Evaluation of Agronomic Traits for Yield and Yield Components in Wheat Genotypes With Respect to Planting Dates

Abstract

Fourteen genotypes including two checks varieties were evaluated for agronomic traits and their adaptability study on two different sowing dates at the experimental farm of Nuclear Institute for Food and Agriculture, Tarnab, Peshawar, Pakistan. The combined analysis of variance showed that there were significant variations among genotypes, dates of sowing and their interaction. Based on regression coefficient (bi) and mean square deviation from linear regression ( 2 ) for the individual genotypes regarding the parameters Viz. plant height, spike length, spikelets spike -1 , number of tillers plant -1 and grain yield (kg) plot -1 under consideration, most of the genotypes responded negatively with respect to all the traits under late planting condition. However, some of the genotypes such as CT-09117, CT-09137, CT-09141 and SRN-09111 revealed stable performance with respect to the yield assorted traits. They have been recommended for the late planting conditions where sowing is delayed due to some unavoidable circumstances than the other elite wheat genotypes. KEYWORDSNormal and late sowing, yield components, environmental effects, Triticum aestivum L.

Mean performance and stability parameters for comparing bread wheat cultivars under different environmental conditions

“…Meanwhile, Giza 168 was relatively better in stress environments because bi was less than one (bi < 1). Similar results were obtained by Al-Otayk (2010) and Khan (2018). According Tai analysis (Table 3 and figure 4), the average stability region included three cultivars (Shandawel1, Giza 168 and Masr 2).…”

A comparison of bread wheat genotypes under various environments using different stability models

“…Meanwhile, fife genotypes namely Lines 5, 17, 18 and Misr 2 were stable in varied environmental conditions but had low spike length when compared with grand mean. Khan et al, 2017 showed that the genotypes CT-09141, SRN-09048 and SRN-09063 are highly stable for spike length under different environments, on the bases of bi values (bi =1) and values nearly equal to zero ( = 0).…”

Estimating the Change of Vegetation Coverage of the Upstream of Minjiang River by Using Remote-Sensing Images

“…The vegetation coverage is generally defined as the fraction or percentage of the vertical projection of the crown area of vegetation on the ground surface in the reference area (Ts et al 1998, Gitelson et al 2002, Guo et al 2007, Fu and Liu 2017, Fang et al 2017, Khan et al 2018. However, considering the supplementary requirements of remote sensing techniques, vegetation coverage can be defined as the green vegetation area which can be directly detected by the sensor from any view direction (Singh et al 2018, Lu et al 2017.…”