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Plant-plant interaction plays a key role in regulating the composition and structure of communities and ecosystems. Studies of plant-plant interactions in forest ecosystems have mainly concentrated on growth effects of neighboring plants on target trees. Physiological effects of neighboring plants on target trees, in particular understorey effects on physiology of overstorey trees, have received less attention. It is still unclear what is the physiological mechanisms underlying positive growth effects of understorey removal, although understorey removal has been applied to improve the wood production for hundreds of years worldwide. Only 17.5% of published works dealt with understorey-overstorey interactions and only a few of those researched the understorey effects on the physiology of overstorey trees. Case studies indicated that overstorey Abies faxoniana trees grown with different understorey shrubs showed significantly different levels of tissue nitrogen and mobile carbohydrates. Removal experiment showed that nitrogen and mobile carbohydrates concentrations in Cunninghamia lanceolata trees grown in the absence of understorey shrubs differed significantly (pure stand > mixture) with those in trees grown in the presence of understorey shrubs, in particular during the dry season. This review highlighted that the neighboring woody plants affect Cand N-physiology in overstorey trees. These effects may be mainly resulted from underground competition for soil water rather than for other resources as the effects were more pronounced during the dry season. The present review suggests that positive effects of neighboring removal (e.g., understorey removal, thinning) on overstorey trees can be expected more rapidly and strongly in stressful area (e.g., low rainfall, nutrient-poor site) than in areas with optimal growth conditions. Hence, ecophysiology-based management strategies for dealing with neighboring plants in forest ecosystems should take into account: 1) site conditions, 2) timing, duration and frequency of management practices, and 3) species-specific properties and other aspects such as biodiversity conservation and soil erosion.

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Uniformity in the height of main stem and tillers is a key factor affecting ideal plant type, a key component in super high-yielding rice breeding. An understanding of the genetic basis of the panicle layer uniformity may thus contribute to breeding varieties with good plant type and high yield. In the present study, a doubled haploid (DH) population, derived from a cross between indica rice variety Zhai-Ye-Qing 8 (ZYQ8) and japonica rice variety Jing-Xi 17 (JX17) was used to analyze quantitative trait loci (QTL) for panicle layer uniformity related traits. Six, four and three QTL were detected for the highest panicle height (HPH), lowest panicle height (LPH) and panicle layer dis-uniformity (PLD), respectively. qHPH-1-1 and qPLD-1 were located at the same interval on chromosome 1. The JX17 allele(s) of these QTL increased HPH and PLD by 2.57 and 1.26 cm, respectively. Similarly, qPLD-7 and qHPH-7 were located at the same interval on chromosome 7, where the ZYQ8 allele(s) increased HPH and PLD by 3.74 and 1.96 cm, respectively. These four QTL were unfavourable for panicle layer uniformity improvement because a decrease of the PLD was accompanied by decrease of the plant height. qPLD-6 and qLPH-6-1 were located at the same interval on chromosome 6, however here the JX17 allele(s) increased LPH, but decreased PLD, suggesting that this QTL was favourable for improvement of panicle layer uniformity. The markers identified in this study are potential for marker assisted breeding for the improvement of the panicle layer uniformity and ideal plant type.

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Biofortifying food crops with essential minerals would help to alleviate mineral deficiencies in humans. Detection of quantitative trait loci (QTLs) for mineral nutrient contents in rice was conducted using backcross inbred lines derived from an interspecific cross of Oryza sativa × O. rufipogon. The population was grown in Hangzhou and Lingshui, with the contents of Mg, Zn, Fe, Mn, Cu and Se in brown rice measured in both trials and that in milled rice tested in Hangzhou only. A total of 24 QTLs for mineral element contents were identified, including two for both the brown and milled rice, 17 for brown rice only, and five for milled rice only. All the seven QTLs detected for the mineral contents in milled rice and 13 of the 19 QTLs for the contents in brown rice had the enhancing alleles derived from O. rufipogon. Fifteen QTLs were clustered in seven chromosomal regions, indicating that common genetic-physiological mechanisms were involved for different mineral nutrients and the beneficial alleles could be utilized to improve grain nutritional quality by markerassisted selection.

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Cereal Research Communications
Authors: W.F. Song, Z.Y. Ren, Y.B. Zhang, H.B. Zhao, X.B. Lv, J.L. Li, C.H. Guo, Q.J. Song, C.L. Zhang, W.L. Xin, and Z.M. Xiao

Two lines, L-19-613 and L-19-626, were produced from the common wheat cultivar Longmai 19 (L-19) by six consecutive backcrosses using biochemical marker-assisted selection. L-19 (Glu-D1a, Glu-A3c/Gli-A1?; Gli-A1? is a gene coding for unnamed gliadin) and L-19-613 (Glu-D1d, Glu-A3c/Gli-A1?) formed a set of near-isogenic lines (NILs) for HMW-GS, while L-19-613 and L-19-626 (Glu-D1d, Glu-A3e/Gli-A1m) constituted another set of NILs for the LMW-GS/gliadins. The three L-19 NILs were grown in the wheat breeding nursery in 2007 and 2008. The field experiments were designed using the three-column contrast arrangement method with four replicates. The three lines were ranked as follows for measurements of gluten strength, which was determined by the gluten index, Zeleny sedimentation, the stability and breakdown time of the farinogram, the maximum resistance and area of the extensogram, and the P andWvalues of the alveogram: L-19-613 > L-19-626 > L-19. The parameters listed above were significantly different between lines at the 0.05 or 0.01 level. The Glu-D1 and Glu-A3/Gli-A1 loci had additive effects on the gluten index, Zeleny sedimentation, stability, breakdown time, maximum resistance, area, P and W values. Although genetic variation at the Glu-A3/Gli-A1 locus had a great influence on wheat quality, the genetic difference between Glu-D1d and Glu-D1a at the Glu-D1 locus was much larger than that of Glu-A3c/Gli-A1? and Glu-A3e/Gli-A1m at the Glu-A3/Gli-A1 locus. Glu-D1d had negative effects on the extensibility and the L value compared with Glu-D1a. In contrast, Glu-A3c/Gli-A1? had a positive effect on these traits compared with Glu-A3e/Gli-A1m.

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