ABSTRACT''Soft'' and ''hard'' are the two main market classes of wheat (Triticum aestivum L.) and are distinguished by expression of the Hardness gene. Friabilin, a marker protein for grain softness (Ha), consists of two proteins, puroindoline a and b (pinA and pinB, respectively). We previously demonstrated that a glycine to serine mutation in pinB is linked inseparably to grain hardness. Here, we report that the pinB serine mutation is present in 9 of 13 additional randomly selected hard wheats and in none of 10 soft wheats. The four exceptional hard wheats not containing the serine mutation in pinB express no pinA, the remaining component of the marker protein friabilin. The absence of pinA protein was linked inseparably to grain hardness among 44 near-isogenic lines created between the soft variety Heron and the hard variety Falcon. Both pinA and pinB apparently are required for the expression of grain softness. The absence of pinA protein and transcript and a glycine-to-serine mutation in pinB are two highly conserved mutations associated with grain hardness, and these friabilin genes are the suggested tightly linked components of the Hardness gene. A previously described grain hardness related gene termed ''GSP-1'' (grain softness protein) is not controlled by chromosome 5D and is apparently not involved in grain hardness. The association of grain hardness with mutations in both pinA or pinB indicates that these two proteins alone may function together to effect grain softness. Elucidation of the molecular basis for grain hardness opens the way to understanding and eventually manipulating this wheat endosperm property.

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Calibration of comprehension is the correlation between subjective assessments of knowledge gained from reading and performance on an objective test. Contrary to intuition, this correlation is typically close to zero. This article is structured around four points concerning calibration of comprehension. First, poor calibration of comprehension is the rule, rather than the exception, a fact that has been repeatedly demonstrated in our laboratory and in others. Poor calibration is also typical in at least one other domain: solving insight problems. The high levels of calibration reported in studies on the calibration of probabilities and feeling-of-knowing research may be dependent on using feedback from taking the test to assess the probability of correct performance on the test.Second, we present two experiments that demonstrate that poor calibration of comprehension is not associated with a particular type of performance test but is found with inference tests, verbatim recognition tests, and idea recognition tests. For the most part, poor calibration is found when the test is given immediately after reading as well as when the test is given after a delay. Also, we demonstrate that poor calibration cannot be attributed to unreliable testing procedures.Third, the evidence from three experiments indicates that a likely reason for poor calibration is that subjects assess familiarity with the general domain of a text instead of assessing knowledge gained from a particular text. Assessing domain familiarity is probably easier than assessing knowledge gained from a particular text. Also, under some conditions, applying a domain familiarity strategy does result in spurious calibration, which thereby reinforces application of the strategy.Fourth, we demonstrate that calibration of comprehension can be enhanced if subjects are given a pretest that provides (self-generated) feedback. Even this ability is limited, however. Calibration is enhanced only when the processes and knowledge tapped by the pretest are closely related to the processes and knowledge required on the criterion test. Under these conditions, subjects apparently use feedback from the pretest to predict criterion test performance with a modest degree of accuracy. We briefly discuss the implications of these results for theories of representation of knowledge gained from reading.In preparing for a test of learning, a rational strategy is to our claim that beliefs about how much has been learned are study until one believes that the material is learned. Studying often uncorretated with performance on a test of comprehenfor less time is risky; studying for more time may be wasteful.sion. Second, we will demonstrate that the lack of correlation is For this strategy to be effective, however, beliefs and judgments not due to some methodological artifact, but that it is represenabout how much has been learned must be calibrated. That is, tative of a wide range of situations. Third, we present data supthese beliefs must be correlated with performance. Unfortu-porti...

Cereal Chem. 74(1):63-71The starch of wheat (Triticum aestivum L.) flour affects food product quality due to the temperature-dependent interactions of starch with water during gelatinization, pasting, and gelation. The objective of this study was to determine the fundamental basis of variation in gelatinization, pasting, and gelation of prime starch derived from seven different wheat cultivars: Kanto 107, which is a partial waxy mutant line, and six near-isogenic lines (NILs) differing in hardness. Complete pasting curves with extended 16-min hold at 93°C were obtained using the Rapid Visco Analyser (RVA). Apparent amylose content ranged from 17.5 to 23.5%; total amylose content ranged from 22.8 to 28.2%. Starches exhibited significant variation in onset of gelatinization. However, none of the parameters measured consistently correlated with onset or other RVA curve parameters that preceded peak paste viscosity. Peak paste viscosity varied from 190 to 323 RVA units (RVU). Higher peak, greater breakdown, lower final viscosity, negative setback, and less total setback

The hardness or texture of cereal grains is a primary determinant of their technological and processing quality. Among members of the Triticeae, most notably wheat, much of the variation in texture is controlled by a single locus comprised of the Puroindoline a, Puroindoline b and Grain Softness Protein-1 (Gsp-1) genes. Puroindolines confer the three major texture classes of soft and hard common wheat and the very hard durum wheat. The protein products of these genes interact with lipids and are associated with the surface of isolated starch (as a protein fraction known as 'friabilin'). During the past ten years a great diversity of alleles of both Puroindoline genes have been discovered and significant advances made in understanding the relationship between the gene presence/absence, sequence polymorphism and texture of cereal grains. Efforts have also focussed on Puroindoline and Gsp-1 genes in diploid progenitors, other Triticeae grasses and synthetic wheats in order to understand the evolution of this gene family and find potentially useful variants. The puroindoline homologues in other cereals such as rye and barley are also receiving attention. This work summarises new developments in molecular genetics of puroindolines in wheat and related Triticeae grasses, and the related genes in other cereals.

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Recent results have shown that mutations in genes coding for puroindoline a and b (PinA and PinB) are associated with the expression of the hard texture of wheat (Triticum aestivum L.) grain. A majority of hard wheats have a glycine‐to‐serine mutation in puroindoline b (allele PinB‐D1b), or they are devoid of puroindoline a (allele PinA‐D1b). Hard wheats with PinA‐D1b tend to be harder than those with PinB‐D1b Grain hardness is known to affect milling and baking traits. Our objective was to determine the influence of allelic variation in PinA and PinB on milling and bread quality traits in a recombinant inbred population segregating for PinA‐D1b and PinB‐D1b One hundred thirty‐nine recombinant inbred lines from the cross ‘Butte 86’ (PinA‐D1b allele)/ND2603 (PinB‐D1b allele) and parents were grown in a field trial with two replications at two locations. Grain hardness was measured by near‐infrared reflectance (NIR) and the single‐kernel characterization system (SKCS). Grain was milled and baked for each line. Puroindoline allele type was determined for each line. The PinB‐D1b group had significantly softer grain, higher break flour yield, flour yield, milling score, and loaf volume, and lower flour ash and crumb grain score (low score being desirable) than the PinA‐D1b group. Significant genetic variability was detected within allelic classes for all traits. The proportion of variation among entry means attributed to puroindoline classes was 34% for break flour yield, 26% for NIR hardness, and 22% for SKCS harness index. Grain hardness was negatively correlated with break flour yield, flour yield, and mixing score and positively correlated with flour ash. Grain hardness was not correlated with loaf volume or crumb grain score. The PinB‐D1b allele was more desirable for milling and bread baking, although superior milling and bread quality genotypes could be selected within either class.

Polyphenol oxidase (PPO) activity is highly related to the undesirable browning of wheat-based end products, especially Asian noodles. Characterization of PPO genes and the development of their functional markers are of great importance for marker-assisted selection in wheat breeding. In the present study, complete genomic DNA sequences of two PPO genes, one each located on chromosomes 2A and 2D and their allelic variants were characterized by means of in silico cloning and experimental validation. Sequences were aligned at both DNA and protein levels. Two haplotypes on chromosome 2D showed 95.2% sequence identity at the DNA level, indicating much more sequence diversity than those on chromosome 2A with 99.6% sequence identity. Both of the PPO genes on chromosomes 2A and 2D contain an open reading frame (ORF) of 1,731 bp, encoding a PPO precursor peptide of 577 amino acids with a predicted molecular mass of approximately 64 kD. Two complementary dominant STS markers, PPO16 and PPO29, were developed based on the PPO gene haplotypes located on chromosome 2D; they amplify a 713-bp fragment in cultivars with low PPO activity and a 490-bp fragment in those with high PPO activity, respectively. The two markers were mapped on chromosome 2DL using a doubled haploid population derived from the cross Zhongyou 9507/CA9632, and a set of nullisomic-tetrasomic lines and ditelosomic line 2DS of Chinese Spring. QTL analysis indicated that the PPO gene co-segregated with the two STS markers and was closely linked to SSR marker Xwmc41 on chromosome 2DL, explaining from 9.6 to 24.4% of the phenotypic variance for PPO activity across three environments. In order to simultaneously detect PPO loci on chromosomes 2A and 2D, a multiplexed marker combination PPO33/PPO16 was developed and yielded distinguishable DNA patterns in a number of cultivars. The STS marker PPO33 for the PPO gene on chromosome 2A was developed from the same gene sequences as PPO18 that we reported previously, and can amplify a 481-bp and a 290-bp fragment from cultivars with low and high PPO activity, respectively. A total of 217 Chinese wheat cultivars and advanced lines were used to validate the association between the polymorphic fragments and grain PPO activity. The results showed that the marker combination PPO33/PPO16 is efficient and reliable for evaluating PPO activity and can be used in wheat breeding programs aimed for noodle and other end product quality improvement.