000			02129naa a22003137a 4500
999			_c56919 _d56911
001			56919
003			MX-TxCIM
005			20200810215438.0
008			150721s2015 ii |||||o|||| 00| 0 eng d
040			_aMX-TxCIM
100	1		_9764 _aHuihui Li _gGenetic Resources Program _8CLIH01
245	1	0	_aChapter 17. Biometrical approaches for analysis of phenotypic data of complex traits
260			_aIndia: _bSpringer, _c2015.
520			_aPhenotype (or phenotypic value) is the performance of a trait in interest, which can be observed in the field and then used in estimating the unknown genotypic value (or the phenotypic mean). In this chapter, we introduced statistical approaches to analyze three types of phenotypic observation, i.e., (1) replicated observations of one genotype in one environment, (2) replicated observations of multiple genotypes in one environment, and (3) replicated observations of multiple genotypes in multiple environments. The principle of analysis of variance (ANOVA) was applied on each kind of phenotypic data. From the results of ANOVA, we can further estimate genotypic value, genetic effects, variance components, heritability, etc., which can be further used in genetic studies and breeding applications. In the end, we present a computer tool implemented in the integrated genetic software QTL IciMapping, which includes the biometrical approaches introduced in this chapter and can be readily used in phenotyping complex traits.
536			_aGenetic Resources Program
546			_aText in English
594			_aCLIH01
594			_aINT2542
650		7	_91370 _aPhenotype prediction
650		7	_91384 _aAnalysis of variance
650		7	_91385 _aGenetic variance _2AGROVOC
650		7	_91386 _aHeritability _2AGROVOC
650		7	_91134 _aGenotypes _2AGROVOC
700	1		_9842 _aJiankang Wang _gGenetic Resources Program _8INT2542
773	0		_wu49637 _dIndia: Springer, 2015. _z978-81-322-2225-5 _tPhenomics in crop plants: trends, options and limitations _gp. 249-272
942			_2ddc _cBP _n0