A simple procedure for yield component analysis

Summary This paper introduces a simple method of analysing yield components. It allows quantification of the contribution of each component to the variability of final yield. The method is based on log-transforms of measurements of the component traits. Applications in heterosis breeding and stability analysis are discussed. The method is compared to other procedures of yield component analysis.     

Segregation of non‐target‐site resistance to herbicides in multiple‐resistant Alopecurus myosuroides plants

Non‐target‐site resistance (NTSR) comprises a set of mechanisms conferring resistance to multiple modes of action. Investigation of the number of loci involved in NTSR will aid in the understanding of these resistance mechanisms. Therefore, six different multiple herbicide‐resistant Alopecurus myosuroides plants with different herbicide history were crossed in two generations with a susceptible wild type. Seeds from the backcrossing generation were studied for their segregation rate for resistance to five herbicides with four different modes of action (HRAC groups C₂, A, B and K₃). Taking into account that NTSR is a set of quantitative traits, the numbers of loci controlling NTSR were estimated using a normal mixture model fitted by the NLMIXED procedure of SAS. Each herbicide was controlled by a different number of loci comparing the six plants. In most of the cases, chlorotoluron resistance was controlled by one locus, whereas resistance to fenoxaprop‐P‐ethyl needed one or two loci. Resistance to pinoxaden was in all plants conferred by two loci. Cross‐resistance of fenoxaprop‐P‐ethyl and pinoxaden was found in all backcrossings, indicating that at least one of the two loci is responsible for both resistances. Resistance to mesosulfuron + iodosulfuron was conferred by a minimum of two loci. Results indicated that a minimum of five different loci can be involved in a multiple NTSR plant. Furthermore, the plant‐specific accumulation of NTSR loci was demonstrated. Such behaviour should be taken into account when evaluating the development and further spread of herbicide resistance.     

Rank correlation among parametric and nonparametric measures of phenotypic stability

Summary There is an increasing number of stability parameters for genotypes grown in different environments. It is therefore useful to study the statistical relations between these parameters. One approach is the calculation of rank correlations between different stability parameters in empirical data sets. In the data analysed there are high rank correlations between ecovalence W_i, deviation mean square s² _di, the nonparametric measures S_i ⁽¹⁾, S_i ⁽²⁾, and two new measures R_i and L_i as well as between environmental variance S² _xi and regression coefficient b_i. The results suggest that S_i ⁽¹⁾, S_i ⁽²⁾, L_i, and R_i can be used as alternatives to W_i and the stability variance ² _i. This may be worthwhile, if certain statistical assumptions do not hold, particularly if significance testing is needed.     

Responses of different arabica coffee (Coffea arabica L.) clones to varied environmental conditions

Different improved coffee arabica crosseshaving resistance to coffee berry diseaseand leaf rust, plus a standard cultivar,were grown under a range of environmentalconditions in a series of field trials inKenya. The effects of location and year ofproduction and their interactions with theclones were determined for berry yield.These data were used to estimate andcompare methods of analysis of GEI. An AMMImodel, joint regression model and ANOVAwith repeated measurements were used toinvestigate these interactions. The resultsindicated the relative effects of theclones and the environmental conditions,with Meru being the location where therewas greatest discrimination between theclones, probably because it was bettersuited for coffee. Clones,environments and joint regressions combinedaccounted for 31.20% of the interaction,leaving a residual of 68.80%. Significantresidual mean squares showed therelationship between clones andenvironments not to be strictly linear,thus indicating that regression analysisdid not always provide good estimates ofindividual clonal performance acrossenvironments. High correlations wereobtained between mean yield and regressioncoefficients and between ecovalence andmean square deviations as well as thecoefficient of determination. Resultsshowed that the improved clones surpassedthe standard cultivar both in terms ofyield and stability.Different analyses of the various aspectsof genotype response enabled the 21 clonesto be classified into different similaritygroups based on their performance andphenotypic stability as measured by variousstability parameters and the use of biplotsfrom the AMMI analysis.     

Analysis of Unbalanced Data by Mixed Linear Models Using the mixed Procedure of the SAS System

Unbalanced data are a common problem in plant research based on designed experiments. Such data are often conveniently analysed using linear mixed models. Recent developments in mixed model theory have been implemented in major packages. This paper describes the use of the mixed procedure of the SAS System for the analysis of designed experiments. Special emphasis is given to the specification of options as depending on the assumed mixed model and on the unbalancedness in the data. In addition, we consider a compact representation of multiple comparisons for unbalanced data (letter display). Two small data sets are used to exemplify the methods.     

Mixed modelling for QTL × environment interaction analysis

Phenotypic data for quantitative trait loci (QTL) mapping studies are typically generated at multiple environments in order to broaden the inference space. Many aspects of the usually complex design call for a mixed modelling approach taking into account various sources of variation, e.g., incomplete blocks, a spatial error structure, genetic correlations due to the pedigree, and random environmental effects, including QTL × E interaction. Perhaps the most important source of random variation is the genetic correlation across environment, which arises when the same set of lines is tested in each environment. This correlation is likely to be positive, and ignoring it will lead to an increased rate of false positives. In this paper, we present a mixed modelling framework for QTL mapping based on complex data from multiple environments. Our main focus is on an appropriate modelling for the non-QTL part. The methodology will be illustrated using a barley data set from a BC₂F_2:5 advanced backcross trial. This revised version was published online in July 2006 with corrections to the Cover Date.     

南极半岛海洋气候区的土壤Ⅲ.冻-融作用与水分状况

自由水活动在南极海洋性气候区土壤形成与演化过程中发挥极为重要的作用。本文对土壤自由水的来源、冻-融作用、永冻层和活动层动态以及自由水参与下的物质迁移过程等几个方面进行了论述,讨论了上述不同过程的影响因素以及土壤发生学意义,指出以土壤水形态转化和自由水活动为基础的土壤过程具有显著的微域性特点,是决定本区土壤发生类型与分布模式的重要因素之一。     

Modelling of a recording scheme for market-oriented smallholder pig producers in Northwest Vietnam

Village breeding programmes are being developed by an integrated long-term project for smallholders in Northwest Vietnam to improve pig production in different production systems. In total, 120 smallholders with 169 sows in 5 of the 9 project villages were approached in single person interviews, using a structured questionnaire. Frequency analysis of data on breeding management and ranking of smallholders' trait preferences and selection criteria used for pigs were performed with SAS 9.1, using the FREQ procedure. Survey results indicate that both improved local breeds and exotic genotypes should be incorporated in future village breeding programmes for market-oriented smallholder pig production, improving the reproductive and growth performance as well as the carcass quality. In a next step, a model reflecting the status quo at farms with market-oriented pig production was developed integrating data from farmers' survey and information from the project's current recording scheme. A deterministic approach was used to assess the profitability and genetic merit of the current recording scheme. Modelling results show that the current recording scheme is unprofitable (− 33.90 € sow^− 1). As continued success of village breeding programmes depends on the profitability of breeding measures, the long-term sustainability of the current recording scheme seems unlikely. Genetic gains are achieved in production and carcass quality traits, while a small reduction in reproduction traits can be observed. In a last step, possible effects of increased pig performances on the profitability and genetic merit of the current recording scheme were evaluated. Effects of increased pig performances on the genetic and economic success of the recording scheme are generally limited. Further model calculations are necessary for finding possibilities to improve smallholder pig breeding in a profitable way.     

Analysis of series of variety trials with perennial crops

Field trials with perennial crops give rise to repeated measurements taken on the same plot on several occasions. It is important to account for serial correlation among repeated measurements in such trials. This study illustrates the use of mixed models for this purpose. We consider the analysis of trials conducted at several locations and the combination of trials with different starting years. A key issue in the analysis is the distinction between effects of calendar years, which are associated with external environmental variation, and harvest years, which represent internal yield formation processes of the perennial crop. Two methods of two‐stage analysis are compared with single‐stage analysis. It is shown that results of two‐stage analysis are very similar to those of single‐stage analysis, if serial correlation is properly taken into account. Program code for the MIXED procedure of the SAS system is given in an Appendix S1 for all considered cases.