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Recent efforts to engineer C4 photosynthetic traits into C3 plants such as rice demand an understanding of the genetic elements that enable C4 plants to outperform C3 plants. As a part of the C4 Rice Consortium's efforts to identify genes needed to support C4 photosynthesis, EMS mutagenized sorghum populations were generated and screened to identify genes that cause a loss of C4 function. Stable carbon isotope ratio (δ13C) of leaf dry matter has been used to distinguishspecies with C3 and C4 photosynthetic pathways. Here, we report the identification of a sorghum (Sorghum bicolor) mutant with a low δ13C characteristic. A mutant (named Mut33) with a pale phenotype and stunted growth was identified from an EMS treated sorghum M2 population. The stable carbon isotope analysis of the mutants showed a decrease of 13C uptake capacity. The noise of random mutation was reduced by crossing the mutant and its wildtype (WT). The back-cross (BC1F1) progenies were like the WT parent in terms of 13C values and plant phenotypes. All the BC1F2 plants with low δ13C died before they produced their 6th leaf. Gas exchange measurements of the low δ13C sorghum mutants showed a higher CO2 compensation point (25.24 μmol CO2.mol-1air) and the maximum rate of photosynthesis was less than 5μmol.m-2.s-1. To identify the genetic determinant of this trait, four DNA pools were isolated; two each from normal and low δ13C BC1F2 mutant plants. These were sequenced using an Illumina platform. Comparison of allele frequency of the single nucleotide polymorphisms (SNPs) between the pools with contrasting phenotype showed that a locus in Chromosome 10 between 57,941,104 and 59,985,708 bps had an allele frequency of 1. There were 211 mutations and 37 genes in the locus, out of which mutations in 9 genes showed non-synonymous changes. This finding is expected to contribute to future research on the identification of the causal factor differentiating C4 from C3 species that can be used in the transformation of C3 to C4 plants.

Tillering plays an important role in determining rice grain yield. Several models have been developed to predict tiller production in irrigated rice. In this paper we tested three models using data drawn from a wide range of plant densities and N inputs in two field experiments conducted at the International Rice Research Institute, Philippines during the 1997 and 1998 dry seasons. Two rice cultivars (IR64 and IR72) were used in the experiments. Plant samples were taken at intervals to determine number of tillers, leaf area index (LAI), biomass, relative growth rate (RGR) and leaf N concentration. The models were parameterized using an iteration procedure of the simplex method. Previous models (TIL and SINK) using the original values of parameters for IR64 failed to predict the number of tillers of IR64 in 1997. However, when re-parameterized, both models described the 1997 data well for both cultivars. The two models also predicted fairly well the number of tillers of different transplanting spacing and N input treatments of IR72 in 1998 using IR72 parameters derived from the 1997 experiment. A simple RGR model was comparable with the TIL and SINK models in descriptive and predictive ability. It appears that all three models could be used for predicting tiller production of irrigated rice.