Response to zinc deficiency of two rice lines with contrasting tolerance is determined by root growth maintenance and organic acid exudation rates, and not by zinc-transporter activity

Zinc (Zn)-deficient soils constrain rice (Oryza sativa) production and cause Zn malnutrition. The identification of Zn-deficiency-tolerant rice lines indicates that breeding might overcome these constraints. Here, we seek to identify processes underlying Zn-deficiency tolerance in rice at the physiological and transcriptional levels. A Zn-deficiency-tolerant line RIL46 acquires Zn more efficiently and produces more biomass than its nontolerant maternal line (IR74) at low Zn(ext) under field conditions. We tested if this was the result of increased expression of Zn(2+) transporters; increased root exudation of deoxymugineic acid (DMA) or low-molecular-weight organic acids (LMWOAs); and/or increased root production. Experiments were performed in field and controlled environment conditions. There was little genotypic variation in transcript abundance of Zn-responsive root Zn(2+)-transporters between the RIL46 and IR74. However, root exudation of DMA and LMWOA was greater in RIL46, coinciding with increased root expression of putative ligand-efflux genes. Adventitious root production was maintained in RIL46 at low Zn(ext), correlating with altered expression of root-specific auxin-responsive genes. Zinc-deficiency tolerance in RIL46 is most likely the result of maintenance of root growth, increased efflux of Zn ligands, and increased uptake of Zn-ligand complexes at low Zn(ext); these traits are potential breeding targets.

Rapid quality assessment of wheat cultivars registered in Poland using the 2-g mixograph and multivariate statistical analysis

Baking and 2-g mixograph analyses were performed for 55 cultivars (19 spring and 36 winter wheat) from various quality classes from the 2002 harvest in Poland. An instrumented 2-g direct-drive mixograph was used to study the mixing characteristics of the wheat cultivars. A number of parameters were extracted automatically from each mixograph trace and correlated with baking volume and flour quality parameters (protein content and high molecular weight glutenin subunit [HMW-GS] composition by SDS-PAGE) using multiple linear regression statistical analysis. Principal component analysis of the mixograph data discriminated between four flour quality classes, and predictions of baking volume were obtained using several selected mixograph parameters, chosen using a best subsets regression routine, giving R-2 values of 0.862-0.866. In particular, three new spring wheat strains (CHD 502a-c) recently registered in Poland were highly discriminated and predicted to give high baking volume on the basis of two mixograph parameters: peak bandwidth and 10-min bandwidth.