Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the m...Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.展开更多
Emerging new races of wheat stem rust(Puccinia graminis f.sp.tritici)are threatening global wheat(Triticum aestivum L.)production.Host resistance is the most effective and environmentally friendly method of controllin...Emerging new races of wheat stem rust(Puccinia graminis f.sp.tritici)are threatening global wheat(Triticum aestivum L.)production.Host resistance is the most effective and environmentally friendly method of controlling stem rust.The stem rust resistance gene Sr59 was previously identified within a T2DS 2RL wheat-rye whole arm translocation,providing broad-spectrum resistance to various stem rust races.Seedling evaluation,molecular marker analysis,and cytogenetic studies identified wheat-rye introgression line#284 containing a new translocation chromosome T2BL 2BS-2RL.This line has demonstrated broad-spectrum resistance to stem rust at the seedling stage.Seedling evaluation and cytogenetic analysis of three backcross populations between the line#284 and the adapted cultivars SLU-Elite,Navruz,and Linkert confirmed that Sr59 is located within the short distal 2RL translocation.This study aimed physical mapping of Sr59 in the 2RL introgression segment and develop a robust molecular marker for marker-assisted selection.Using genotyping-by-sequencing(GBS),GBS-derived SNPs were aligned with full-length annotated rye nucleotide-binding leucine-rich repeat(NLR)genes in the parental lines CS ph1b,SLU238,SLU-Elite,Navruz,and Linkert,as well as in 33 BC4F5progeny.Four NLR genes were identified on the 2R chromosome,with Chr2R_NLR_60 being tightly linked to the Sr59resistance gene.In-silico functional enrichment analysis of the translocated 2RL region(25,681,915 bp)identified 223 genes,with seven candidate genes associated with plant disease resistance and three linked to agronomic performance,contributing to oxidative stress response,protein kinase activity,and cellular homeostasis.These findings facilitate a better understanding of the genetic basis of stem rust resistance provided by Sr59.展开更多
Ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR MS)is an advanced instrument capable of separating and determining molecular mass-to-charge ratios with sub-ppm level accuracy.A ...Ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR MS)is an advanced instrument capable of separating and determining molecular mass-to-charge ratios with sub-ppm level accuracy.A typical FT-ICR MS spectrogram can identify hundreds to thousands of formulas in a complex sample.This perspective briefly examines the application of FT-ICR MS to soil organic matter and plant biomass studies,highlighting their significant contributions to sustainable agriculture and environment.展开更多
Remote sensing technologies play a vital role in our understanding of earthquakes and their impact on the Earth's surface.These technologies,including satellite imagery,aerial surveys,and advanced sensors,contribu...Remote sensing technologies play a vital role in our understanding of earthquakes and their impact on the Earth's surface.These technologies,including satellite imagery,aerial surveys,and advanced sensors,contribute significantly to our understanding of the complex nature of earthquakes.This review highlights the advancements in the integration of remote sensing technologies into earthquake studies.The combined use of satellite imagery and aerial photography in conjunction with geographic information systems(GIS)has been instrumental in showcasing the significance of fusing various types of satеllitеdata sourcеs for comprеhеnsivееarthquakеdamagеassеssmеnts.However,remote sensing encounters challenges due to limited pre-event imagery and restricted postearthquake site access.Furthеrmorе,thеapplication of dееp-lеarning mеthods in assеssingеarthquakе-damagеd buildings dеmonstratеs potеntial for furthеr progrеss in this fiеld.Overall,the utilization of remote sensing technologies has greatly enhanced our comprehension of earthquakes and their effects on the Earth's surface.The fusion of remote sensing technology with advanced data analysis methods holds tremendous potential for driving progress in earthquake studies and damage assessment.展开更多
Background India harbors the world’s largest cattle population,encompassing over 50 distinct Bos indicus breeds.This rich genetic diversity underscores the inadequacy of a single reference genome to fully capture the...Background India harbors the world’s largest cattle population,encompassing over 50 distinct Bos indicus breeds.This rich genetic diversity underscores the inadequacy of a single reference genome to fully capture the genomic landscape of Indian cattle.To comprehensively characterize the genomic variation within Bos indicus and,specifically,dairy breeds,we aim to identify non-reference sequences and construct a comprehensive pangenome.Results Five representative genomes of prominent dairy breeds,including Gir,Kankrej,Tharparkar,Sahiwal,and Red Sindhi,were sequenced using 10X Genomics‘linked-read’technology.Assemblies generated from these linked-reads ranged from 2.70 Gb to 2.77 Gb,comparable to the Bos indicus Brahman reference genome.A pangenome of Bos indicus cattle was constructed by comparing the newly assembled genomes with the reference using alignment and graph-based methods,revealing 8 Mb and 17.7 Mb of novel sequence respectively.A confident set of 6,844 Non-reference Unique Insertions(NUIs)spanning 7.57 Mb was identified through both methods,representing the pange-nome of Indian Bos indicus breeds.Comparative analysis with previously published pangenomes unveiled 2.8 Mb(37%)commonality with the Chinese indicine pangenome and only 1%commonality with the Bos taurus pange-nome.Among these,2,312 NUIs encompassing~2 Mb,were commonly found in 98 samples of the 5 breeds and des-ignated as Bos indicus Common Insertions(BICIs)in the population.Furthermore,926 BICIs were identified within 682 protein-coding genes,54 long non-coding RNAs(lncRNA),and 18 pseudogenes.These protein-coding genes were enriched for functions such as chemical synaptic transmission,cell junction organization,cell-cell adhesion,and cell morphogenesis.The protein-coding genes were found in various prominent quantitative trait locus(QTL)regions,suggesting potential roles of BICIs in traits related to milk production,reproduction,exterior,health,meat,and carcass.Notably,63.21%of the bases within the BICIs call set contained interspersed repeats,predominantly Long Inter-spersed Nuclear Elements(LINEs).Additionally,70.28%of BICIs are shared with other domesticated and wild species,highlighting their evolutionary significance.Conclusions This is the first report unveiling a robust set of NUIs defining the pangenome of Bos indicus breeds of India.The analyses contribute valuable insights into the genomic landscape of desi cattle breeds.展开更多
In response to the effectiveness of reforestation in controlling soil erosion,there has been a dramatic increase in forest coverage in the hilly red soil region of southern China.Aggregate stability and soil shear str...In response to the effectiveness of reforestation in controlling soil erosion,there has been a dramatic increase in forest coverage in the hilly red soil region of southern China.Aggregate stability and soil shear strength are indicators that reflect soil resistance to erosion and its ability to prevent shallow landslides,respectively.However,limited research has focused on the response of soil aggregate stability and shear strength to reforestation.We selected three types of reforestations(Phyllostachys edulis forest,Cunninghamia lanceolata(Lamb.)Hook.forest,Citrus sinensis(L.)Osbeck.orchard),a natural forest(mixed coniferous and broadleaf forests),and a fallow land as study plots,and measured root traits,and soil physicochemical traits,i.e.,pH,soil organic matter(SOC),Soil water content(SWC),soil bulk density(BD),soil cohesion(c),soil internal friction angle(φ)and analyzed their multiple interactions.The soil aggregate stability traits,refer to the mean weight diameter(MWD)and geometric mean diameter(GMD),exhibited a significant increase in reforested plots,approximately 200%compared to fallow land and 50%compared to natural forests.For soil shear strength the values were approximately 20%higher than in fallow land and approximately 10%lower than in natural forests.Soil aggregate stability and soil shear strength did not exhibit a significant positive correlation across all plots,and the underlying drivers of these traits were variable.For instance,in natural forest and timber stands,soil aggregate stability was mainly influenced by soil organic carbon,while soil shear strength was primarily affected by root length density.In economic forest,aggregate stability and shear strength are mainly affected by organic carbon.Overall,we found that vegetation restoration enhances soil erosion resistance,however,the primary drivers for the improvement of aggregate stability(soil organic carbon)and shear strength(root length density)are different.Therefore,in future benefit assessments of vegetation restoration projects aimed at soil erosion control,different indicators should be considered based on specific conditions.展开更多
Oxalate content in spinach is a key trait of interest due to its relevance to human health.Understanding the genetic basis of it can facilitate the development of spinach varieties with reduced oxalate levels.In pursu...Oxalate content in spinach is a key trait of interest due to its relevance to human health.Understanding the genetic basis of it can facilitate the development of spinach varieties with reduced oxalate levels.In pursuit of understanding the genetic determinants,a diverse panel comprising 288 spinach accessions underwent thorough phenotyping of oxalate content and were subjected to whole-genome resequencing,resulting in a comprehensive dataset encompassing 14386 single-nucleotide polymorphisms(SNPs).Leveraging this dataset,we conducted a genome-wide association study(GWAS)to identify noteworthy SNPs associated with oxalate content.Furthermore,we employed genomic prediction(GP)via cross-prediction,utilizing five GP models,to assess genomic estimated breeding values(GEBVs)for oxalate content.The observed normal distribution and the wide range of oxalate content,exceeding 600.0 mg$100 g^(-1),underscore the complex and quantitative nature of this trait,likely influenced by multiple genes.Additionally,our analysis revealed distinct stratification,delineating the population into four discernible subpopulations.Furthermore,GWAS analysis employing five models in GAPIT 3 and TASSEL 5 unveiled nine significant SNPs(four SNPs on chromosome 1 and five on chromosome 5)associated with oxalate content.These loci exhibited associations with six candidate genes,which might have potential contribution to oxalate content regulation.Remarkably,our GP models exhibited notable predictive abilities,yielding average accuracies of up to 0.51 for GEBV estimation.The integration of GWAS and GP approaches offers a holistic comprehension of the genetic underpinnings of oxalate content in spinach.These findings offered a promising avenue for the development of spinach cultivars and hybrids optimized for oxalate levels,promoting consumer health.展开更多
Crop leaf area index(LAI)and biomass are two major biophysical parameters to measure crop growth and health condition.Measuring LAI and biomass in field experiments is a destructive method.Therefore,we focused on the ...Crop leaf area index(LAI)and biomass are two major biophysical parameters to measure crop growth and health condition.Measuring LAI and biomass in field experiments is a destructive method.Therefore,we focused on the application of unmanned aerial vehicles(UAVs)in agriculture,which is a cost and labor-efficientmethod.Hence,UAV-captured multispectral images were applied to monitor crop growth,identify plant bio-physical conditions,and so on.In this study,we monitored soybean crops using UAV and field experiments.This experiment was conducted at theMAFES(Mississippi Agricultural and Forestry Experiment Station)Pontotoc Ridge-Flatwoods Branch Experiment Station.It followed a randomized block design with five cover crops:Cereal Rye,Vetch,Wheat,MC:mixed Mustard and Cereal Rye,and native vegetation.Planting was made in the fall,and three fertilizer treatments were applied:Synthetic Fertilizer,Poultry Litter,and none,applied before planting the soybean,in a full factorial combination.We monitored soybean reproductive phases at R3(initial pod development),R5(initial seed development),R6(full seed development),and R7(initial maturity)and used UAV multispectral remote sensing for soybean LAI and biomass estimations.The major goal of this study was to assess LAI and biomass estimations from UAV multispectral images in the reproductive stages when the development of leaves and biomass was stabilized.Wemade about fourteen vegetation indices(VIs)fromUAVmultispectral images at these stages to estimate LAI and biomass.Wemodeled LAI and biomass based on these remotely sensed VIs and ground-truth measurements usingmachine learning methods,including linear regression,Random Forest(RF),and support vector regression(SVR).Thereafter,the models were applied to estimate LAI and biomass.According to the model results,LAI was better estimated at the R6 stage and biomass at the R3 stage.Compared to the other models,the RF models showed better estimation,i.e.,an R^(2) of about 0.58–0.68 with an RMSE(rootmean square error)of 0.52–0.60(m^(2)/m^(2))for the LAI and about 0.44–0.64 for R^(2) and 21–26(g dry weight/5 plants)for RMSE of biomass estimation.We performed a leave-one-out cross-validation.Based on cross-validatedmodels with field experiments,we also found that the R6 stage was the best for estimating LAI,and the R3 stage for estimating crop biomass.The cross-validated RF model showed the estimation ability with an R^(2) about 0.25–0.44 and RMSE of 0.65–0.85(m^(2)/m^(2))for LAI estimation;and R^(2) about 0.1–0.31 and an RMSE of about 28–35(g dry weight/5 plants)for crop biomass estimation.This result will be helpful to promote the use of non-destructive remote sensing methods to determine the crop LAI and biomass status,which may bring more efficient crop production and management.展开更多
Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explici...Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explicitly conducted on the Texas Marker^(-1)(TM1)variety,potentially making its functional equations more aligned with this cultivar.To assess the model’s broader applicability,this study analyzed fiber quality data from 40 upland cotton cultivars,including TM1.The measured fiber quality from all cultivars was then compared with the modelsimulated fiber quality.Results Among the 40 upland cultivars,fiber strength varied from 28.4 cN·tex^(-1) to 34.6 cN·tex^(-1),fiber length ranged from 27.1 mm to 33.3 mm,micronaire value ranged from 2.7 to 4.6,and length uniformity index varied from 82.3%to 85.5%.The model simulated fiber quality closely matched the measured values for TM1,with the absolute percentage error(APE)being less than 0.92%for fiber strength,fiber length,and length uniformity index and 4.7%for micronaire.However,significant differences were observed for the other cultivars.The Pearson correlation coefficient(r)between the measured and simulated values was negative for all fiber quality traits,and Wilmotts’s index of agreement(WIA)was below 0.45,indicating a strong model bias toward TM1 without incorporating cultivar-specific parameters.After incorporating cultivar-specific parameters,the model’s performance improved significantly,with an average r-value of 0.84 and WIA of 0.88.Conclusions The adopted methodology and estimated cultivar-specific parameters improved the model’s simulation accuracy.This approach can be applied to newer cotton cultivars,enhancing the GOSSYM model’s utility and its applicability for agricultural management and policy decisions.展开更多
Sugarcane is recognized as the fifth largest crop globally,supplying 80%of sugar and 40%of bioenergy production.However,sugarcane genetic research has significantly lagged behind other crops due to its complex genetic...Sugarcane is recognized as the fifth largest crop globally,supplying 80%of sugar and 40%of bioenergy production.However,sugarcane genetic research has significantly lagged behind other crops due to its complex genetic background,high ploidy(8-13×),aneuploidy,limited flowering,and a long growth cycle(more than one year).Cross breeding began in 1887 following the discovery that sugarcane seeds could germinate.Both self-and cross-pollination and selection were conducted by sugarcane breeders,but new cultivars were often eliminated due to disease susceptibility.Within the Saccharum genus,different species possess variable numbers of chromosomes.Wild sugarcane species intercrossed with each other,leading to development of the‘Nobilization’breeding strategy,which significantly improved yield,sucrose,fiber content,and disease resistance,and accelerated genetic improvement of cultivars.In recent years,scientific achievements have also been made in sugarcane genome sequencing,molecular marker development,genetic linkage map construction,localization of quantitative trait locus(QTL),and trait-associated gene identification.This review focuses on the progress in sugarcane genetic research,analyzes the technical difficulties faced,presents opportunities and challenges,and provides guidance and references for future sugarcane genetics research and cultivar breeding.Finally,it offers directions for future on sugarcane genetics.展开更多
Non-destructive time-series assessment of chlorophyll content in flag-leaf(FLC)accurately mimics the senescence rate and the identification of genetic loci associated with senescence provides valuable knowledge to imp...Non-destructive time-series assessment of chlorophyll content in flag-leaf(FLC)accurately mimics the senescence rate and the identification of genetic loci associated with senescence provides valuable knowledge to improve yield stability under stressed environments.In this study,we employed both unmanned aerial vehicles(UAVs)equipped with red–green–blue(RGB)camera and ground-based SPAD-502 instrument to conduct temporal phenotyping of senescence.A total of 262 recombinant inbred lines derived from the cross of Zhongmai 578/Jimai 22 were evaluated for senescence-related traits across three environments,spanning from heading to 35 d post-anthesis.The manual senescence rate(MSR)was quantified using the FLC and the active accumulated temperature,and UAV derived vegetation index were utilized to assess the stay-green rate(USG)facilitating the identification of senescent and stay-green lines.Results indicated that higher senescence rates significantly impacted grain yield,primarily by influencing thousand-kernel weight,and plant height.Quantitative trait loci(QTL)mapping for FLC,USG,and MSR using the 50K SNP array identified 38 stable loci associated with RGB-based vegetation indices and senescence-related traits:among which 19 loci related to senescence traits from UAV and FLC were consistently detected across at least two growth stages,with nine loci likely representing novel QTL.This study highlights the potential of UAV-based high-throughput phenotyping and phenology in identifying critical loci associated with senescence rates in wheat,validating the relationship between senescence rates and yield-related traits in wheat,offering valuable opportunities for gene discovery and significant applications in breeding programs.展开更多
Although big data is publicly available on water quality parameters,virtual simulation has not yet been adequately adapted in environmental chemistry research.Digital twin is different from conventional geospatial mod...Although big data is publicly available on water quality parameters,virtual simulation has not yet been adequately adapted in environmental chemistry research.Digital twin is different from conventional geospatial modeling approaches and is particularly useful when systematic laboratory/field experiment is not realistic(e.g.,climate impact and water-related environmental catastrophe)or difficult to design and monitor in a real time(e.g.,pollutant and nutrient cycles in estuaries,soils,and sediments).Data-driven water research could realize early warning and disaster readiness simulations for diverse environmental scenarios,including drinking water contamination.展开更多
The original online version of this article (Ghozlan, M.H., EL-Argawy, E., Tokgöz, S., Lakshman, D.K. and Mitra, A. (2020) Plant Defense against Necrotrophic Pathogens. American Journal of Plant Sciences, 11, 212...The original online version of this article (Ghozlan, M.H., EL-Argawy, E., Tokgöz, S., Lakshman, D.K. and Mitra, A. (2020) Plant Defense against Necrotrophic Pathogens. American Journal of Plant Sciences, 11, 2122-2138. https://doi.org/10.4236/ajps.2020.1112149) was published mistakenly without another co-author, Nikita Gambhir. In this regard, we revise authors and “how to cite” sections by adding her name.展开更多
California is one of the major alfalfa (Medicago sativa L) forage-producing states in the U.S, but its production area has decreased significantly in the last couple of decades. Selection of cultivars with high yield ...California is one of the major alfalfa (Medicago sativa L) forage-producing states in the U.S, but its production area has decreased significantly in the last couple of decades. Selection of cultivars with high yield and nutritive value under late-cutting schedule strategy may help identify cultivars that growers can use to maximize yield while maintaining area for sustainable alfalfa production, but there is little information on this strategy. A field study was conducted to determine cumulative dry matter (DM) and nutritive values of 20 semi- and non-fall dormant (FD) ratings (FD 7 and FD 8 - 10, respectively) cultivars under 35-day cut in California’s Central Valley in 2020-2022. Seasonal cumulative DM yields ranged from 6.8 in 2020 to 37.0 Mg·ha−1 in 2021. Four FD 8 - 9 cultivars were the highest yielding with 3-yrs avg. DM greater than the lowest yielding lines by 46%. FD 7 cultivar “715RR” produced the highest crude protein (CP: 240 g·Kg−1) while FD 8 cultivar “HVX840RR” resulted in the highest neutral detergent fiber digestibility (NDFD: 484 g·Kg−1, 7% greater than the top yielding cultivars) but with DM yield intermediate. Yields and NDFD correlated positively but weakly indicating some semi- and non-FD cultivars performing similarly. These results suggest that selecting high yielding cultivars under 35-day cutting schedule strategy can be used as a tool to help growers to maximize yield while achieving good quality forages for sustainable alfalfa production in California’s Central Valley.展开更多
Pretreated wheat insoluble arabinoxylan was converted to oligosaccharides of structural variants using combinatorial enzyme approach. The digestive products were separated by preparative scale chromatographic Amberlit...Pretreated wheat insoluble arabinoxylan was converted to oligosaccharides of structural variants using combinatorial enzyme approach. The digestive products were separated by preparative scale chromatographic Amberlite XAD-2 column. Fractions containing feruloyl oligosaccharides (FOS) were isolated, pooled, freeze-dried, and demonstrated to possess antimicrobial activity. The FOS suppressed cell growth of the test organism ATCC 8739 E. coli with a MIC value of 0.028% (w/v, 35˚C, 24 hr). The antimicrobial action was observed exceeding 72 hr of culture incubation. The FOS product could be a useful source of prebiotics or preservatives. The present results further confirm the science and application of the concept of combinatorial enzyme technique.展开更多
In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance...In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance was compared in the spring following autumn establishment as for age cover crops after soybean [Glycine max (L.) Merr.] grain harvest. Replicated pastures (0.4 ha) were no-till seeded in three consecutive years into soybean stubble in autumn, fertilized, and grazed the following spring near Ithaca, NE, USA. Each pasture (n = 3) was continuously stocked in spring with four yearling steers (380 ± 38 kg) for 17, 32, and 28 d in 2005, 2006, and 2007, respectively. In 2005, average daily gain (ADG) for steers grazing triticale exceeded the ADG for wheat by 0.31 kghd<sup>-1</sup>d<sup>-1</sup>. In 2006, wheat ADG exceeded that for triticale by 0.12 kghd<sup>-1</sup>d<sup>-1</sup>. In 2007, steers grazing wheat lost weight, while steers grazing triticale gained 0.20 kghd<sup>-1</sup>d<sup>-1</sup>. Based on the 3-year average animal gains valued at $1.32 kg<sup>-1</sup>, mean net return ($ ha<sup>-1</sup> yr<sup>-1</sup>) was $62.15 for triticale and $22.55 for wheat. Since these grazed cover crops provide ecosystem services in addition to forage, grazing could be viewed as a mechanism for recovering costs and adds additional value to the system. Based on this 3-year grazing trial, triticale was superior to wheat and likely will provide the most stable beef yearling performance across years with variable weather for the western Cornbelt USA.展开更多
We are evaluating dryland cotton production in Martin County, Texas, measuring cotton lint yield per unit of rainfall. Our goal is to collect rainfall data per 250 - 400 ha. Upon selection of a rainfall gauge, we real...We are evaluating dryland cotton production in Martin County, Texas, measuring cotton lint yield per unit of rainfall. Our goal is to collect rainfall data per 250 - 400 ha. Upon selection of a rainfall gauge, we realized that the cost of using, for example, a tipping bucket-type rain gauge would be too expensive and thus searched for an alternative method. We selected an all-in-one commercially available weather station;hereafter, referred to as a Personal Weather Station (PWS) that is both wireless and solar powered. Our objective was to evaluate average measurements of rainfall obtained with the PWS and to compare these to measurements obtained with an automatic weather station (AWS). For this purpose, we installed four PWS deployed within 20 m of the Plant Stress and Water Conservation Meteorological Tower that was used as our AWS, located at USDA-ARS Cropping Systems Research Laboratory, Lubbock, TX. In addition, we measured and compared hourly average values of short-wave irradiance (R<sub>g</sub>), air temperature (T<sub>air</sub>) and relative humidity (RH), and wind speed (WS), and calculated values of dewpoint temperature (T<sub>dew</sub>). This comparison was done over a 242-day period (1 October 2022-31 May 2023) and results indicated that there was no statistical difference in measurements of rainfall between the PWS and AWS. Hourly average values of R<sub>g</sub> measured with the PWS and AWS agreed on clear days, but PWS measurements were higher on cloudy days. There was no statistical difference between PWS and AWS hourly average measurements of T<sub>air</sub>, RH, and calculated T<sub>dew</sub>. Hourly average measurements of R<sub>g</sub> and WS were more variable. We concluded that the PWS we selected will provide adequate values of rainfall and other weather variables to meet our goal of evaluating dryland cotton lint yield per unit rainfall.展开更多
Spatial variation is often encountered when large scale field trials are conducted which can result in biased estimation or prediction of treatment (i.e. genotype) values. An effective removal of spatial variation is ...Spatial variation is often encountered when large scale field trials are conducted which can result in biased estimation or prediction of treatment (i.e. genotype) values. An effective removal of spatial variation is needed to ensure unbiased estimation or prediction and thus increase the accuracy of field data evaluation. A moving grid adjustment (MGA) method, which was proposed by Technow, was evaluated through Monte Carlo simulation for its statistical properties regarding field spatial variation control. Our simulation results showed that the MGA method can effectively account for field spatial variation if it does exist;however, this method will not change phenotype results if field spatial variation does not exist. The MGA method was applied to a large-scale cotton field trial data set with two representative agronomic traits: lint yield (strong field spatial pattern) and lint percentage (no field spatial pattern). The results suggested that the MGA method was able to effectively separate the spatial variation including blocking effects from random error variation for lint yield while the adjusted data remained almost identical to the original phenotypic data. With application of the MGA method, the estimated variance for residuals was significantly reduced (62.2% decrease) for lint yield while more genetic variation (29.7% increase) was detected compared to the original data analysis subject to the conventional randomized complete block design analysis. On the other hand, the results were almost identical for lint percentage with and without the application of the MGA method. Therefore, the MGA method can be a useful addition to enhance data analysis when field spatial pattern exists.展开更多
Morphological(e.g.shape,size,and height)and function(e.g.working,living,and shopping)information of buildings is highly needed for urban planning and management as well as other applications such as city-scale buildin...Morphological(e.g.shape,size,and height)and function(e.g.working,living,and shopping)information of buildings is highly needed for urban planning and management as well as other applications such as city-scale building energy use modeling.Due to the limited availability of socio-economic geospatial data,it is more challenging to map building functions than building morphological information,especially over large areas.In this study,we proposed an integrated framework to map building functions in 50 U.S.cities by integrating multi-source web-based geospatial data.First,a web crawler was developed to extract Points of Interest(POIs)from Tripadvisor.com,and a map crawler was developed to extract POIs and land use parcels from Google Maps.Second,an unsupervised machine learning algorithm named OneClassSVM was used to identify residential buildings based on landscape features derived from Microsoft building footprints.Third,the type ratio of POIs and the area ratio of land use parcels were used to identify six non-residential functions(i.e.hospital,hotel,school,shop,restaurant,and office).The accuracy assessment indicates that the proposed framework performed well,with an average overall accuracy of 94%and a kappa coefficient of 0.63.With the worldwide coverage of Google Maps and Tripadvisor.com,the proposed framework is transferable to other cities over the world.The data products generated from this study are of great use for quantitative city-scale urban studies,such as building energy use modeling at the single building level over large areas.展开更多
Needle chlorosis(NC)in Pinus taeda L.systems in Brazil becomes more frequent after second and third harvest rotation cycles.In a study to identify factors contributing to yellowing needle chorosis(YNC),trees were grow...Needle chlorosis(NC)in Pinus taeda L.systems in Brazil becomes more frequent after second and third harvest rotation cycles.In a study to identify factors contributing to yellowing needle chorosis(YNC),trees were grown in soils originating from contrasting parent materials,and soils and needles(whole,green and chlorotic portions)from 1-and 2-year-old branches and the first and second needle flush release at four sites with YNC on P.taeda were analyzed for various elements and properties.All soils had very low base levels(Ca^(2+),Mg^(2+)and K^(+))and P,suggesting a possible lack of multiple elements.YNC symptoms started at needle tips,then extended toward the needle base with time.First flush needles had longer portions with YNC than second flush needles did.Needles from the lower crown also had more symptoms along their length than those higher in the canopy.Symptoms were similar to those reported for Mg.In chlorotic portions,Mg and Ca concentrations were well below critical values;in particular,Mg levels were only one third of the critical value of 0.3 g kg^(-1).Collectively,results suggest that Mg deficiency is the primary reason for NC of P.taeda in various parent soils in Brazil.展开更多
文摘Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.
基金the financial support from FORMAS(2018-01029)the Swedish Institute(01132-2022)for supporting Ivan Motsnyi’s visit and research at Swedish University of Agricultural Sciences。
文摘Emerging new races of wheat stem rust(Puccinia graminis f.sp.tritici)are threatening global wheat(Triticum aestivum L.)production.Host resistance is the most effective and environmentally friendly method of controlling stem rust.The stem rust resistance gene Sr59 was previously identified within a T2DS 2RL wheat-rye whole arm translocation,providing broad-spectrum resistance to various stem rust races.Seedling evaluation,molecular marker analysis,and cytogenetic studies identified wheat-rye introgression line#284 containing a new translocation chromosome T2BL 2BS-2RL.This line has demonstrated broad-spectrum resistance to stem rust at the seedling stage.Seedling evaluation and cytogenetic analysis of three backcross populations between the line#284 and the adapted cultivars SLU-Elite,Navruz,and Linkert confirmed that Sr59 is located within the short distal 2RL translocation.This study aimed physical mapping of Sr59 in the 2RL introgression segment and develop a robust molecular marker for marker-assisted selection.Using genotyping-by-sequencing(GBS),GBS-derived SNPs were aligned with full-length annotated rye nucleotide-binding leucine-rich repeat(NLR)genes in the parental lines CS ph1b,SLU238,SLU-Elite,Navruz,and Linkert,as well as in 33 BC4F5progeny.Four NLR genes were identified on the 2R chromosome,with Chr2R_NLR_60 being tightly linked to the Sr59resistance gene.In-silico functional enrichment analysis of the translocated 2RL region(25,681,915 bp)identified 223 genes,with seven candidate genes associated with plant disease resistance and three linked to agronomic performance,contributing to oxidative stress response,protein kinase activity,and cellular homeostasis.These findings facilitate a better understanding of the genetic basis of stem rust resistance provided by Sr59.
文摘Ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR MS)is an advanced instrument capable of separating and determining molecular mass-to-charge ratios with sub-ppm level accuracy.A typical FT-ICR MS spectrogram can identify hundreds to thousands of formulas in a complex sample.This perspective briefly examines the application of FT-ICR MS to soil organic matter and plant biomass studies,highlighting their significant contributions to sustainable agriculture and environment.
基金funded through an appointment with the Agricultural Research Service,managed by the Oak Ridge Institute for Science and Education。
文摘Remote sensing technologies play a vital role in our understanding of earthquakes and their impact on the Earth's surface.These technologies,including satellite imagery,aerial surveys,and advanced sensors,contribute significantly to our understanding of the complex nature of earthquakes.This review highlights the advancements in the integration of remote sensing technologies into earthquake studies.The combined use of satellite imagery and aerial photography in conjunction with geographic information systems(GIS)has been instrumental in showcasing the significance of fusing various types of satеllitеdata sourcеs for comprеhеnsivееarthquakеdamagеassеssmеnts.However,remote sensing encounters challenges due to limited pre-event imagery and restricted postearthquake site access.Furthеrmorе,thеapplication of dееp-lеarning mеthods in assеssingеarthquakе-damagеd buildings dеmonstratеs potеntial for furthеr progrеss in this fiеld.Overall,the utilization of remote sensing technologies has greatly enhanced our comprehension of earthquakes and their effects on the Earth's surface.The fusion of remote sensing technology with advanced data analysis methods holds tremendous potential for driving progress in earthquake studies and damage assessment.
基金the project “Genomics for Conservation of Indigenous Cattle Breeds and for Enhancing Milk Yield, Phase-I” [BT/ PR26466/AAQ/1/704/2017], funded by the Department of Biotechnology (DBT ), Indiathe project “Identification of key molecular factors involved in resistance/susceptibility to paratuberculosis infection in indigenous breeds of cows” [BT/PR32758/AAQ/1/760/2019], which was also funded by Department of Biotechnology (DBT ), India。
文摘Background India harbors the world’s largest cattle population,encompassing over 50 distinct Bos indicus breeds.This rich genetic diversity underscores the inadequacy of a single reference genome to fully capture the genomic landscape of Indian cattle.To comprehensively characterize the genomic variation within Bos indicus and,specifically,dairy breeds,we aim to identify non-reference sequences and construct a comprehensive pangenome.Results Five representative genomes of prominent dairy breeds,including Gir,Kankrej,Tharparkar,Sahiwal,and Red Sindhi,were sequenced using 10X Genomics‘linked-read’technology.Assemblies generated from these linked-reads ranged from 2.70 Gb to 2.77 Gb,comparable to the Bos indicus Brahman reference genome.A pangenome of Bos indicus cattle was constructed by comparing the newly assembled genomes with the reference using alignment and graph-based methods,revealing 8 Mb and 17.7 Mb of novel sequence respectively.A confident set of 6,844 Non-reference Unique Insertions(NUIs)spanning 7.57 Mb was identified through both methods,representing the pange-nome of Indian Bos indicus breeds.Comparative analysis with previously published pangenomes unveiled 2.8 Mb(37%)commonality with the Chinese indicine pangenome and only 1%commonality with the Bos taurus pange-nome.Among these,2,312 NUIs encompassing~2 Mb,were commonly found in 98 samples of the 5 breeds and des-ignated as Bos indicus Common Insertions(BICIs)in the population.Furthermore,926 BICIs were identified within 682 protein-coding genes,54 long non-coding RNAs(lncRNA),and 18 pseudogenes.These protein-coding genes were enriched for functions such as chemical synaptic transmission,cell junction organization,cell-cell adhesion,and cell morphogenesis.The protein-coding genes were found in various prominent quantitative trait locus(QTL)regions,suggesting potential roles of BICIs in traits related to milk production,reproduction,exterior,health,meat,and carcass.Notably,63.21%of the bases within the BICIs call set contained interspersed repeats,predominantly Long Inter-spersed Nuclear Elements(LINEs).Additionally,70.28%of BICIs are shared with other domesticated and wild species,highlighting their evolutionary significance.Conclusions This is the first report unveiling a robust set of NUIs defining the pangenome of Bos indicus breeds of India.The analyses contribute valuable insights into the genomic landscape of desi cattle breeds.
基金supported by the National Natural Science Foundation of China(NO.32201626)the Key Research and Development Program of Jiangxi Province(20223BBG74S01,20223BBG71013).
文摘In response to the effectiveness of reforestation in controlling soil erosion,there has been a dramatic increase in forest coverage in the hilly red soil region of southern China.Aggregate stability and soil shear strength are indicators that reflect soil resistance to erosion and its ability to prevent shallow landslides,respectively.However,limited research has focused on the response of soil aggregate stability and shear strength to reforestation.We selected three types of reforestations(Phyllostachys edulis forest,Cunninghamia lanceolata(Lamb.)Hook.forest,Citrus sinensis(L.)Osbeck.orchard),a natural forest(mixed coniferous and broadleaf forests),and a fallow land as study plots,and measured root traits,and soil physicochemical traits,i.e.,pH,soil organic matter(SOC),Soil water content(SWC),soil bulk density(BD),soil cohesion(c),soil internal friction angle(φ)and analyzed their multiple interactions.The soil aggregate stability traits,refer to the mean weight diameter(MWD)and geometric mean diameter(GMD),exhibited a significant increase in reforested plots,approximately 200%compared to fallow land and 50%compared to natural forests.For soil shear strength the values were approximately 20%higher than in fallow land and approximately 10%lower than in natural forests.Soil aggregate stability and soil shear strength did not exhibit a significant positive correlation across all plots,and the underlying drivers of these traits were variable.For instance,in natural forest and timber stands,soil aggregate stability was mainly influenced by soil organic carbon,while soil shear strength was primarily affected by root length density.In economic forest,aggregate stability and shear strength are mainly affected by organic carbon.Overall,we found that vegetation restoration enhances soil erosion resistance,however,the primary drivers for the improvement of aggregate stability(soil organic carbon)and shear strength(root length density)are different.Therefore,in future benefit assessments of vegetation restoration projects aimed at soil erosion control,different indicators should be considered based on specific conditions.
基金supported by USDA-SCRI(Grant Nos.2017-51181-26830 and 2023-51181-41321)USDA-AMS SCMP(Grant No.16SCCMAR0001)+1 种基金Arkansas Department of Agriculture SCBGP(Grant No.AM22SCBGPAR1130-00)USDA NIFA Hatch project(Grant Nos.ARK0VG2018 and ARK02440).
文摘Oxalate content in spinach is a key trait of interest due to its relevance to human health.Understanding the genetic basis of it can facilitate the development of spinach varieties with reduced oxalate levels.In pursuit of understanding the genetic determinants,a diverse panel comprising 288 spinach accessions underwent thorough phenotyping of oxalate content and were subjected to whole-genome resequencing,resulting in a comprehensive dataset encompassing 14386 single-nucleotide polymorphisms(SNPs).Leveraging this dataset,we conducted a genome-wide association study(GWAS)to identify noteworthy SNPs associated with oxalate content.Furthermore,we employed genomic prediction(GP)via cross-prediction,utilizing five GP models,to assess genomic estimated breeding values(GEBVs)for oxalate content.The observed normal distribution and the wide range of oxalate content,exceeding 600.0 mg$100 g^(-1),underscore the complex and quantitative nature of this trait,likely influenced by multiple genes.Additionally,our analysis revealed distinct stratification,delineating the population into four discernible subpopulations.Furthermore,GWAS analysis employing five models in GAPIT 3 and TASSEL 5 unveiled nine significant SNPs(four SNPs on chromosome 1 and five on chromosome 5)associated with oxalate content.These loci exhibited associations with six candidate genes,which might have potential contribution to oxalate content regulation.Remarkably,our GP models exhibited notable predictive abilities,yielding average accuracies of up to 0.51 for GEBV estimation.The integration of GWAS and GP approaches offers a holistic comprehension of the genetic underpinnings of oxalate content in spinach.These findings offered a promising avenue for the development of spinach cultivars and hybrids optimized for oxalate levels,promoting consumer health.
基金This research was supported in part by a postdoctoral research fellow appointment to the Agricultural Research Service(ARS)Research Participation Program administered by the Oak Ridge Institute for Science and Education(ORISE)through an interagency agreement between the U.S.Department of Energy(DOE)and the U.S.Department of Agriculture(USDA).
文摘Crop leaf area index(LAI)and biomass are two major biophysical parameters to measure crop growth and health condition.Measuring LAI and biomass in field experiments is a destructive method.Therefore,we focused on the application of unmanned aerial vehicles(UAVs)in agriculture,which is a cost and labor-efficientmethod.Hence,UAV-captured multispectral images were applied to monitor crop growth,identify plant bio-physical conditions,and so on.In this study,we monitored soybean crops using UAV and field experiments.This experiment was conducted at theMAFES(Mississippi Agricultural and Forestry Experiment Station)Pontotoc Ridge-Flatwoods Branch Experiment Station.It followed a randomized block design with five cover crops:Cereal Rye,Vetch,Wheat,MC:mixed Mustard and Cereal Rye,and native vegetation.Planting was made in the fall,and three fertilizer treatments were applied:Synthetic Fertilizer,Poultry Litter,and none,applied before planting the soybean,in a full factorial combination.We monitored soybean reproductive phases at R3(initial pod development),R5(initial seed development),R6(full seed development),and R7(initial maturity)and used UAV multispectral remote sensing for soybean LAI and biomass estimations.The major goal of this study was to assess LAI and biomass estimations from UAV multispectral images in the reproductive stages when the development of leaves and biomass was stabilized.Wemade about fourteen vegetation indices(VIs)fromUAVmultispectral images at these stages to estimate LAI and biomass.Wemodeled LAI and biomass based on these remotely sensed VIs and ground-truth measurements usingmachine learning methods,including linear regression,Random Forest(RF),and support vector regression(SVR).Thereafter,the models were applied to estimate LAI and biomass.According to the model results,LAI was better estimated at the R6 stage and biomass at the R3 stage.Compared to the other models,the RF models showed better estimation,i.e.,an R^(2) of about 0.58–0.68 with an RMSE(rootmean square error)of 0.52–0.60(m^(2)/m^(2))for the LAI and about 0.44–0.64 for R^(2) and 21–26(g dry weight/5 plants)for RMSE of biomass estimation.We performed a leave-one-out cross-validation.Based on cross-validatedmodels with field experiments,we also found that the R6 stage was the best for estimating LAI,and the R3 stage for estimating crop biomass.The cross-validated RF model showed the estimation ability with an R^(2) about 0.25–0.44 and RMSE of 0.65–0.85(m^(2)/m^(2))for LAI estimation;and R^(2) about 0.1–0.31 and an RMSE of about 28–35(g dry weight/5 plants)for crop biomass estimation.This result will be helpful to promote the use of non-destructive remote sensing methods to determine the crop LAI and biomass status,which may bring more efficient crop production and management.
基金supported by United States Department of Agriculture,Agricultural Research Service(No.58-8042-9-072)United States Department of Agriculture-National Institute of Food and Agriculture(No.2019-34263-30552)+1 种基金Management Information System(No.043050)United States Department of Agriculture-Agricultural Research Service-Non-Assistance Cooperative Agreement(No.58-6066-2-030).
文摘Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explicitly conducted on the Texas Marker^(-1)(TM1)variety,potentially making its functional equations more aligned with this cultivar.To assess the model’s broader applicability,this study analyzed fiber quality data from 40 upland cotton cultivars,including TM1.The measured fiber quality from all cultivars was then compared with the modelsimulated fiber quality.Results Among the 40 upland cultivars,fiber strength varied from 28.4 cN·tex^(-1) to 34.6 cN·tex^(-1),fiber length ranged from 27.1 mm to 33.3 mm,micronaire value ranged from 2.7 to 4.6,and length uniformity index varied from 82.3%to 85.5%.The model simulated fiber quality closely matched the measured values for TM1,with the absolute percentage error(APE)being less than 0.92%for fiber strength,fiber length,and length uniformity index and 4.7%for micronaire.However,significant differences were observed for the other cultivars.The Pearson correlation coefficient(r)between the measured and simulated values was negative for all fiber quality traits,and Wilmotts’s index of agreement(WIA)was below 0.45,indicating a strong model bias toward TM1 without incorporating cultivar-specific parameters.After incorporating cultivar-specific parameters,the model’s performance improved significantly,with an average r-value of 0.84 and WIA of 0.88.Conclusions The adopted methodology and estimated cultivar-specific parameters improved the model’s simulation accuracy.This approach can be applied to newer cotton cultivars,enhancing the GOSSYM model’s utility and its applicability for agricultural management and policy decisions.
基金supported by the National Key Research and Development Program of China(2022YFD2301100)National Natural Science Foundation of China(32272156)+3 种基金Natural Science Foundation of Fujian Province,China(2022J01160)Central Publicinterest Scientific Institution Basal Research Fund(1630052024003,1630052024020)Chinese Academy of Tropical Agricultural Sciences for Science and Technology Innovation Team of National Tropical Agricultural Science Center(CATASCXTD202402)China Agriculture Research System of MOF and MARA(CARS-17).
文摘Sugarcane is recognized as the fifth largest crop globally,supplying 80%of sugar and 40%of bioenergy production.However,sugarcane genetic research has significantly lagged behind other crops due to its complex genetic background,high ploidy(8-13×),aneuploidy,limited flowering,and a long growth cycle(more than one year).Cross breeding began in 1887 following the discovery that sugarcane seeds could germinate.Both self-and cross-pollination and selection were conducted by sugarcane breeders,but new cultivars were often eliminated due to disease susceptibility.Within the Saccharum genus,different species possess variable numbers of chromosomes.Wild sugarcane species intercrossed with each other,leading to development of the‘Nobilization’breeding strategy,which significantly improved yield,sucrose,fiber content,and disease resistance,and accelerated genetic improvement of cultivars.In recent years,scientific achievements have also been made in sugarcane genome sequencing,molecular marker development,genetic linkage map construction,localization of quantitative trait locus(QTL),and trait-associated gene identification.This review focuses on the progress in sugarcane genetic research,analyzes the technical difficulties faced,presents opportunities and challenges,and provides guidance and references for future sugarcane genetics research and cultivar breeding.Finally,it offers directions for future on sugarcane genetics.
基金funded by the National Key Research and Development Program of China(2022ZD0115703)the National Natural Science Foundation of China(32372196)+1 种基金the Beijing Joint Research Program for Germplasm Innovation and New Variety Breeding(G20220628002)National Natural Science Foundation of China(32250410307)。
文摘Non-destructive time-series assessment of chlorophyll content in flag-leaf(FLC)accurately mimics the senescence rate and the identification of genetic loci associated with senescence provides valuable knowledge to improve yield stability under stressed environments.In this study,we employed both unmanned aerial vehicles(UAVs)equipped with red–green–blue(RGB)camera and ground-based SPAD-502 instrument to conduct temporal phenotyping of senescence.A total of 262 recombinant inbred lines derived from the cross of Zhongmai 578/Jimai 22 were evaluated for senescence-related traits across three environments,spanning from heading to 35 d post-anthesis.The manual senescence rate(MSR)was quantified using the FLC and the active accumulated temperature,and UAV derived vegetation index were utilized to assess the stay-green rate(USG)facilitating the identification of senescent and stay-green lines.Results indicated that higher senescence rates significantly impacted grain yield,primarily by influencing thousand-kernel weight,and plant height.Quantitative trait loci(QTL)mapping for FLC,USG,and MSR using the 50K SNP array identified 38 stable loci associated with RGB-based vegetation indices and senescence-related traits:among which 19 loci related to senescence traits from UAV and FLC were consistently detected across at least two growth stages,with nine loci likely representing novel QTL.This study highlights the potential of UAV-based high-throughput phenotyping and phenology in identifying critical loci associated with senescence rates in wheat,validating the relationship between senescence rates and yield-related traits in wheat,offering valuable opportunities for gene discovery and significant applications in breeding programs.
文摘Although big data is publicly available on water quality parameters,virtual simulation has not yet been adequately adapted in environmental chemistry research.Digital twin is different from conventional geospatial modeling approaches and is particularly useful when systematic laboratory/field experiment is not realistic(e.g.,climate impact and water-related environmental catastrophe)or difficult to design and monitor in a real time(e.g.,pollutant and nutrient cycles in estuaries,soils,and sediments).Data-driven water research could realize early warning and disaster readiness simulations for diverse environmental scenarios,including drinking water contamination.
文摘The original online version of this article (Ghozlan, M.H., EL-Argawy, E., Tokgöz, S., Lakshman, D.K. and Mitra, A. (2020) Plant Defense against Necrotrophic Pathogens. American Journal of Plant Sciences, 11, 2122-2138. https://doi.org/10.4236/ajps.2020.1112149) was published mistakenly without another co-author, Nikita Gambhir. In this regard, we revise authors and “how to cite” sections by adding her name.
文摘California is one of the major alfalfa (Medicago sativa L) forage-producing states in the U.S, but its production area has decreased significantly in the last couple of decades. Selection of cultivars with high yield and nutritive value under late-cutting schedule strategy may help identify cultivars that growers can use to maximize yield while maintaining area for sustainable alfalfa production, but there is little information on this strategy. A field study was conducted to determine cumulative dry matter (DM) and nutritive values of 20 semi- and non-fall dormant (FD) ratings (FD 7 and FD 8 - 10, respectively) cultivars under 35-day cut in California’s Central Valley in 2020-2022. Seasonal cumulative DM yields ranged from 6.8 in 2020 to 37.0 Mg·ha−1 in 2021. Four FD 8 - 9 cultivars were the highest yielding with 3-yrs avg. DM greater than the lowest yielding lines by 46%. FD 7 cultivar “715RR” produced the highest crude protein (CP: 240 g·Kg−1) while FD 8 cultivar “HVX840RR” resulted in the highest neutral detergent fiber digestibility (NDFD: 484 g·Kg−1, 7% greater than the top yielding cultivars) but with DM yield intermediate. Yields and NDFD correlated positively but weakly indicating some semi- and non-FD cultivars performing similarly. These results suggest that selecting high yielding cultivars under 35-day cutting schedule strategy can be used as a tool to help growers to maximize yield while achieving good quality forages for sustainable alfalfa production in California’s Central Valley.
文摘Pretreated wheat insoluble arabinoxylan was converted to oligosaccharides of structural variants using combinatorial enzyme approach. The digestive products were separated by preparative scale chromatographic Amberlite XAD-2 column. Fractions containing feruloyl oligosaccharides (FOS) were isolated, pooled, freeze-dried, and demonstrated to possess antimicrobial activity. The FOS suppressed cell growth of the test organism ATCC 8739 E. coli with a MIC value of 0.028% (w/v, 35˚C, 24 hr). The antimicrobial action was observed exceeding 72 hr of culture incubation. The FOS product could be a useful source of prebiotics or preservatives. The present results further confirm the science and application of the concept of combinatorial enzyme technique.
文摘In addition to their value as cereal grains, wheat (Triticum aestivum L.) and triticale (× Triticosecale Wittmack) are important cool-season annual forages and cover crops. Yearling steer (Bos taurus) performance was compared in the spring following autumn establishment as for age cover crops after soybean [Glycine max (L.) Merr.] grain harvest. Replicated pastures (0.4 ha) were no-till seeded in three consecutive years into soybean stubble in autumn, fertilized, and grazed the following spring near Ithaca, NE, USA. Each pasture (n = 3) was continuously stocked in spring with four yearling steers (380 ± 38 kg) for 17, 32, and 28 d in 2005, 2006, and 2007, respectively. In 2005, average daily gain (ADG) for steers grazing triticale exceeded the ADG for wheat by 0.31 kghd<sup>-1</sup>d<sup>-1</sup>. In 2006, wheat ADG exceeded that for triticale by 0.12 kghd<sup>-1</sup>d<sup>-1</sup>. In 2007, steers grazing wheat lost weight, while steers grazing triticale gained 0.20 kghd<sup>-1</sup>d<sup>-1</sup>. Based on the 3-year average animal gains valued at $1.32 kg<sup>-1</sup>, mean net return ($ ha<sup>-1</sup> yr<sup>-1</sup>) was $62.15 for triticale and $22.55 for wheat. Since these grazed cover crops provide ecosystem services in addition to forage, grazing could be viewed as a mechanism for recovering costs and adds additional value to the system. Based on this 3-year grazing trial, triticale was superior to wheat and likely will provide the most stable beef yearling performance across years with variable weather for the western Cornbelt USA.
文摘We are evaluating dryland cotton production in Martin County, Texas, measuring cotton lint yield per unit of rainfall. Our goal is to collect rainfall data per 250 - 400 ha. Upon selection of a rainfall gauge, we realized that the cost of using, for example, a tipping bucket-type rain gauge would be too expensive and thus searched for an alternative method. We selected an all-in-one commercially available weather station;hereafter, referred to as a Personal Weather Station (PWS) that is both wireless and solar powered. Our objective was to evaluate average measurements of rainfall obtained with the PWS and to compare these to measurements obtained with an automatic weather station (AWS). For this purpose, we installed four PWS deployed within 20 m of the Plant Stress and Water Conservation Meteorological Tower that was used as our AWS, located at USDA-ARS Cropping Systems Research Laboratory, Lubbock, TX. In addition, we measured and compared hourly average values of short-wave irradiance (R<sub>g</sub>), air temperature (T<sub>air</sub>) and relative humidity (RH), and wind speed (WS), and calculated values of dewpoint temperature (T<sub>dew</sub>). This comparison was done over a 242-day period (1 October 2022-31 May 2023) and results indicated that there was no statistical difference in measurements of rainfall between the PWS and AWS. Hourly average values of R<sub>g</sub> measured with the PWS and AWS agreed on clear days, but PWS measurements were higher on cloudy days. There was no statistical difference between PWS and AWS hourly average measurements of T<sub>air</sub>, RH, and calculated T<sub>dew</sub>. Hourly average measurements of R<sub>g</sub> and WS were more variable. We concluded that the PWS we selected will provide adequate values of rainfall and other weather variables to meet our goal of evaluating dryland cotton lint yield per unit rainfall.
文摘Spatial variation is often encountered when large scale field trials are conducted which can result in biased estimation or prediction of treatment (i.e. genotype) values. An effective removal of spatial variation is needed to ensure unbiased estimation or prediction and thus increase the accuracy of field data evaluation. A moving grid adjustment (MGA) method, which was proposed by Technow, was evaluated through Monte Carlo simulation for its statistical properties regarding field spatial variation control. Our simulation results showed that the MGA method can effectively account for field spatial variation if it does exist;however, this method will not change phenotype results if field spatial variation does not exist. The MGA method was applied to a large-scale cotton field trial data set with two representative agronomic traits: lint yield (strong field spatial pattern) and lint percentage (no field spatial pattern). The results suggested that the MGA method was able to effectively separate the spatial variation including blocking effects from random error variation for lint yield while the adjusted data remained almost identical to the original phenotypic data. With application of the MGA method, the estimated variance for residuals was significantly reduced (62.2% decrease) for lint yield while more genetic variation (29.7% increase) was detected compared to the original data analysis subject to the conventional randomized complete block design analysis. On the other hand, the results were almost identical for lint percentage with and without the application of the MGA method. Therefore, the MGA method can be a useful addition to enhance data analysis when field spatial pattern exists.
基金supported by the National Science Foundation[grant numbers 1854502 and 1855902]Publication was made possible in part by support from the HKU Libraries Open Access Author Fund sponsored by the HKU Libraries.USDA is an equal opportunity provider and employer.Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S.Department of Agriculture.
文摘Morphological(e.g.shape,size,and height)and function(e.g.working,living,and shopping)information of buildings is highly needed for urban planning and management as well as other applications such as city-scale building energy use modeling.Due to the limited availability of socio-economic geospatial data,it is more challenging to map building functions than building morphological information,especially over large areas.In this study,we proposed an integrated framework to map building functions in 50 U.S.cities by integrating multi-source web-based geospatial data.First,a web crawler was developed to extract Points of Interest(POIs)from Tripadvisor.com,and a map crawler was developed to extract POIs and land use parcels from Google Maps.Second,an unsupervised machine learning algorithm named OneClassSVM was used to identify residential buildings based on landscape features derived from Microsoft building footprints.Third,the type ratio of POIs and the area ratio of land use parcels were used to identify six non-residential functions(i.e.hospital,hotel,school,shop,restaurant,and office).The accuracy assessment indicates that the proposed framework performed well,with an average overall accuracy of 94%and a kappa coefficient of 0.63.With the worldwide coverage of Google Maps and Tripadvisor.com,the proposed framework is transferable to other cities over the world.The data products generated from this study are of great use for quantitative city-scale urban studies,such as building energy use modeling at the single building level over large areas.
基金the National council for scientific and technological development(CNPq)and Higher Education Personnel Improvement Coordination(CAPES)。
文摘Needle chlorosis(NC)in Pinus taeda L.systems in Brazil becomes more frequent after second and third harvest rotation cycles.In a study to identify factors contributing to yellowing needle chorosis(YNC),trees were grown in soils originating from contrasting parent materials,and soils and needles(whole,green and chlorotic portions)from 1-and 2-year-old branches and the first and second needle flush release at four sites with YNC on P.taeda were analyzed for various elements and properties.All soils had very low base levels(Ca^(2+),Mg^(2+)and K^(+))and P,suggesting a possible lack of multiple elements.YNC symptoms started at needle tips,then extended toward the needle base with time.First flush needles had longer portions with YNC than second flush needles did.Needles from the lower crown also had more symptoms along their length than those higher in the canopy.Symptoms were similar to those reported for Mg.In chlorotic portions,Mg and Ca concentrations were well below critical values;in particular,Mg levels were only one third of the critical value of 0.3 g kg^(-1).Collectively,results suggest that Mg deficiency is the primary reason for NC of P.taeda in various parent soils in Brazil.
