Comparing test cultivars using reliability functions of test-check differences from on-farm trials

An approach to selection is proposed that is based on the probabilities that a test cultivar outperforms a check by more than an amount d in a future environment. The function that gives these probabilities for all possible values of d is called the reliability function. When d=0, the value of the reliability function is the probability that the test cultivar outperforms the check. The method is illustrated using data from on-farm maize (Zea mays L.) strip test trials grown cooperatively by Pioneer Hi-bred International and farmers. Results indicate that reliability functions are useful for evaluating how test cultivars perform relative to a check across a range of environments since the location, slope and shape of the reliability function may be used to describe a test cultivar's performance, similarity to the check and stability, and identify environments where the test cultivar has performance problems.Contribution from the Agric Res Div, Univ Nebraska, Lincoln, Neb. Paper No. 9913.     

Expected utility maximization and selection of stable plant cultivars

Summary In most plant breeding programs, selection of the best commercially suitable cultivars for a target group of environments is based on information obtained from evaluation trials cultivated in a sample of environments. Information on the performance of cultivars collected in a sample of environments can only be approximate and, consequently, selection of the best cultivar involves choosing among cultivars that respond uncertainly in many environments. The agronomic and/or economic value of a cultivar across environments may be considered the general or overall utility of the cultivar. Data from a sample of environments therefore provides only an estimate of any cultivar's overall utility, with the overall goal of selection among all cultivars being the maximization of the expected utility. Within this frame-work, expected utility maximization, an approach to decision making that has been well developed in the disciplines of economics and statistics, can assist the plant breeder in making such decisions. This research was initiated (1) to determine how expected utility maximization might be used to develop indices that are useful for selecting broadly adapted plant cultivars, and (2) to determine how the breeder's preferences might affect choice of the best cultivar. The data used in this research were from USDA Regional Soybean Tests. The results indicated that expected utility maximization, which explicitly incorporates into the selection rule the plant breeder's preferences regarding stability, can be a useful aid in the selection of stable plant cultivars.     

Parameter stability of the functional-structural plant model GREENLAB as affected by variation within populations, among seasons and among growth stages

BACKGROUND AND AIMS: It is increasingly accepted that crop models, if they are to simulate genotype-specific behaviour accurately, should simulate the morphogenetic process generating plant architecture. A functional-structural plant model, GREENLAB, was previously presented and validated for maize. The model is based on a recursive mathematical process, with parameters whose values cannot be measured directly and need to be optimized statistically. This study aims at evaluating the stability of GREENLAB parameters in response to three types of phenotype variability: (1) among individuals from a common population; (2) among populations subjected to different environments (seasons); and (3) among different development stages of the same plants. METHODS: Five field experiments were conducted in the course of 4 years on irrigated fields near Beijing, China. Detailed observations were conducted throughout the seasons on the dimensions and fresh biomass of all above-ground plant organs for each metamer. Growth stage-specific target files were assembled from the data for GREENLAB parameter optimization. Optimization was conducted for specific developmental stages or the entire growth cycle, for individual plants (replicates), and for different seasons. Parameter stability was evaluated by comparing their CV with that of phenotype observation for the different sources of variability. A reduced data set was developed for easier model parameterization using one season, and validated for the four other seasons. KEY RESULTS AND CONCLUSIONS: The analysis of parameter stability among plants sharing the same environment and among populations grown in different environments indicated that the model explains some of the inter-seasonal variability of phenotype (parameters varied less than the phenotype itself), but not inter-plant variability (parameter and phenotype variability were similar). Parameter variability among developmental stages was small, indicating that parameter values were largely development-stage independent. The authors suggest that the high level of parameter stability observed in GREENLAB can be used to conduct comparisons among genotypes and, ultimately, genetic analyses.     

Genetic properties of four types of stability parameter

Summary The genetic properties of four types of stability parameter for individual genotypes were investigated using a set of diallel cross data (28 genotypes x four locations x 3 years). The specific parameters studied were: the variance of a genotype across environments (T1); the genotype x environment (GE) interaction effect for a genotype, squared and summed across all environments (T2); the residual mean square (MS) of deviations from the regression of a genotype on an environmental index (T3); and years within locations MS for a genotype, averaged over all locations (T4). Each stability statistic was fitted to the additive model, based on the assumption that if the stability parameter is heritable, stability of F₁ is most likely to be the average stability of its parents. The results showed that T1 and T4 were additive, but T2 and T3 were not. A study of the consistency of stability rankings between two seeding rates over the same set of environments showed a similar pattern. It appears that stability parameters of types 1 and 4 are heritable, and thus useful for selection, while those of types 2 and 3 are nonheritable, and thus not useful.Contribution No. R-029     

Biotechnology applications of amino acids in protein purification and formulations

Summary. Amino acids are widely used in biotechnology applications. Since amino acids are natural compounds, they can be safely used in pharmaceutical applications, e.g., as a solvent additive for protein purification and as an excipient for protein formulations. At high concentrations, certain amino acids are found to raise intra-cellular osmotic pressure and adjust to the high salt concentrations of the surrounding medium. They are called “compatible solutes”, since they do not affect macromolecular function. Not only are they needed to increase the osmotic pressure, they are known to increase the stability of the proteins. Sucrose, glycerol and certain amino acids were used to enhance the stability of unstable proteins after isolation from natural environments. The mechanism of the action of these protein-stabilizing amino acids is relatively well understood. On the contrary, arginine was accidentally discovered as a useful reagent for assisting in the refolding of recombinant proteins. This effect of arginine was ascribed to its ability to suppress aggregation of the proteins during refolding, thereby increasing refolding efficiency. By the same mechanism, arginine now finds much wider applications than previously anticipated in the research and development of proteins, in particular in pharmaceutical applications. For example, arginine solubilizes proteins from loose inclusion bodies, resulting in efficient production of active proteins. Arginine suppresses protein–protein interactions in solution and also non-specific adsorption to gel permeation chromatography columns. Arginine facilitates elution of bound proteins from various column resins, including Protein-A or dye affinity columns and hydrophobic interaction columns. This review covers various biotechnology applications of amino acids, in particular arginine.     

Global stability, local stability and permanence in model food webs

The dynamical theory of food webs has been based typically on local stability analysis. The relevance of local stability to food web properties has been questioned because local stability holds only in the immediate vicinity of the equilibrium and provides no information about the size of the basin of attraction. Local stability does not guarantee persistence of food webs in stochastic environments. Moreover, local stability excludes more complex dynamics such as periodic and chaotic behaviors, which may allow persistence. Global stability and permanence could be better criteria of community persistence. Our simulation analysis suggests that these three stability measures are qualitatively consistent in that all three predict decreasing stability with increasing complexity. Some new predictions on how stability depends on food web configurations are generated here: a consumer-victim link has a smaller effect on the probabilities of stability, as measured by all three stability criteria, than a pair of recipient-controlled and donor-controlled links; a recipient-controlled link has a larger effect on the probabilities of local stability and permanence than a donor-controlled link, while they have the same effect on the probability of global stability; food webs with equal proportions of donor-controlled and recipient-controlled links are less stable than those with different proportions.     

试用多元分析方法研究植物形态结构与生态环境的关系

应用多元分析方法对栎属高山栎组不同环境条件下的３３个植物样品的形态解剖性状的１７个指标进行了综合分析．结果表明,二元指示种分析（ＴＷＩＮＳＰＡＮ）聚类的结果能很好地把相似生态环境条件下的样品聚在一起,对样品进行无趋势对应分析（ＤＣＡ）和主成分分析（ＰＣＡ）都得到了满意结果．植物形态解剖性状的聚类、排序分析也可用来研究个体性状之间变异的连续性和间断性,进而有助于分类学的研究．     

Strategies for Improving Drought Resistance in Grain Legumes

This review distills recent information on drought resistance characteristics of grain legumes with a view toward developing appropriate genetic enhancement strategies for water-limited environments. First, the possible adaptations that allow grain legumes to better cope with drought stress are summarized. It is suggested that there are considerable gains to be made in increasing yield and yield stability in environments characterized by terminal drought stress by further exploiting drought escape, by shortening crop duration. Many traits conferring dehydration avoidance and dehydration tolerance are available, but integrated traits, expressing at a higher level of organization, are suggested to be more useful in crop improvement programs. Possible genetic improvement strategies are outlined, ranging from empirical selection for yield in droughted environments to a physiological genetic approach. It is suggested that in view of recent advances in understanding drought resistance mechanisms, the latter strategy is becoming more feasible. It is concluded that use of this recently derived knowledge in a systematic manner can lead to significant gains in yield and yield stability of the world's major grain legumes, as they are mainly grown (and will continue to be grown) under rain-fed conditions.     

NM+: software implementing parentage-based models for estimating gene dispersal and mating patterns in plants

NM+ is computer software designed for making inferences on plant gene dispersal and mating patterns by modelling parentage probabilities of offspring based on the spatially explicit neighbourhood model. NM+ requires a sample of mapped and genotyped candidate parents and offspring; however, offspring may optionally be assigned to single maternal parents (forming so-called half-sib progeny arrays). Using maximum likelihood, NM+ estimates a number of parameters, including proportions of offspring due to self-fertilization, pollen immigration from outside of a defined study site, parameters of pollen (and/or seed) dispersal kernels (exponential-power, Weibull, geometric or 2Dt) and selection gradients relating covariates (phenotypic traits) with male (and/or female) reproductive success. NM+ allows for missing data both in parents and in offspring. It accounts for null alleles and their frequencies can optionally be considered as estimable parameters. Data files are formatted in a table-like structure so they can be easily prepared in a spreadsheet software. By default NM+ is for studying plant populations, however, it can be used for any organism as long as data requirements and model assumptions are met. NM+ runs under Windows, but it can be launched under Linux using WINE emulator. NM+ can be downloaded free of charge from http://www.genetyka.ukw.edu.pl/index_pliki/software.htm.     

Assessing three methods for identification of desirable genotypes in white cabbage (Brassica oleracea L. var. capitata)

Summary A desirable genotype is a genotype performing well in a chosen set of environments. Three methods for identification of desirable genotypes were assessed in two cabbage data sets: regression analysis, multidimensional scaling of dissimilarity matrices, and biplot of deviation matrices. Using the regression approach is not recommended mainly for two reasons: (1) it is difficult to identify the desirable genotypes since one has to unify three parameters into one decision; (2) the regression method failed to identify the most desirable genotypes in one of the data sets. Multidimensional scaling and the biplot method were in accordance with each other and with the mean tables when different subsets where compared. Consequently, they were considered more adequate for identifying desirable genotypes. In cases where rank 2 approximation of the analysed matrix was justified, the biplot revealed more information in one display and was, therefore, considered particularly useful in plant breeding for larger target areas.     

An alternative approach to multivariate selection in plant breeding where genotypes are evaluated at many locations

Summary A new approach to genotypic selection in a plant breeding programme where the genotypes under assessment are grown in a number of environments is examined. It is assumed that these environments are a random sub-set of all possible environments where the genotypes are likely to be grown. It involves estimating the probability that each genotype will, if grown at any location, exceed predefined target values for one or more characters. The multi-normal probabilities are estimated from the genotype means and environmental variance of each variate. Where more than a single variate is to be considered, the correlation coefficients between variates are also used in the estimation. It was found that the coefficient obtain by correlating the predicted proportion of locations that genotypes would exceed the set target values, with the observed proportion of locations in a different year, were consistently higher than similar coefficients between observed proportions in different seasons. The latter were high enough to conclude that the approach would be of use in practise. Such a method may therefore be used to identify genotypes which have a high probability of being suitable over a range of locations.     

Shrubs, granivores and annual plant community stability in an arid ecosystem

Compensatory population dynamics among species stabilise aggregate community variables. Inter-specific competition is thought to be stabilising as it promotes asynchrony among populations. However, we know little about other inter-specific interactions, such as facilitation and granivory. Such interactions are also likely to influence population synchrony and community stability, especially in harsh environments where they are thought to have relatively strong effects in plant communities. We use a manipulative experiment to test the effects of granivores (harvester ants) and nurse plants (dwarf shrubs) on annual plant community dynamics in the Negev desert, Israel. We present evidence for weak and inconsistent effects of harvester ants on plant abundance and on population and community stability. By contrast, we show that annual communities under shrubs were more species rich, had higher plant density and were temporally less variable than communities in the inter-shrub matrix. Species richness and plant abundance were also more resistant to drought in the shrub under-storey compared with the inter-shrub matrix, although population dynamics in both patch types were synchronised. Hence, we show that inter-specific interactions other than competition affect community stability, and that hypothesised mechanisms linking compensatory dynamics and community stability may not operate to the same extent in arid plant communities.     

Critical analysis of biophysicochemical parameters for qualitative improvement of phytogenic nanoparticles

Conventional chemical approaches for synthesizing nanoparticles (NPs) may restrict their applicability as they are not eco-friendly, energetically efficient and often involve toxic reducing/capping agents; but phytonanotechnology enabled the synthesis of safe, inexpensive, highly biocompatible NPs. In this regard, thorough understanding of green components and the modulatory effects of different reaction conditions on the physicochemical parameters of green synthesized NPs would be a prerequisite, which is not depicted elsewhere. This review critically analyzes the relevant reaction conditions from their mechanistic viewpoints in plant-based synthesis of NPs arising fundamental issues which need to be determined carefully. The size, stability and surface chemistry of phytogenic NPs may be fabricated as a function of multiple interconnected reaction parameters and the plant species used. The therapeutic potential of phytogenic NPs may depend on the plant species used; and so the meticulous understanding of physicochemical parameters and the family wise shorting of elite plant species may potentially benefit the theranostic future of plant-based NPs.     

Potential gain from selection for yield stability in two grain sorghum populations

Summary Maximum yield under highly unpredictable environments should be associated with selection of genotypes with superior performance across good and poor environments. Several stability parameters have been proposed to identify superior genotypes over a wide range of environments. None of these has been used as selection criteria, however, because of their low heritability. The objective of the study presented here was to compare the relative efficiency of predicted gain from indirect selection among three stability parameters: the coefficient of regression (b), deviation from regression (S _d ² ), and principal components scores (PC) from the AMMI model; two indices including mean yield and a stability parameter; and three indices involving yield at the best, the worst, and an intermediate environment. Two hundred S₁ families from each of two sorghum populations (TP24D and KP9B) were evaluated at four dry-land evironments over 2 years. The low heritability estimates and the low genetic correlation between the various stability parameters and mean yield resulted in their low relative efficiency as indirect selection criteria for high yield across environments. However, when the parameters were combined with mean yield over all to create indices, the relative efficiency increased for all the environments. In terms of resource allocation, these indices were not as efficient as mean productivity, rank summation, and selection index that involved fewer environments in their estimation.Contribution no. 9820 of Agricultural Research Division, Univ. of Neb. and no. 92-203-J of Kansas Exp. Stn.     

Characteristic metabolism of free amino acids in cetacean plasma: cluster analysis and comparison with mice

From an evolutionary perspective, the ancestors of cetaceans first lived in terrestrial environments prior to adapting to aquatic environments. Whereas anatomical and morphological adaptations to aquatic environments have been well studied, few studies have focused on physiological changes. We focused on plasma amino acid concentrations (aminograms) since they show distinct patterns under various physiological conditions. Plasma and urine aminograms were obtained from bottlenose dolphins, pacific white-sided dolphins, Risso's dolphins, false-killer whales and C57BL/6J and ICR mice. Hierarchical cluster analyses were employed to uncover a multitude of amino acid relationships among different species, which can help us understand the complex interrelations comprising metabolic adaptations. The cetacean aminograms formed a cluster that was markedly distinguishable from the mouse cluster, indicating that cetaceans and terrestrial mammals have quite different metabolic machinery for amino acids. Levels of carnosine and 3-methylhistidine, both of which are antioxidants, were substantially higher in cetaceans. Urea was markedly elevated in cetaceans, whereas the level of urea cycle-related amino acids was lower. Because diving mammals must cope with high rates of reactive oxygen species generation due to alterations in apnea/reoxygenation and ischemia-reperfusion processes, high concentrations of antioxidative amino acids are advantageous. Moreover, shifting the set point of urea cycle may be an adaptation used for body water conservation in the hyperosmotic sea water environment, because urea functions as a major blood osmolyte. Furthermore, since dolphins are kept in many aquariums for observation, the evaluation of these aminograms may provide useful diagnostic indices for the assessment of cetacean health in artificial environments in the future.     

Sensitivity of Resistance to Net Blotch in Barley

The aim of this study was to demonstrate various methods of analysing terminal net blotch, Pyrenophora teres Drechs. f. teres Smedeg., severity data from 15 spring barleys, Hordeum vulgare L., grown in Finnish official variety trials in five environments. The analyses have been developed and used principally by plant breeders for assessing crop yield, but lend themselves to use by plant pathologists. Pyrenophora teres is the major barley phytopathogen in Finland and improved resistance to it is sought. Joint regression analysis (JRA) and an additive main effects and multiplicative interaction (AMMI) model were used to investigate the data. Statistically significant genotype by environment (GE) interaction for resistance was indicated, and this included qualitative (crossover) interactions among genotypes over environments. A stable, non-sensitive, response to net blotch over environments, combined with a low mean score for terminal severity of the disease characterized the six-row barley 'Thule' which showed statistically significant crossover interaction only with 'Tyra'. 'Kustaa' exhibited the lowest mean terminal net blotch severity, but was relatively sensitive to net blotch. 'Arve' exhibited severe terminal net blotch in all environments, was relatively sensitive to environment and exhibited no crossover interaction with other genotypes. AMMI analysis appeared to represent a useful method for analysing these disease severity data, facilitating the selection of useful sources of resistance. Plots of AMMI-adjusted mean net blotch severities against first principal component axis (PCA) scores were informative for differentiating genotype response over environments, and are therefore potentially useful to plant pathologists and barley breeders seeking to gauge and subsequently improve the resistance status of barley to net blotch.     

Spatial dynamics of an invasive bird species assessed using robust design occupancy analysis: the case of the Eurasian collared dove (Streptopelia decaocto) in France

Aim The study of the spatial dynamics of invasive species is a key issue in invasion ecology. While mathematical models are useful for predicting the extent of population expansions, they are not suitable for measuring and characterizing spatial patterns of invasion unless the probability of detection is homogeneous across the distribution range. Here, we apply recently developed statistical approaches incorporating detection uncertainty to characterize the spatial dynamics of an invasive bird species, the Eurasian collared dove (Streptopelia decaocto). Location France. Methods Data on presence/absence of doves were recorded from 1996 to 2004 over 1045 grid cells (28 × 20 km) covering the entire country. Each grid cell included five point counts spaced along a route, which was visited twice a year, allowing for an estimation of detection probability. Each route was assigned to one of six geographical regions. We used robust design occupancy analysis to assess spatial and temporal variation in parameters related to the spatial dynamics of the species. These parameters included occupancy rate, colonization and local extinction probabilities. Our inference approach was based on the selection of the most parsimonious model among competitive models parametrized with conditional probabilities. Results The probability of detecting the presence of doves on a given route was high. However, we found evidence to incorporate detection uncertainty in inference processes about spatial dynamics, since detection probability was neither perfect (i.e. it was < 1), nor constant over space and time. Results showed a clear positive trend in occupancy rate over the study period, increasing from 55% in 1996 to 76% in 2004. In addition, occupancy rate differed among regions (range: 37–79%) and further analysis showed that colonization probability by region was positively related to occupancy rate. Finally, local extinction probability was lower than colonization probability and showed a tendency to decrease over the study period. Main conclusions Our results emphasize the importance of estimating detection probabilities in order to draw proper inferences about the spatial and temporal dynamics of the invasion pattern of the collared dove. In contrast to the perceived spatial dynamics from national atlas surveys, we provide evidence that the range of this species is currently increasing in France. Other results, such as regional specificity in colonization probabilities and time variation in local extinction are consistent with expectations from invasion and metapopulation theory.     

Vertebrate-dispersed species in a fire-prone environment

Abstract It is hypothesized that plant species that produce vertebrate-dispersed seeds (fleshy fruits and brightly coloured arillate seeds) would not be common in fire-prone vegetation because seeds are deposited on the soil surface and are unlikely to survive fires. They have not previously been known to have any means of burial that would enable them to await the next fire as a buried soil seed-bank. We studied vertebrate-dispersed species in fire-prone sclerophyll vegetation to look at mechanisms used by vertebrate-dispersed plants for persisting in these environments. Seeds do not survive heating to 150°C, although species from fire-prone environments are more likely to tolerate moderate heating (80°C) without affecting viability than vertebrate-dispersed species from environments where fire is rare. Most vertebrate-dispersed species have the capacity to regenerate vegetatively, although they are not more likely to have this strategy than ant-dispersed species. Finally, ants do take vertebrate-dispersed seeds and fruits (particularly small ones) indicating the potential for the formation of a soil seed-bank. Some species only persist in fire-prone environments by recolonizing from unburnt areas.     

Mapping QTLs for Plant Phenology and Production Traits Using Indica Rice (Oryza sativa L.) Lines Adapted to Rainfed Environment

Drought is a major abiotic stress limiting rice production and yield stability in rainfed ecosystems. Identifying quantitative trait loci (QTL) for rice yield and yield components under water limited environments will help to develop drought resilient cultivars using marker assisted breeding (MAB) strategy. A total of 232 recombinant inbred lines of IR62266/Norungan were used to map QTLs for plant phenology and production traits under rainfed condition in target population of environments. A total of 79 QTLs for plant phenology and production traits with phenotypic variation ranging from 4.4 to 72.8% were detected under non-stress and drought stress conditions across two locations. Consistent QTLs for phenology and production traits were detected across experiments and water regimes. The QTL region, RM204-RM197-RM217 on chromosome 6 was linked to days to 50% flowering and grain yield per plant under both rainfed and irrigated conditions. The same genomic region, RM585-RM204-RM197 was also linked to harvest index under rainfed condition with positive alleles from Norungan, a local landrace. QTLs for plant production and drought resistance traits co-located near RM585-RM204-RM197-RM217 region on chromosome 6 in several rice genotypes. Thus with further fine mapping, this region may be useful as a candidate QTL for MAB, map-based cloning of genes and functional genomics studies for rainfed rice improvement.     

Deep insights into the plant proteome by pretreatment with combinatorial hexapeptide ligand libraries

Proteome analyses suffer from the large complexity of even small proteomes. Additionally, in many protein samples a few highly abundant proteins are hindering detailed proteomic studies, since they mask low abundant proteins. Recently, a new technology has emerged, which reduces dynamic range of protein concentrations within a given sample using combinatorial hexapeptide ligand libraries (CPLLs). This technique has been widely used in the microbial, animal and human fields and is now going to enter plant research. It can be a useful tool for fractionation of protein samples and might help to get a deeper insight into specific plant proteomes. In this review we describe the CPLL protein fractionation, summarize its possible applications in the plant field and discuss the limitations of this method.