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Wheat genotypes were evaluated under multi environment trials for Northern Hills Zone of India to study the adaptability performance. Genotypes HS612, HS507 and HPW430 were of high yield and better adaptability by analytic measures of adaptability based on BLUP values during 2015-16. Two interaction principal components, accounted for 89.9 % of total GxE interaction sum of squares in biplot analysis. HPW428, HS613, VL2020, VL2024 had specific adaptations to Almora and Malan while HS616, HPW423, HPW430, VL2021, HPW426 expressed for Shimla and Khudwani locations. Wheat genotypes HS612, HS507 and HPW430 were cited by analytic measures as per BLUE values. HPW429, HS613, VL2020, VL2024 had specific adaptations to Almora and Malan while HS616, HS618, HPW425, HPW426, HPW430, VL2023, VL2021, HPW426 observed for Shimla and Khudwani. Second year (2017-18) had seen high yield and better adaptability of HS631, HS632, VL2030, VL2025 genotypes as per BLUP values. Biplot analysis expressed specific adaptations of HPW429, HS613, VL2020, VL2024 to Almora and Malan locations. BLUE values based measures showed high yield and better adaptability of HS631, HS632, VL2030, VL2025 genotypes. Biplot analysis while utilizing 79.5 % of total GxE interaction sum of squares exhibited specific adaptations of HPW446, VL907, HS632, VL2025, VL2030 to Almora and Shimla. Stratification of wheat genotypes as per BLUP values was more efficient than that by BLUE. Biplot analysis exhibited more of GxE interactions sum of squares by first two significant principal components based on BLUP as compared to BLUE values.

Wheat improvement programs conduct multi environment trials (MET) for estimation of main of genotypes, environments and genotype x environment interactions (Crespo

Northern hills zone encompasses the hilly terrain of Northern region extending from Jammu & Kashmir to North Eastern States. NHZ comprises J&K (except Jammu and Kathua distt.); Himachal Pradesh (except Una and Paonta Valley); Uttarakhand (except Tarai area); Sikkim, hills of West Bengal and North Eastern states. Advanced wheat genotypes were evaluated in field trials at major locations of the zone during cropping season’s viz. 2015-16 and 2017-18 as details are reflected in tables 1 &2 for ready reference. Randomized block design with three replications were used for research field trials and recommended agronomical practices had followed to harvest good crop. More over yield were further analysed as per recent analytic adaptability measures.

Simple and effective measure for adaptability is based on the relative performance of genetic values (PRVG) across environments. MHVG method (harmonic mean of genetic values) as based on the harmonic mean of the genotypic values considered the yield & stability. The lower the standard deviation of genotypic performance across environments, the greater is the harmonic mean of genotypes. For the use of mixed models, the simultaneous analysis of stability, adaptability and yield based on the harmonic mean of the relative performance of the genotypic values (MHPRVG).

The MHPRVG combines the methods PRVG and MHVG, simultaneously. Consequently, the selection for higher values of the harmonic mean results in selection for both yield and stability (Resende and Duarte, 2007).

VG_{ij} is the genotypic value of the i genotype, in the j environment, expressed as a proportion of the average in this environment. PRVG and MHPRVG values were multiplied by the general mean (GM) to have results in the same magnitude as of the average wheat yield in order to facilitate interpretation (Verardi et al. 2009). Estimation of the variance components were carried out by using residual maximum likelihood (REML) along with estimation/ prediction of the fixed as well as random effects by ASReml-R package. Mohammadi & Amri, 2008 defined geometric adaptability index (GAI) to evaluate the adaptability of genotypes as GAI =

First year (2015-16) based on BLUP

Average yield of genotypes as per BLUP values identified HS612, HS507 and HPW430 as of high yield with better adaptations while HS615 & UP2952 expressed low yield. Harmonic mean ranked genotypes as HS612, HPW430 and VL2024 for better adaptation at the same time pointed out suitability of HS615 & HS617 for specific adaptations (

Agro climatics zones for wheat cultivation in country

First two highly significant Interaction Principal Components expressed stable yield of HS618, UP2953, HS613, HPW431 and HPW428 genotypes in Biplot analysis. HS612, VL2019 and HS615 would be good for specific adaptations. Two interaction principal components, accounted for 89.9 % of total G×E interaction sum of squares (

Biplot analysis of genotypes vis-ŕ-vis environments based on BLUP (2015-16)

Mean yield of wheat genotypes based on BLUE values selected HS612, HPW430 and HS507as of high yield with better adaptations while HS615 & UP2952 achieved low yield. Ranking of genotypes based on harmonic mean selected HS612, HPW430 and VL2024 as better adapted genotypes along with suitability of HS615 & HS617 for specific adaptations (

Parentage details and environmental conditions (2015-16)

Parentage details and environmental conditions (2016-17)

Adaptability measures of wheat genotypes as per BLUP(2015-16)

Rank of wheat genotypes as per adaptability measures based on BLUP (2015-16)

Two interaction principal components, accounted for 87.9 % of total GxE interaction sum of squares in biplot analysis (

HPW447, HS631, HS632, VL2030 wheat genotypes were selected by average yield based on the BLUP values for possessing high yield with better adaptation and HS635, HS637 & VL2028 for low yield & specific adaptation. Harmonic mean identified HS631, HS632, VL2030, VL2025 for better adaptation along with suitability of HS635, VL2028 & HPW444 for specific adaptations (

Biplot analysis of genotypes vis-ŕ-vis environments based on BLUE (2015-16)

Total of 87.8 % of G×E interaction sum of squares was explained by first two significant interaction principal components in biplot analysis (

Adaptability measures of wheat genotypes as per BLUE(2015-16)

Rank of wheat genotypes as per adaptability measures based on BLUE(2015-16)

Biplot analysis of genotypes vis-à-vis environments based on BLUP (2016-17)

Wheat genotypes HS631, HPW447, HS632, VL2030 were identified by mean yield as per their BLUE values for high yield and better adaptation at the same time low yield & specific adaptation of HS635, HS637 & HPW444. Harmonic mean of genotypes values selected HS631, HS632, VL2030, VL2025 for better adaptation and specific adaptations of HS635, HPW444, VL2028 (

First two significant interaction principal components expressed 79.5 % of total G×E interaction sum of squares in biplot analysis (

Biplot analysis of genotypes vis-ŕ-vis environments based on BLUE (2016-17)

Adaptability measures of wheat genotypes as per BLUP(2016-17)

Ranks of wheat genotypes as per adaptability measures based on BLUP (2016-17)

Adaptability measures of wheat genotypes as per BLUE(2016-17)

Rank of wheat genotypes as per adaptability measures based on BLUE (2016-17)

Classification of wheat genotypes as per their adaptability by analytic measures based on BLUP by exploiting REML procedure was more efficient than that by BLUE (Smith and Cullis 2018). Biplot analysis showed that more of G×E interactions sum of squares was explained by first two principal components as compared to accounted by BLUE. There was no overall difference between analytic measures as far as adaptability of genotypes is concerned either based on Harmonic or Geometric means as compared to usual mean yield of genotypes. Genotype classifications by BLUP/REML were superior to that of by BLUE for both years, despite the presence of cross over genotype × environment interactions (Kleinknecht

Guidance and financial support extended by Dr RP Singh, CIMMYT Mexico acknowledged by the authors. Efforts of staff, working at various coordinated centers of wheat, are highly appreciated for field evaluation wheat genotypes.