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The current assays to confirm herbicide resistance can be time- and labor-intensive (dose–response) or require a skill set/technical equipment (genetic sequencing). Stakeholders could benefit from a rapid assay to confirm herbicide-resistant weeds to ensure sustainable crop production. Because protoporphyrinogen oxidase (PPO)-inhibiting herbicides rapidly interfere with chlorophyll production/integrity; we propose a new, rapid assay utilizing spectral reflectance to confirm resistance. Leaf disks were excised from two PPO-inhibiting herbicide-resistant (target-site [TSR] and non–target site [NTSR]) and herbicide-susceptible redroot pigweed (Amaranthus retroflexus L.) populations and placed into a 24-well plate containing different concentrations (0 to 10 mM) of fomesafen for 48 h. A multispectral sensor captured images from the red (668 nm), green (560 nm), blue (475 nm), and red edge (717 nm) wavebands after a 48-h incubation period. The green leaf index (GLI) was utilized to determine spectral reflectance ratios of the treated leaf disks. Clear differences of spectral reflectance were observed in the red edge waveband for all populations treated with the 10 mM concentration in the dose–response assays. Differences of spectral reflectance were observed for the NTSR population compared with the TSR and susceptible populations treated with the 10 mM concentration in the green waveband and the GLI in the dose–response assay. Leaf disks from the aforementioned A. retroflexus populations and two additional susceptible populations were subjected to a similar assay with the discriminating concentration (10 mM). Spectral reflectance was different between the PPO-inhibiting herbicide-resistant and herbicide-susceptible populations in the red, blue, and green wavebands. Spectral reflectance was not distinctive between the populations in the red edge waveband and the GLI. The results provide a basis for rapidly (∼48 h) detecting PPO-inhibiting herbicide-resistant A. retroflexus via spectral reflectance. Discrimination between TSR and NTSR populations was possible only in the dose–response assay, but the assay still has utility in distinguishing herbicide-resistant plants from herbicide-susceptible plants.

Complaints of control failures with acetolactate synthase (ALS)- and protoporphyrinogen oxidase (PPO)-inhibiting herbicides on redroot pigweed (Amaranthus retroflexus L.) were reported in conventional soybean [Glycine max (L.) Merr.] fields in North Carolina. Greenhouse dose–response assays confirmed that the Camden County and Pasquotank County populations were less sensitive to ALS- and PPO-inhibiting herbicides compared with susceptible A. retroflexus populations, suggesting the evolution of resistance to these herbicides. Sanger sequencing of target genes determined the Camden County population carried a Trp-574-Leu mutation in the ALS gene and an Arg-98-Gly mutation in the PPX2 gene, while the Pasquotank County population carried a His-197-Pro mutation in the ALS gene (first documentation of the mutation in the Amaranthus genus), but no mutation was detected in the PPX2 gene. Single-nucleotide polymorphism (SNP) genotyping assays were developed to enable efficient screening of future control failures in order to limit the spread of these herbicide-resistant populations. In addition, preliminary testing of these assays revealed the three mutations were ubiquitous in the respective populations. These two populations represent the first confirmed cases of PPO-inhibiting herbicide-resistant A. retroflexus in the United States, as well as the first confirmed cases of this particular herbicide-resistance profile in A. retroflexus inhabiting North America. While no mutation was found in the PPX2 gene of the Pasquotank County population, we suggest that this population has evolved resistance to PPO-inhibiting herbicides, but the mechanism of resistance is to be determined.

Glufosinate is an effective postemergence herbicide, and overreliance on this herbicide for weed control is likely to increase and select for glufosinate-resistant weeds. Common assays to confirm herbicide resistance are dose–response and molecular sequencing techniques; both can require significant time, labor, unique technical equipment, and a specialized skillset to perform. As an alternative, we propose an image-based approach that uses a relatively inexpensive multispectral sensor designed for unmanned aerial vehicles to measure and quantify surface reflectance from glufosinate-treated leaf disks. Leaf disks were excised from a glufosinate-resistant and glufosinate-susceptible corn (Zea mays L.), cotton (Gossypium hirsutum L.), and soybean [Glycine max (L.) Merr.] varieties and placed into a 24-well plate containing eight different concentrations (0 to 10 mM) of glufosinate for 48 h. Multispectral images were collected after the 48-h incubation period across five discrete wave bands: blue (475 to 507 nm), green (560 to 587 nm), red (668to 682 nm), red edge (717 to 729 nm), and near infrared (842 to 899 nm). The green leaf index (GLI; a metric to measure chlorophyll content) was utilized to determine relationships between measured reflectance from the tested wave bands from the treated leaf disks and the glufosinate concentration. Clear differences of spectral reflectance were observed between the corn, cotton, and soybean leaf disks of the glufosinate-resistant and glufosinate-susceptible varieties at the 10 mM concentration for select wave bands and GLI. Leaf disks from two additional glufosinate-resistant and glufosinate-susceptible varieties of each crop were subjected to a similar assay with two concentrations: 0 and 10 mM. No differences of spectral reflectance were observed from the corn and soybean varieties in all wave bands and the GLI. The leaf disks of the glufosinate-resistant and glufosinate-susceptible cotton varieties were spectrally distinct in the green, blue, and red-edge wave bands. The results provide a basis for rapidly detecting glufosinate-resistant plants via spectral reflectance. Future research will need to determine the glufosinate concentrations, useful wave bands, and susceptible/resistant thresholds for weeds that evolve resistance.

The peanut is mostly grown in semi-arid tropical regions of the world, characterized by unpredictable rainfall amounts and distribution. Average annual precipitation in the Virginia–Carolina (VC) region is around 1300 mm; however, unpredictable distribution can result in significant periods of water deficit and subsequent reduction in yield and gross income. The development of new peanut cultivars with high yield and acceptable levels of yield stability across various water-availability scenarios is an important component of the peanut breeding program in Virginia and the Carolinas, where the large-seeded Virginia-type peanut is the predominantly grown market type. In addition, the simultaneous use of runner cultivars developed in the dryer southeastern region has been proposed as a practical solution to limited irrigation availability in the VC region. Still, the identification and adequate utilization of available commercial cultivars with the best combination of yield, drought tolerance, and gross income is more immediately beneficial to the peanut industry, yet this assessment has not been carried out to date. The aim of this study was to identify cultivars that maintain high yield and grade, therefore gross income, across a wide range of environmental conditions. We evaluated five commercially available Virginia and runner-type peanut cultivars for pod yield stability using multilocation trials over four years across 13 environments. Additive main effects and multiplicative interaction (AMMI) and different stability approaches were used to study genotype (G), environment (E), and their interaction (G × E) on pod yield. Pod yield stability was specifically assessed by using the Lin and Binn approach, Wricke’s ecovalence, Shukla’s stability, and the Finlay–Wilkinson approach. The combined analysis of variance showed highly significant effects (p ≤ 0.001) for genotypes, environments, and G × E for pod yield. The environments varied in yield (2840–8020 kg/ha). Bailey, Sullivan, and Wynne are Virginia-type cultivars. The grade factors SMK, SS, and TK changed with water regime within both market types. Among the runner cultivars, TUFRunner 297 presented high mean productivity; however, it showed specific adaptation to limited environmental conditions. Based on different stability approaches, this study concludes that Sullivan and Bailey are the most stable and adaptable cultivars across the testing environments, whereas Wynne exhibited specific adaptability to some environments. These findings have important implications for peanut cultivar recommendations in terms of meeting peanut industry standards for yield, grading quality, and breeding progress. Published version

Evolution of resistance to multiple herbicides with different sites of action and of nontarget site resistance (NTSR) often involves multiple genes. Thus, single‐gene analyses, typical in studies of target site resistance, are not sufficient for understanding the genetic architecture and dynamics of NTSR and multiple resistance. The genetics of weed adaptation to varied agricultural environments is also generally expected to be polygenic. Recent advances in whole‐genome sequencing as well as bioinformatic and statistical tools have made it possible to use population and quantitative genetics methods to expand our understanding of how resistance and other traits important for weed adaptation are genetically controlled at the individual and population levels, and to predict responses to selection pressure by herbicides and other environmental factors. The use of tools such as quantitative trait loci mapping, genome‐wide association studies, and genomic prediction will allow pest management scientists to better explain how pests adapt to control tools and how specific genotypes thrive and spread across agroecosystems and other human‐disturbed systems. The challenge will be to use this knowledge in developing integrated weed management systems that inhibit broad resistance to current and future weed‐control methods. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry., Recent advances in whole‐genome sequencing as well as bioinformatic and statistical tools have made it possible to use population and quantitative genetics methods to expand our understanding of how resistance and fitness changes are genetically controlled and to predictively measure their response to selection pressure.

Symbiotic nitrogen-fixation activity of grain legumes commonly does not exhibit tolerance to soil drying, including in peanut (Arachis hypogaea L.). Since the demand for nitrogen of peanut is large...

The objective of this study was to examine peanut (Arachis hypogaea L.) kernel percent sound splits as a function of sound mature kernel seed size when shelled on a reciprocating sheller. Data were compiled from a total of 139 field experiments conducted in the Virginia-Carolina region and Georgia from 2005 to 2020. Runner and Virginia peanut market types were graded according to United States Department of Agriculture (USDA) standards using standard sheller screens with upper grid sizes corresponding to the red pan from the pre-sizer of 10.3 × 19.1 mm (26/64 × 3/4 ″) and 13.5 × 25.4 mm (34/64 × 1 ″) with minimum bar grid clearances of 8.7 (11/32 ″) and 12.7 mm (1/2 ″), respectively. A subset of runner market type samples was graded using the Virginia sheller screen. Grade data per market type and sheller screen was analyzed separately. Among runner market types shelled with the standard runner-type screen, percent sound splits increased linearly with increasing seed size at the logit rate of 1.16 per sound mature kernel g (p < 0.001). Sound splits for Virginia and runner market types shelled on the standard Virginia-type screen did not significantly vary by kernel size (p = 0.939 and 0.687, respectively). Extra-large kernels (proportion) for Virginia types linearly increased with seed size at 1.91 per sound mature kernel g (logit scale) (p < 0.001). Runner market types sized 75 to 91 g/100 sound mature kernels (605 to 500 seed/lb) were estimated to have a 50% probability of a 2.3 to 4.5% or greater increase in sound splits when shelled with the standard runner-type screen compared to runner-type seed sized 55 g/100 sound mature kernels (820 seed/lb), respectively, equivalent to a potential deduction increase of 1.8 to 4.4 USD /1000 kg. For both Virginia and runner market types, seed weight linearly increased with pod weight at 0.169 and 0.195 g/g (p < 0.001), respectively. Results from this study may be used as a reference to suggest runner-type seed sizes above which larger reciprocating sheller screen utilization in line with USDA grading practices is warranted to reduce mechanically induced sound splits during grading and subsequent economic deduction penalties for corresponding farmer stock peanut. Published version

Bermudagrass (Cynodon (L.)) is the most important warm-season grass grown for forage or turf. It shows extensive variation in morphological characteristics and growth attributes, but the genetic basis of this variation is little understood. Detection and tagging of quantitative trait loci (QTL) affecting above-ground morphology with diagnostic DNA markers would provide a foundation for genetic and molecular breeding applications in bermudagrass. Here, we report early findings regarding genetic architecture of foliage (canopy height, HT), stolon (stolon internode length, ILEN and length of the longest stolon LLS), and leaf traits (leaf blade length, LLEN and leaf blade width, LW) in 110 F1 individuals derived from a cross between Cynodon dactylon (T89) and C. transvaalensis (T574). Separate and joint environment analyses were performed on trait data collected across two to five environments (locations, and/or years, or time), finding significant differences (P < 0.001) among the hybrid progeny for all traits. Analysis of marker-trait associations detected 74 QTL and 135 epistatic interactions. Composite interval mapping (CIM) and mixed-model CIM (MCIM) identified 32 main effect QTL (M-QTL) and 13 interacting QTL (int-QTL). Colocalization of QTL for plant morphology partially explained significant correlations among traits. M-QTL qILEN-3-2 (for ILEN; R2 = 11–19%), qLLS-7-1 (for LLS; R2 = 13–27%), qLEN-1-1 (for LLEN; R2 = 10–11%), and qLW-3-2 (for LW; R2 = 10–12%) were ‘stable’ across multiple environments, representing candidates for fine mapping and applied breeding applications. QTL correspondence between bermudagrass and divergent grass lineages suggests opportunities to accelerate progress by predictive breeding of bermudagrass.

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

The development of cultivars ‘TifGrand’ and ‘Celebration’ has shown potential increases in shade tolerance compared to previous industry standards of bermudagrass ( Cynodon spp.). Based on the literature, further improvements in shade tolerance can be attained through changes in nitrogen fertility rates, mowing heights, and the application of plant growth regulators. In this study, two South African hybrid ( Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt Davy) bermudagrass accessions (‘WIN10F’ and ‘STIL03’) and three standard cultivars (Celebration, Tifgrand, and ‘Tifway’) were compared for their ability to persist under 63% shade, two mowing heights, two trinexapac-ethyl (TE) treatments, and two nitrogen fertility rates. The experimental design was a strip-strip-split plot and digital image analysis was used to measure percent turfgrass cover, percent turfgrass spread after cup-cutter removal, and percent turfgrass re-growth after divot formation. Turf quality was measured using the normalized difference vegetation index (NDVI). Differences among genotypes, TE treatments, and mowing heights were observed across all response variables in 2014 and 2015. Differences in fertility treatments were observed in NDVI, percent turfgrass growth, and percent turfgrass recovery within and across years. Significant differences were observed for the interactions between entry by plant growth regulator (PGR) treatments, entry by mowing height, and mowing height by PGR. These results suggest shade management recommendations should be dependent on genotype and site-specific considerations. The development and implementation of specific management plans for certain bermudagrass varieties will contribute to the more widespread use of Cynodon spp. in shaded environments.

The use of genetic information to predict the value of individuals in plant breeding populations began about 40 years ago. The original paradigm was to identify genomic regions with outsize influence on a trait of economic value and then to use markers in that genomic region to select individuals carrying the desired allelic variants. An explosion of interest in mapping such quantitative trait loci (QTL) followed, with thousands of genomic regions associated with important traits across many species. The practical use of such information lagged well behind the discovery of QTL, however, due mostly to the problem that individual markers were often only associated with a small proportion of genetic variation, such that their value in selection was very small. In a few lucky cases, individual genes with very large effects on important traits were discovered, and these could be more easily turned into useful selection targets. Genome-wide association studies have improved the ability to identify individual variants associated with useful effects in crops, but the fundamental problem of accurately estimating marker effects and using them in selection remains for traits affected by many genes. Genomic selection was proposed by animal breeders as a way to more effectively use the information contained in dense genetic marker sets for the prediction of quantitative traits. Crop breeders subsequently discovered that this approach could be generalized across the diverse population structures and mating systems of plants and have begun implementing genomic selection in crops with success. Here, we first discuss how to identify and select for major genes and QTL in the breeding process. We then discuss the myriad benefits of implementing genomic selection to improve the rate of genetic gain.

A diversity of pests can adversely affect peanut (Arachis hypogaea L.) yield, quality, and financial return. Farmers rely heavily on applied chemicals to suppress many of the economically important pests present in peanut. The effectiveness of this approach to pest management may not be sustainable, however, due to evolved resistance in pests to chemicals, reluctance of basic chemical manufacturers to invest in product development because of the relatively small market for peanut compared with other crops, cost to initially register or re‐register chemicals, and the desire for peanut buyers and processors to capture international markets that may have varying agrochemical residue restrictions for peanut. Heavy reliance on chemical control could leave peanut production systems vulnerable to yield loss; thus, a more concerted research effort is needed to increase the number and availability of nonchemical tools that protect peanut from pests in order to ensure long‐term sustainability of peanut production systems.

Zoysiagrasses (Zoysiaspp.) are warm season turfgrasses primarily grown in the southern and transition zones of the United States. An understanding of the physiological changes that zoysiagrasses undergo during cold acclimation may shed light on physiological phenotypic traits useful in selection of freeze tolerant genotypes. We investigated the relationship between cold acclimation, protein expression, and freeze tolerance in cold-acclimated (CA) and non-acclimated (NCA) plants ofZoysia japonicaSteud. cultivars ‘Meyer’ (freeze-tolerant) and ‘Victoria’ (freeze-susceptible). Freeze tolerance was assessed using chambers reaching −6, −8, −10, and −12°C. Additionally, meristematic tissues from the grass crowns of ‘Meyer’ and ‘Victoria’ were harvested for proteomic analysis after a four week cold acclimation period. Freeze testing indicated that cold acclimation accounted for a 1.9-fold increase in plant survival compared to the non-acclimation treatment. Overall, proteomic analysis identified 62 protein spots having at least a twofold change in abundance under cold acclimation. Nine and 22 unique protein spots were identified for Meyer and Victoria, respectively, with increased abundance (up-regulated) or decreased abundance (down-regulated). In addition, 23 shared protein spots were found among the two cultivars having differential expression in response to cold acclimation. In Meyer, protein response to cold acclimation was primarily upregulated, while in Victoria, protein response was primarily downregulated. These cold acclimation responsive proteins were found to be involved primarily in transcription, metabolism, protein destination and storage, and energy production. As identified through MALDI-TOF/TOF mass spectrometry followed matching of protein homologues against the NCBI Arabidopsis database, major proteins of interest for their association with cold acclimation were LEA 3, MAPK, SOD, GAST1, Phytochrome A, ATP synthase, AGP, PLD, and PSII. Further investigation of these proteins and their functional categories may contribute to increase our understanding of the differences in freezing tolerance among zoysiagrass germplasm.

Bermudagrass, Cynodon spp. is one of the most commonly grown turfgrass genera in the southern United States having excellent drought tolerance, but poor tolerance to shade. Developing cultivars tolerant to shade would allow bermudagrass to become more prevalent in home lawns or other recreational areas in the southeast, where trees dominate the landscape. In this field study, nine accessions collected from Pretoria, South Africa were evaluated for their ability to grow under shade with varying fertility treatments. These accessions and cultivars ‘Celebration’, ‘TifGrand’, and ‘Tifway’ were evaluated under 0%, 63%, and 80% continuous shade during 2011–12. For both years, significant differences among shade levels, genotypes, and the interaction of the two were observed. As expected, the progression from 0% to 63% to 80% shade reduced normalized difference vegetation index (NDVI), percent turfgrass cover (TC), and turf quality (TQ) readings for all accessions. Some genotypes, however, were able to maintain adequate quality and aggressiveness under 63% shade. ‘Celebration’, WIN10F, and STIL03 performed better than ‘Tifway’ (P ≤ 0.05), the susceptible control. Overall, our results indicate that there are promising genotypes among the bermudagrass materials collected from South Africa. These accessions represent additional sources of shade hardiness to be used in bermudagrass breeding. Furthermore, higher nitrogen fertility provided increased NDVI and TQ in some instances suggesting an added benefit of fertility under low-light conditions. However, the increased economic value attributed to the added inputs associated with these increases is outweighed by the low impacts offered.

The phenotypic and genetic diversity of maize worldwide is remarkable. This chapter summarizes decades of studies of the genetic diversity of maize populations from different parts of the world, methods used to group maize into informal hierarchies, and how these groupings partition genetic and trait variation. The USA is the most important maize-producing nation, but the genetic diversity of USA maize is small relative to the available worldwide variation. Tropical maize harbors more genetic variation, but is not adapted to growing in temperate environments. Two distinct approaches to tapping the global reservoir of maize diversity to improve USA and other temperate region maize crops are outlined. One approach, allele mining, involves discovery of alleles with large favorable effects on traits in exotic germplasm, followed by marker-aided backcrossing or gene editing to introduce specific unique alleles into elite breeding populations. Alternatively, for traits conditioned mostly by many small-effect polygenes, rapid genomic selection for adaptation followed by combining ability within pure exotic populations could be used to create adapted and improved versions of exotic populations before they are crossed to elite adapted inbreds to make new breeding populations.

Zoysia japonica Steud. (2n = 4× = 40) is a C4 turfgrass well-adapted for the warm-humid and transitional climatic zones of the USA. Its use is limited to warmer climates because of a relative lack of winter hardiness compared to C3 grasses. Molecular markers associated with this trait would be useful for effective selection of winter hardy germplasm before field testing. A pseudo-F2 mapping population of 175 individuals was developed from crosses between Z. japonica cultivars “Meyer” (freeze-tolerant) and “Victoria” (freeze-susceptible) and used to generate a high-density genetic map of 104 SSR markers and 2359 sequencing-derived SNP markers. The map covers 324 Mbp and 2520 cM as well as the 20 chromosomes for the zoysiagrass haploid genome. Phenotypic data on winter injury, establishment, and turf quality collected in North Carolina and Indiana in 2014–2016 were used in conjunction with this map to identify quantitative trait loci (QTL) associated with winter hardiness. Fifty-six QTL associated with winter injury, establishment, and turf quality were identified over six environments. Twelve of those were identified in two or more environments. Furthermore, seven regions of interest were identified on chromosomes 8, 11, and 13 where co-location of QTL for three or more traits occurred. Within these regions, analysis with NCBI basic local alignment search tool (BLAST) identified proteins related to cold and other abiotic stresses tolerance. These QTL and associated markers could be valuable in implementing marker-assisted selection for winter hardiness in zoysiagrass breeding programs.

Intercept drain tile installation and subsequent sand topdressing applications can provide a built-up sand-based system. There are a number of different intercept drain tile spacing and sand layer depth recommendations. The objectives of this research were to determine the effects of intercept drain tile spacing on the surface runoff, soil water content, and surface shear strength of a compacted sandy loam with sand topdressing. A single factor, RCBD field study in East Lansing, Michigan, was seeded May 29, 2007, with a Kentucky bluegrass (Poa pratensis L.)― perennial ryegrass (Lolium perenne L.) mixture. Intercept drain tiles were spaced 2.0, 3.0, 4.0, and 6.0 m apart and were compared with an 8.1-m-long control without intercept drain tiles. Well-graded sand (90.0% sand, 7.0% silt, and 3.0% clay) was used for topdressing. After the accumulation of a 2.4-cm sand layer, simulated traffic at two applications per week was applied to all treatments using the Cady traffic simulator from October 10 to November 3, 2007. In 2008, topdressing, providing a 4.8-cm depth accumulated during a 2-year period, and traffic were repeated on the same experimental treatments. When a 2.4-cm sand layer is present, surface runoff and soil water content are generally directly related to intercept drain tile spacing, and drain tiles, spaced 2.0, 3.0, and 4.0 m apart, will provide increased surface shear strength. As topdressing depths were accumulated to a 4.8-cm sand layer depth in 2008, no differences in surface shear strength were observed regardless of drain tile spacing.

Drain tile installation into a native-soil athletic field and subsequent sand topdressing applications are cost-effective alternatives to complete field renovation. However, if cumulative topdressing rates exceed root system development, surface stability may be compromised. The objective of this research was to evaluate the effects of cumulative topdressing, over a compacted sandy loam soil, on the fall wear tolerance and surface shear strength of a kentucky bluegrass (Poa pratensis)–perennial ryegrass (Lolium perenne) stand. Research was initiated in East Lansing, MI, on 10 Apr. 2007. A well-graded, high-sand-content root zone (90.0% sand, 7.0% silt, and 3.0% clay) was topdressed at a 0.25-inch depth [2.0 lb/ft2 (dry weight)] per application, providing cumulative topdressing depths of 0.0, 0.5, 1.0, 1.5, or 2.0 inches applied from 11 July to 15 Aug. 2007. Fall traffic was applied twice weekly to all treatments from 10 Oct. to 3 Nov. 2007. In 2008, topdressing applications and traffic, as described earlier, were repeated on the same experimental plots. Results obtained from this research suggest that the 0.5-inch topdressing depth applied over a 5-week period in the summer will provide improved shoot density and surface shear strength in the subsequent fall. Results also suggest that topdressing rates as thick as 4.0 inches accumulated over a 2-year period will provide increased shoot density, but diminished surface shear strength.

Apoptosis is a key pathogenic mechanism in sepsis that induces extensive death of lymphocytes and dendritic cells, thereby contributing to the immunosuppression that characterizes the septic disorder. Numerous animal studies indicate that prevention of apoptosis in sepsis improves survival and may represent a potential therapy for this highly lethal disorder. Recently, novel cell-penetrating peptide constructs such as HIV-1 TAT basic domain and related peptides have been developed to deliver bioactive cargoes and peptides into cells. In the present study, we investigated the effects of sepsis-induced apoptosis in Bcl-xL transgenic mice and in wild-type mice treated with an antiapoptotic TAT-Bcl-xL fusion protein and TAT-BH4 peptide. Lymphocytes from Bcl-xL transgenic mice were resistant to sepsis-induced apoptosis, and these mice had a ∼3-fold improvement in survival. TAT-Bcl-xL and TAT-BH4 prevented Escherichia coli-induced human lymphocyte apoptosis ex vivo and markedly decreased lymphocyte apoptosis in an in vivo mouse model of sepsis. In conclusion, TAT-conjugated antiapoptotic Bcl-2-like peptides may offer a novel therapy to prevent apoptosis in sepsis and improve survival.