Cotton bolls exhibit the lowest insecticidal efficacy among all organs of Bt cotton, which would ultimately affect the yield formation.  The objective of this study was to investigate the effects of different urea concentrations on the seed Bt protein contents, seed cotton yield and the corresponding protein metabolism mechanism.  The experiments were conducted during 2017–2018 cotton growing seasons.  Two cultivars, Sikang 3 (hybrid, SK3) and Sikang 1 (conventional, SK1), were treated with six urea concentrations and their seed Bt protein contents were compared during boll formation period.  The urea spray concentration had a significant effect on the seed Bt toxin content and seed cotton yield.  Spraying of either 5 or 6% urea led to higher insecticidal protein contents and higher seed cotton yield for both cultivars.  Moreover, the highest amino acid and soluble protein contents, as well as GPT and GOT activities, and lower protease and peptidase activities were observed at the 5 to 6% urea levels.  Significant positive correlations between the seed Bt toxin and amino acid contents, and between the seed Bt toxin content and GPT activities were detected.  The lower boll worm number and hazard boll rate were also observed with the 5 to 6% urea treatments, which may be the reason why nitrogen spraying increased the seed cotton yield.  Therefore, our results suggested that the seed Bt toxin content and insect resistance were impacted markedly by external nitrogen application, and 5 to 6% urea had the greatest effect on insect resistance.

Initial flowering date (IFD) is closely related to mature period of peanut pods.  In present study, a population of recombinant inbred lines (RIL) derived from the cross between Silihong (female parent) and Jinonghei 3 (male parent) was used to map QTLs associated with IFD.  The RIL population and its two parental cultivars were planted in two locations of Hebei Province, China from 2015 to 2018 (eight environments).  Based on a high-density genetic linkage map (including 2 996 SNP and 330 SSR markers) previously constructed in our laboratory, QTLs were analyzed using phenotypic data and the best linear unbiased prediction (BLUP) value of initial flowering date by inclusive composite interval mapping (ICIM) method.  Interaction effects between every two QTLs and between individual QTL and environment were also analyzed.  In cultivated peanut, IFD was affected by genotypic factor and environments simultaneously, and its broad sense heritability (h2) was estimated as 86.8%.  Using the IFD phenotypic data from the eight environments, a total of 19 QTLs for IFD were detected, and the phenotypic variation explained (PVE) by each QTL ranged from 1.15 to 21.82%.  Especially, five of them were also detected by the BLUP value of IFD.  In addition, 12 additive QTLs and 35 pairs of epistatic QTLs (62 loci involved) were identified by the joint analysis of IFD across eight environments.  Three QTLs (qIFDB04.1, qIFDB07.1 and qIFDB08.1) located on chromosome B04, B07 and B08 were identified as main-effect QTL for IFD, which had the most potential to be used in peanut breeding.  This study would be helpful for the early-maturity and adaptability breeding in cultivated peanut.