carduus nutans) Infestation Using a Target Recognition Algorithm

The outbreaks of invasive plant species can cause great ecological and agronomic problems through aggressively competing for environmental resources that could be otherwise utilized by other desirable species. Thus, it is crucial for detecting small infestations before they reach a significant extent that can cause ecological and economic damages over a large geological area. Remote sensing is a proven method for mapping invasion extent and pattern based on geospatial imagery and indicated great repeatability, large coverage area, and lower cost compared with traditional ground-based methods before. We investigated the feasibility and performances of adopting multispectral satellite imagery analyses for mapping infestation of musk thistle (Carduus nutans) on native grassland, crop field, and residential areas in early June using spectral angle mapper classifier. Our results showed an overall classification accuracy of 94.5%, indicating great potential of using moderate resolution multispectral satellite-based remote sensing techniques for musk thistle detection over a large spatial scale.

Removal of Lithium Citrate from H3A for Determination of Plant Available P

The soil extractant, H3A, has undergone several iterations to extract calcium (Ca), iron (Fe), aluminum (Al), potassium (K), phosphorus (P), ammonium (NH4-N) and nitrate (NO3-N) under ambient soil conditions. Few soil extractants currently used by commercial and university soil testing laboratories can perform multi-nutrient extraction without over- or under-estimating at least one nutrient. Soil pH and plant root exudates have a strong influence on nutrient availability and H3A was developed to mimic soil conditions. Lithium citrate was previously used in the H3A formulation, but resulted in a cloudy supernatant in some samples, complicating laboratory analyses. In this study, we removed lithium citrate and compared the nutrients extracted from the modified (H3A-4) to the established (H3A-3) solutions. We found that the new extractant, H3A-4, produced a clear supernatant even in soils with low pH and high iron and aluminum concentrations. H3A-4 accurately predicts plant available nutrients and is a viable choice for commercial and laboratory settings due to its ease of use.

Comparison of Wheat Yield Simulated Using Three N Cycling Options in the SWAT Model

The Soil and Water Assessment Tool (SWAT) model has been successfully used to predict alterations in streamflow, evapotranspiration and soil water;however, it is not clear how effective or accurate SWAT is at predicting crop growth. Previous research suggests that while the hydrologic balance in each watershed is accurately simulated with SWAT, the SWAT model over or under predicts crop yield relative to fertilizer inputs. The SWAT model now has three alternative N simulation options: 1) SWAT model with an added flush of N (SWAT-flush);2) N routines derived from the CENTURY model (SWAT-C);and 3) a one-pool C and N model (SWAT-One). The objective of this study was to evaluate the performance of SWAT-flush, SWAT-C, and SWAT-One as they affect wheat yield prediction. Simulated yields were compared to wheat yields in a 28-year fertilizer/wheat yield study in Lahoma, OK. Simulated yields were correlated with actual 28-year mean yield;however, none of the available N cycling models predicted yearly yields. SWAT-C simulated average yields were closer than other N sub-models to average actual yield. Annually there was a stronger correlation between SWAT-flush and actual yields than the other submodels. However, none of the N-cycling routines were able to accurately predict annual variability in yield at any fertilizer rate. We found that SWAT-C or SWAT-flush are the most viable choices for accurately simulating long-term average wheat yields although annual variations in yield prediction should be taken into consideration. Further research is needed to determine the effectiveness of SWAT-C and SWAT-flush in determining average and annual yield in various farming regions and with numerous agronomic crops.

A Serratia marcesens Strains Involved in Cotton (<i>Gossypium hirsutum</i>) Boll Infection by a Prokaryote

A boll infection caused by non-traditional cotton pathogens was first reported to occur in the southeastern U.S. Cotton Belt (year 2000) and has since spread to Texas causing significant yield losses. This study was aimed towards investigating the verde plant bug (Creontiades signatus) link between interior boll disease in Texas, USA. Using glasshouse grown bolls, bacteria recovered from locules with disease symptoms from field-grown cotton bolls caged with the piercing-sucking C. signatus were analyzed for the capacity to inflict the disease. For pathogenicity testing, spontaneously generated rifampicin resistant (Rifr) variants were utilized to track the antibiotic resistant bacterium and deter growth of endophytic and contaminating bacteria. To simulate C. signatus feeding, a needle (31 gauge) was employed to inoculate bolls at 13 - 15 days after flower bloom. Bacterial suspensions ranged from 101 - 106 colony forming units/ml. Field infection symptoms were duplicated after two weeks of bacterial exposure. Infectious strains were best categorized as Serratia marcescens based on traditional carbon utilization and enzyme production testing, and a 99% nucleotide sequence identity of 16S ribosomal DNA. Putative S. marcescens representatives isolated from rotted bolls exposed to C. signatus were shown to reproduce field infection symptoms upon inoculation into greenhouse grown fruit. Serratia spp. can inflict disease in alfalfa, cucurbits, and sunflower. The presented data are the first to definitively show that a Serratia sp. has the capacity to infect cotton.

Salt tolerance of seven genotypes of zoysiagrass(Zoysia spp.)

Seven zoysiagrass genotypes were evaluated for salt tolerance in a greenhouse study.The plant materials included Zoysia matrella'Diamond',Z.japonica'Palisades',three Z.matrella×Z.japonica hybrids DALZ 1701,DALZ 1713,and'Innovation',and two Z.minima×Z.matrella hybrids(DALZ 1309 and'Lazer').Treatments included a control(nutrient solution)and two saline treatments representing moderate and high salt levels.The electrical conductivity(EC)was 1.3 dS m−1 for control and moderate(EC5)and high salinity(EC10)were 5.0 and 10.0 dS m−1,respectively.At the end of eight-weeks of treatment,the relative(percent control)shoot dry weight(DW)was greatest in'Diamond'in EC10,and the relative root DW was greatest in DALZ 1309 in EC5.A cluster analysis based on the relative tissue dry weight identified'Diamond',DALZ 1309,and DALZ 1713 as the most salt tolerant genotypes.Additionally,the green leaf area(GLA)index of'Diamond'and DALZ 1713 were 98.8%and 100%,respectively,indicating excellent visual appearance under high salt levels.Bi-weekly clipping DW showed that'Diamond'continued to produce biomass throughout the duration of the study under the EC10 treatment.Sodium(Na^(+))and chloride(Cl−)content in the shoot tissue of the seven turfgrass genotypes indicated that lower concentrations corresponded to greater salt tolerance indicating exclusion of Na+and Cl−from the shoot tissue.Taken together,the genotypes'Diamond'and DALZ 1713 were determined to be the most salt tolerant and recommended for use in areas with high soil or water salinity.

Current status and future trends of precision agricultural aviation technologies

Modern technologies and information tools can be used to maximize agricultural aviation productivity allowing for precision application of agrochemical products.This paper reviews and summarizes the state-of-the-art in precision agricultural aviation technology highlighting remote sensing,aerial spraying and ground verification technologies.Further,the authors forecast the future of precision agricultural aviation technology with key development directions in precision agricultural aviation technologies,such as real-time image processing,variable-rate spraying,multi-sensor data fusion and RTK differential positioning,and other supporting technologies for UAV-based aerial spraying.This review is expected to provide references for peers by summarizing the history and achievements,and encourage further development of precision agricultural aviation technologies.