Near Infrared Spectroscopy (NIRS) Model-Based Prediction for Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R2 0.85) is better than the whole seed (0.33 R2 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R2_whole seed = 0.78, R2_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.

Impact on Soil Organic C and Total Soil N from Cool- and Warm-Season Legumes Used in a Green Manure-Forage Cropping System

Annual forage legumes are important components of livestock production systems in East Texas and the southeastern US. Forage legumes contribute nitrogen (N) to cropping systems through biological N fixation, and their seasonal biomass production can be managed to complement forage grasses. Our research objectives were to evaluate both warm- and cool-season annual forage legumes as green manure for biomass, N content, ability to enhance soil organic carbon (SOC) and soil N, and impact on post season forage grass crops. Nine warm-season forage legumes (WSL) were spring planted and incorporated as green manure in the fall. Forage rye (Secale cereale L.) was planted following the incorporation of WSL treatments. Eight cool-season forage legumes (CSL) were fall planted in previously fallow plots and incorporated as green manure in late spring. Sorghum-sudangrass (Sorghum bicolor x Sorghum bicolor var. sudanense) was planted over all treatments in early summer after forage rye harvest and incorporation of CSL treatments. Sorghum-sudangrass was harvested in June, August and September, and treatments were evaluated for dry matter and N concentration. Soil cores were taken from each plot, split into depths of 0 to 15, 15 to 30 and 30 to 60 cm, and soil C and N were measured using combustion analysis. Nylon mesh bags containing plant samples were buried at 15 cm and used to evaluate decomposition rate of above ground legume biomass, including change in C and N concentrations. Mungbean (Vigna radiata L. [Wilczek]) had the highest shoot biomass yield (6.24 t DM ha-1) and contributed the most total N (167 kg∙ha-1) and total C (3043 kg∙ha-1) of the WSL tested. Decomposition rate of WSL biomass was rapid in the first 10 weeks and very slow afterward. Winter pea (Pisum sativum L. spp. sativum), arrow leaf clover (Trifolium vesiculosum Savi.), and crimson clover (Trifolium incarnatum L.) were the most productive CSL in this trial. Austrian winter pea produced 8.41 t DM ha-1 with a total N yield of 319 kg N ha-1 and total C production of 3835 kg C ha-1. The WSL treatments had only small effects on rye forage yield and N concentration, possibly due to mineralization of N from a large SOC pool already in place. The CSL treatments also had only minimal effects on sorghum-sudangrass forage production. Winter pea, arrow leaf and crimson clover were productive cool season legumes and could be useful as green manure crops. Mungbean and cowpea (Vigna unguiculata [L.] Walp.) were highly productive warm season legumes but may include more production risk in green manure systems due to soil moisture competition.

Exceedance Probability of the Standardized Precipitation-Evapotranspiration Index in the Texas High Plains

Drought is a common occurrence in many arid and semi-arid regions that can have large negative impacts on water resources and agricultural production. Since agricultural drought is affected by both water supply and demand (precipitation and evapotranspiration), it is beneficial to include both in agricultural drought monitoring. The Standardized Precipitation-Evapotranspiration Index (SPEI) was found to be a suitable drought index for monitoring agricultural drought. In this study, the SPEI calculated from agro-meteorological weather stations was used to determine exceedance probabilities at five levels in the Texas High Plains. In addition, the kriging method was used to interpolate between the stations to generate spatial maps for the exceedance probabilities. No significant differences were found between stations, indicating any station should be suitable to represent the Texas High Plains. Results showed drought conditions occurred at all five probability levels during the summer growing season for this region. Although differences were not significantly different, the interpolated maps showed a trend where minor differences in the SPEI values were associated with the West-East precipitation gradient. However, there was no trend associated with the North-South air temperature gradient. A risk analysis showed that the SPEI probability values can provide policy and decision makers with additional information for better water management in the Texas High Plains.

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.

The distribution of drinking water-to-cattle ratios in the summer across four feedlots in the Texas High Plains

In this short communication, we report the findings of a cross-sectional pilot study of the amount of water available per head of cattle (water-to-cattle ratio) and the associated feedlot and environmental factors across 26 pens in four Texas feedlots. The water-to-cattle ratio varied greatly among pens within and between feedlots. Mixed-effect linear regression modeling with feedlot as a random effect indicated that water in troughs with a higher water-to-cattle ratio was generally warmer when compared with water in troughs with a lower water-to-cattle ratio. This may have implications in the transmission and persistence of pathogens in feedlot cattle, such as Shiga toxin-producing Escherichia coli and Salmonella, because warmer water has been reported to favor the growth of these pathogens. Therefore, future field studies in feedlot cattle are warranted to assess whether the water-to-cattle ratio affects the prevalence of these pathogens in the water itself or in feces shed by the animals.

Use of Unmanned Aerial System (UAS) Phenotyping to Predict Pod and Seed Yield in Organic Peanuts

Peanut (Arachis hypogaea L.) is a highly nutritious food that is an excellent source of protein and is associated with increased coronary health, lower risk of type-2 diabetes, lower risk of breast cancer and a healthy profile of inflammatory biomarkers. The domestic demand for organic peanuts has significantly increased, requiring new breeding efforts to develop peanut varieties adapted to the organic farming system. The use of unmanned aerial system (UAS) has gained scientific attention because of the ability to generate high-throughput phenotypic data. However, it has not been fully investigated for phenotyping agronomic traits of organic peanuts. Peanuts are beneficial for cardio system protection and are widely used. Within the U.S., peanuts are grown in 11 states on roughly 600,000 hectares and averaging 4500 kg/ha. This study’s objective was to test the accuracy of UAS data in the phenotyping pod and seed yield of organic peanuts. UAS data was collected from a field plot with 20 Spanish peanut breeding lines on July 07, 2021 and September 27, 2021. The study was a randomized complete block design (RCBD) with 3 blocks. Twenty-five vegetation indices (VIs) were calculated. The analysis of variance showed significant genotypic effects on all 25 vegetation indices for both flights (p < 0.05). The vegetation index Red edge (RE) from the first flight was the most significantly correlated with both pod (r = 0.44) and seed yield (r = 0.64). These results can be used to further advance organic peanut breeding efforts with high-throughput data collection.

Mitigating risks of hybrid rice use in terrace agriculture

The Honghe Hani Rice Terraces of Yunnan Province have become a national emblem for China and a UNESCO World Heritage Site,but some are beginning to crumble.This research attempts to address why this is happening and what can be done about it.Previous work has failed to adequately address the possible shortcomings of recently introduced seed and water management technologies,their particular effect on rice terraces and the people who depend upon them.In an effort to better understand the issue,field observation was triangulated with in-depth interviews with local people,and the examination of scientific literature.To do this,the authors spent time in China with a translator in a key village known to be first in the area to truly succeed in carving the rice terraces and in making the mountain slope irrigation system required actually working.Results validated by experts in each field indicate that while the new seed and technologies do save water and improve lives,paired with migration,they may also be threatening the long-term viability of rice terracing in the region.The authors conclude that an integrated approach is needed and put forward a strategic blueprint to reinforce ecological,social and economic longevity.They also call for more research into the applicability of these resilience measures in other hybrid rice terracing regions,such as in the Philippines and Vietnam.

The El Niño-Southern Oscillation (ENSO) Effects on Cowpea and Winter Wheat Yields in the Semi-Arid Region of the Southern US

Information is limited on the effects of climate variability on cowpea (Vigna unguiculata L.) and winter wheat (Triticum aestivum L.) yields in the semiarid region of the southern US. Using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and weather data spanning 81 years, we assessed the impact of El Niño-Southern Oscillation (ENSO) on the grain yields of these crops in the Llano Estacado region of the southern US as affected by cowpea and wheat planting dates and N application rate. Simulated results showed that the El Niño phase of ENSO produced about 30% more yields of mono-cropped cowpea than those produced under the La Niña phase, especially with the cowpeas planted in July. The cowpea yields under El Niño were about 10% more than the 81-year average normal yield, whereas those under La Niña were about 20% less. At the N rates of 0, 50, and 100 kg·ha−1, regardless of wheat planting dates, the El Niño years produced, respectively, about 8%, 40%, and 60% higher wheat yields than those produced in the La Niña years, and about 5%, 20%, and 27% more than the 81-year average normal yield. In the La Niña years, the wheat yields at 0, 50, and 100 kg N ha−1 were, respectively, about 5%, 15%, and 20% less than the normal yield with similar N levels. The impact of ENSO on wheat yields under cowpea-wheat double-cropping systems was significant, especially for the wheat crops planted on October 15 (October 30) or later following the cowpea crops planted in June (July). At zero N, the mono-cropped wheat yields were not impacted by ENSO due to N limitation. However, the double-cropped wheat yields were impacted by ENSO even when no N fertilizer was applied due to high soil N status caused by N transfer from cowpea stover residues and roots. Results indicated that management strategies need to be attentive to ENSO forecasts and adjust potential planting dates and N application rates with the ENSO phase to avert risks of crop failure and economic loss.

Exploring the Potential of Cowpea-Wheat Double Cropping in the Semi-Arid Region of the Southern United States Using the DSSAT Crop Model

Information is limited on the potential of double-cropping cowpea (Vigna unguiculata L.) and wheat (Triticum aestivum L.) in the semiarid region of the southern United States. Using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and weather data of 80 years, we assessed the possibility of cowpea-wheat double-cropping in this region for grain purpose as affected by planting date and N application rate. Results showed that the possibility of double-cropping varied from 0% to 65%, depending on the cropping system. The possibility was less with systems comprising earlier planting dates of wheat and later planting dates of cowpea. Results indicated that cowpea-wheat double-cropping could be beneficial only when no N was applied, with wheat planted on October 15 or later. At zero N, the double-crops of cowpea planted on July 15 and wheat planted on November 30 were the most beneficial of all the 72 double-cropping systems studied. With a delay in planting cowpea, the percentage of beneficial double-cropping systems decreased. At N rates other than zero, fallow-wheat monocropping systems were more beneficial than cowpea-wheat double-cropping systems, and the benefit was greater at a higher N rate. At 100 kg N ha-1, the monocrop of wheat planted on October 15 was the most beneficial of all the 94 systems studied. Results further showed that fallow-wheat yields increased almost linearly with an increase in N rate from 0 to 100 kg∙ha-1. Fallow-wheat grain yields were quadratically associated with planting dates. With an increase in N rate, wheat yields reached the peak with an earlier planting date. Wheat yields produced under monocropping systems were greater than those produced under double-cropping systems for any cowpea planting date. Cowpea yields produced under monocropping systems were greater than those produced under any double-cropping system. The relationship between cowpea grain yields and planting dates was quadratic, with July 1 planting date associated with the maximum yields.

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.

寄生蜂取食寄主特性及其在害虫生物防治中的作用

许多寄生性天敌昆虫的雌虫不仅寄生寄主,而且还能取食寄主。在卵育型(synovigenic)寄生蜂类群中,取食寄主行为是较为普遍的现象。本文综合近20年相关研究进展,从寄生蜂类群、取食类型、生态学意义及影响因子等方面对寄生蜂的取食寄主行为进行了归纳总结。寄生蜂通过取食不仅可以杀死寄主,直接起到控制害虫种群数量的作用,还能通过取食策略为卵的成熟和再生提供营养来源,对延长雌虫的寿命也有一定的帮助。对取食寄主行为的了解可为筛选优势寄生性天敌种类、评估寄生蜂在害虫生物防治中的作用提供重要信息。

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。

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.

Numerical Simulation on a Tremendous Debris Flow Caused by Typhoon Morakot in the Jiaopu Stream,Taiwan

In August 2009,Typhoon Morakot brought a large amount of rainfall with both high intensity and long duration to a vast area of Taiwan.Unfortunately,this resulted in a catastrophic landslide in Hsiaolin Village,Taiwan.Meanwhile,large amounts of landslides were formed in the Jiaopu Stream watershed near the southeast part of the Hsiaolin Village.The Hsiaolin Village access road(Provincial Highway No.21 and Bridge No.8) was completely destroyed by the landslide and consequent debris flow.The major scope of this study is to apply a debris flow model to simulate the disaster caused by the debris flow that occurred in the Jiaopu Stream during Typhoon Morakot.According to the interviews with local residents,this study applied the destruction time of Bridge No.8 and Chen's house to verify the numerical debris flow model.By the spatial rainfall distributions information,the numerical simulations of the debris flow are conducted in two stages.In the first stage(before the landslide-dam failure),the elevation of the debris flow and the corresponding potential damages toward residential properties were investigated.In the second stage(after the landslidedam failure),comparisons of simulation results between the longitudinal and cross profiles of the Jiaopu Stream were performed using topographic maps and satellite imagery.In summary,applications of the adopted numerical debris flow model have shown positive impact on supporting better understanding of the occurrence and movement of debris flow processes.

Effects of nitrogen management on the ratoon crop yield and head rice yield in South USA

Ratoon rice cropping is an important component of the rice cropping system in Texas and south Louisiana,USA,and expanded to Asian countries in 1970.Two field studies were conducted with widely planted rice(Oryza sativa L.)cultivars at Eagle Lake,Texas,USA to determine the effects of nitrogen(N)management in main(first)crop(MC)and ratoon(second)crop(RC)on RC yield.In 2012 and 2013,one cultivar(Presidio)was adopted to determine the effects of RC N management on ratoon yield and head rice yield.In 2016 and 2017,CL153,CL163 and CL272 in addition to Presidio were adopted to examine the effect of MC N management on ratoon yield and head rice yield.N applied at preflood after MC harvest considerably improved RC yield.Application of 99 kg N ha^(–1)at preflood after MC harvest was practically adequate for RC regrowth,development and approaching the yield potential for Presidio.RC could produce quite high average grain yields of 5.90 to 6.53 t ha–1 in 2012 and 2013,respectively.Main crop N rate only significantly affected MC yield;however,given N applied of 99 kg ha^(–1)at preflood after MC harvest,ratoon yield was not significantly affected by MC N rate.Neither the main nor ratoon crop N management had a significant effect on RC head rice yield.Considerable RC head rice yields(55–65%)were observed in all of the four cultivars and 4 years except for CL272 in 2016.These results indicat that without very high N fertilizer application,rice ratoon crop could produce a considerable grain yield and an expectative head rice yield.Rice ratooning could be a practical way to increase rice yields with the minimal input in south Texas and regions with a similar climate.

The effects of soil moisture and salinity as functions of groundwater depth on wheat growth and yield in coastal saline soils

In the coastal saline soils,moisture and salinity are the functions of groundwater depth affecting crop growth and yield.Accordingly,the objectives of this study were to:1)investigate the combined effects of moisture and salinity stresses on wheat growth as affected by groundwater depth,and 2)find the optimal groundwater depth for wheat growth in coastal saline soils.The groundwater depths(0.7,1.1,1.5,1.9,2.3,and 2.7 m during 2013-2014(Y1)and 0.6,1.0,1.4,1.8,2.2,and 2.6 m during 2014-2015(Y2))of the field experiment were maintained by soil columns.There was a positive correlation between soil moisture and salinity.Water logging with high salinity(groundwater depth at 0.7 m in Y1 and 0.6 m in Y2)showed a greater decline towards wheat growth than that of slight drought with medium(2.3 m in Y1)or low salinity(2.7 m in Y1,2.2 and 2.6 m in Y2).The booting stage was the most sensitive stage of wheat crop under moisture and salinity stresses.Data showed the most optimal rate of photosynthesis,grain yield,and flour quality were obtained under the groundwater depth(ditch depth)of 1.9 m(standard soil moisture with medium salinity)and 2.3 m(slight drought with medium salinity)in Y1 and 1.8 m(standard soil moisture with medium salinity)and 2.2 m(slight drought with low salinity)in Y2.The corresponding optimal soil relative moisture content and conductivity with the 1:5 distilled water/soil dilution,in the depth of 0-20 cm and 20-40 cm in coastal saline soils,were equal to 58.67-63.07%and 65.51-72.66%in Y1,63.09-66.70%and 69.75-74.72%in Y2;0.86-1.01 dS m^-1 and 0.63-0.77 dS m^-1 in Y1,0.57-0.93 dS m^-1 and 0.40-0.63 dS m^-1 in Y2,respectively.

Impact of time lags on diurnal estimates of canopy transpiration and canopy conductance from sap-flow measurements of Populus cathayana in the Qinghai–Tibetan Plateau

Recently, canopy transpiration （Ec） has been often estimated by xylem sap-flow measurements. However, there is a significant time lag between sap flow measured at the base of the stem and canopy transpiration due to the capacitive exchange between the transpiration stream and stem water storage. Significant errors will be introduced in canopy conductance （gc） and canopy transpiration estimation if the time lag is neglected. In this study, a cross-correlation analysis was used to quantify the time lag, and the sap flowbased transpiration was measured to pararneterize Jarvistype models of gc and thus to simulate Ec of Populus cathayana using the Penman-Monteith equation. The results indicate that solar radiation （Rs） and vapor pressure deficit （VPD） are not fully coincident with sap flow and have an obvious lag effect; the sap flow lags behind Rs and precedes VPD, and there is a 1-h time shift between Eo and sap flow in the 30-min interval data set. A parameterized Jarvis-type gc model is suitable to predict P. cathayana transpiration and explains more than 80% of the variation observed in go, and the relative error was less than 25%, which shows a preferable simulation effect. The root mean square error （RMSEs） between the predicted and measured Ec were 1.91×10^-3 （with the time lag） and 3.12×10^-3cm h^-1 （without the time lag）. More importantly, Ec simulation precision that incorporates time lag is improved by 6% compared to the results without the time lag, with the mean relative error （MRE） of only 8.32% and the mean absolute error （MAE） of 1.48 × 10^-3 cm h^-1.

Remote Monitoring of Wheat Streak Mosaic Progression Using Sub-Pixel Classification of Landsat 5 TM Imagery for Site Specific Disease Management in Winter Wheat

Wheat streak mosaic (WSM), caused by Wheat streak mosaic virus is a viral disease that affects wheat (Triticum aestivum L.), other grains, and numerous grasses over large geographical areas around the world. To improve disease management and crop production, it is essential to have adequate methods for monitoring disease epidemics at various scales and multiple times. Remote sensing has become an essential tool for monitoring and quantifying crop stress due to biotic and abiotic factors. The objective of our study was to explore the utility of Landsat 5 TM imagery for detecting, quantifying, and mapping the occurrence of WSM in irrigated commercial wheat fields. The infection and progression of WSM was biweekly assessed in the Texas Panhandle during the 2007-2008 crop years. Diseased-wheat was separated from uninfected wheat on the images using a sub-pixel classifier. The overall classification accuracies were >91% with kappa coefficient between 0.80 and 0.94 for disease detection were achieved. Omission errors varied between 2% and 14%, while commission errors ranged from 1% to 21%. These results indicate that the TM image can be used to accurately detect and quantify disease for site-specific WSM management. Remote detection of WSM using geospatial imagery may substantially improve monitoring, planning, and management practices by overcoming some of the shortcomings of the ground-based surveys such as observer bias and inaccessibility. Remote sensing techniques for accurate disease mapping offer a unique set of advantages including repeatability, large area coverage, and cost-effectiveness over the ground-based methods. Hence, remote detection is particularly and practically critical for repeated disease mo- nitoring and mapping over time and space during the course of a growing season.

Effect of Source-Sink Manipulation on Photosynthetic Characteristics of Flag Leaf and the Remobilization of Dry Mass and Nitrogen in Vegetative Organs of Wheat

The photosynthetic characteristics of flag leaf and the accumulation and remobilization of pre-anthesis dry mass（DM） and nitrogen（N） in vegetable organs in nine wheat cultivars under different source-sink manipulation treatments including defoliation（DF）, spike shading（SS） and half spikelets removal（SR） were investigated. Results showed that the SS treatment increased the photosynthetic rate（Pn） of flag leaf in source limited cultivar, but had no significant effect on sink limited cultivar. The SR treatment decreased the Pn of flag leaf. Grain DM accumulation was limited by source in some cultivars, in other cultivars, it was limited by sink. Grain N accumulation was mainly limited by source supply. The contribution of pre-anthesis dry mass to grain yield from high to low was stem, leaf and chaff, while the contribution of pre-anthesis N to grain N from high to low was leaf, stem and chaff. Cultivars S7221 and TA9818 can increase the contribution of remobilization of DM and N to grain at the maximum ratio under reducing source treatments, which may be the major reason for these cultivars having lower decrease in grain yield and N content under reducing source treatments.