Hiroyuki Sato

In this paper, we characterized the Wx-mq gene for low amylose content in a rice variety, Milky Queen, at the molecular level. The Wx-mq gene was cloned by RT-PCR, and a nearly full-length cDNA sequence of the gene was determined. Sequence comparison between the Wx-mq gene and the wild type allele (Wx-b), cloned from cv. Koshihikari, revealed that two base changes existed within the coding region; a G to A base change at nucleotide position 497 and a T to C base change at nucleotide position 595

The rice line WSS2 which was derived from the Vietnamese indica variety Tetep, displays a high partial resistance to sheath blight. Quantitative trait locus (QTL) analysis of the resistance using simple sequence repeat (SSR) and sequence-tagged site (STS) markers was conducted in a BC1F1 population derived from the cross Hinohikari/WSS2//Hinohikari. Sheath blight resistance in this population and its cross-parents was studied using syringe inoculation. Two QTLs for sheath blight resistance (qSB-

In recent years, stochastic variance reduction algorithms have attracted considerable attention for minimizing the average of a large but finite number of loss functions. This paper proposes a novel Riemannian extension of the Euclidean stochastic variance reduced gradient (R-SVRG) algorithm to a manifold search space. The key challenges of averaging, adding, and subtracting multiple gradients are addressed with retraction and vector transport. For the proposed algorithm, we present a global con

Abstract We formulate and solve a discrete‐time path‐optimization problem where a single searcher, operating in a discretized three‐dimensional airspace, looks for a moving target in a finite set of cells. The searcher is constrained by maximum limits on the consumption of one or more resources such as time, fuel, and risk along any path. We develop a specialized branch‐and‐bound algorithm for this problem that uses several network reduction procedures as well as a new bounding technique based o

In rice (Oryza sativa L.), damage from diseases such as brown spot, caused by Bipolaris oryzae, and bacterial seedling rot and bacterial grain rot, caused by Burkholderia glumae, has increased under global warming because the optimal temperature ranges for growth of these pathogens are relatively high (around 30 °C). Therefore, the need for cultivars carrying genes for resistance to these diseases is increasing to ensure sustainable rice production. In contrast to the situation for other importa

The problem of the singular value decomposition of a matrix can be brought into an optimization problem on the product of two Stiefel manifolds of different sizes. The steepest descent, the conjugate gradient, and Newton's methods for the problem are developed and applied with several numerical experiments. These algorithms do not need the preconditioning that is inevitable in the usual singular value decomposition algorithm. The present Newton's method can serve to make more accurate the singul

Brown spot is a devastating rice disease. Quantitative resistance has been observed in local varieties (e.g., 'Tadukan'), but no economically useful resistant variety has been bred. Using quantitative trait locus (QTL) analysis of recombinant inbred lines (RILs) from 'Tadukan' (resistant) × 'Hinohikari' (susceptible), we previously found three QTLs (qBS2, qBS9, and qBS11) that conferred resistance in seedlings in a greenhouse. To confirm their effect, the parents and later generations of RILs we

In Arabidopsis, FLOWERING LOCUS T (FT) and TERMINAL FLOWER 1 (TFL1) are known to control growth habit of determinate or indeterminate type. In cucumber (Cucumis sativus L.), any FT or TFL1 homolog is expected to be the candidate for the gene controlling the growth habit. Most cucumber cultivars show indeterminate type of growth habits. For more effective breeding, it is necessary to develop determinate type cultivars. In this study, we isolated one FT and five TFL1 homologs in cucumber. On these

In recent years, stochastic variance reduction algorithms have attracted considerable attention for minimizing the average of a large but finite number of loss functions. This paper proposes a novel Riemannian extension of the Euclidean stochastic variance reduced gradient (R-SVRG) algorithm to a manifold search space. The key challenges of averaging, adding, and subtracting multiple gradients are addressed with retraction and vector transport. For the proposed algorithm, we present a global con