Dataset Information

A new method for evaluation of the resistance to rice kernel cracking based on moisture absorption in brown rice under controlled conditions.

ABSTRACT: We developed and evaluated the effectiveness of a new method to detect differences among rice cultivars in their resistance to kernel cracking. The method induces kernel cracking under laboratory controlled condition by moisture absorption to brown rice. The optimal moisture absorption conditions were determined using two japonica cultivars, 'Nipponbare' as a cracking-resistant cultivar and 'Yamahikari' as a cracking-susceptible cultivar: 12% initial moisture content of the brown rice, a temperature of 25°C, a duration of 5 h, and only a single absorption treatment. We then evaluated the effectiveness of these conditions using 12 japonica cultivars. The proportion of cracked kernels was significantly correlated with the mean 10-day maximum temperature after heading. In addition, the correlation between the proportions of cracked kernels in the 2 years of the study was higher than that for values obtained using the traditional late harvest method. The new moisture absorption method could stably evaluate the resistance to kernel cracking, and will help breeders to develop future cultivars with less cracking of the kernels.

SUBMITTER: Hayashi T

PROVIDER: S-EPMC4671698 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A new method for evaluation of the resistance to rice kernel cracking based on moisture absorption in brown rice under controlled conditions.

Hayashi Takeshi T Kobayashi Asako A Tomita Katsura K Shimizu Toyohiro T

Breeding science 20151201 5

We developed and evaluated the effectiveness of a new method to detect differences among rice cultivars in their resistance to kernel cracking. The method induces kernel cracking under laboratory controlled condition by moisture absorption to brown rice. The optimal moisture absorption conditions were determined using two japonica cultivars, 'Nipponbare' as a cracking-resistant cultivar and 'Yamahikari' as a cracking-susceptible cultivar: 12% initial moisture content of the brown rice, a tempera ...[more]

PMID: 26719740

Similar Datasets

Project description:IntroductionIn wheat, kernel weight (KW) is a key determinant of grain yield (GY). However, it is often overlooked when improving wheat productivity under climate warming. Moreover, little is known about the complex effects of genetic and climatic factors on KW. Here, we explored the responses of wheat KW to diverse allelic combinations under projected climate warming conditions.MethodsTo focus on KW, we selected a subset of 81 out of 209 wheat varieties with similar GY, biomass, and kernel number (KN) and focused on their thousand-kernel weight (TKW). We genotyped them at eight kompetitive allele-specific polymerase chain reaction markers closely associated with TKW. Subsequently, we calibrated and evaluated the process-based model known as Agricultural Production Systems Simulator (APSIM-Wheat) based on a unique dataset including phenotyping, genotyping, climate, soil physicochemistry, and on-farm management information. We then used the calibrated APSIM-Wheat model to estimate TKW under eight allelic combinations (81 wheat varieties), seven sowing dates, and the shared socioeconomic pathways (SSPs) designated SSP2-4.5 and SSP5-8.5, driven by climate projections from five General Circulation Models (GCMs) BCC-CSM2-MR, CanESM5, EC-Earth3-Veg, MIROC-ES2L, and UKESM1-0-LL.ResultsThe APSIM-Wheat model reliably simulated wheat TKW with a root mean square error (RMSE) of < 3.076 g TK-1 and R2 of > 0.575 (P < 0.001). The analysis of variance based on the simulation output showed that allelic combination, climate scenario, and sowing date extremely significantly affected TKW (P < 0.001). The impact of the interaction allelic combination × climate scenario on TKW was also significant (P < 0.05). Meanwhile, the variety parameters and their relative importance in the APSIM-Wheat model accorded with the expression of the allelic combinations. Under the projected climate scenarios, the favorable allelic combinations (TaCKX-D1b + Hap-7A-1 + Hap-T + Hap-6A-G + Hap-6B-1 + H1g + A1b for SSP2-4.5 and SSP5-8.5) mitigated the negative effects of climate change on TKW.DiscussionThe present study demonstrated that optimizing favorable allelic combinations can help achieve high wheat TKW. The findings of this study clarify the responses of wheat KW to diverse allelic combinations under projected climate change conditions. Additionally, the present study provides theoretical and practical reference for marker-assisted selection of high TKW in wheat breeding.

Dataset Information

A new method for evaluation of the resistance to rice kernel cracking based on moisture absorption in brown rice under controlled conditions.

Publications

A new method for evaluation of the resistance to rice kernel cracking based on moisture absorption in brown rice under controlled conditions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets