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摘要
本文试验选用黄淮麦区近年来推广的具有较高产量的19个小麦品种,分析了4种溶剂保持力和容重、蛋白质、湿面筋、粉质仪参数和淀粉粘度仪参数等17个品质指标品种间的差异,以及性状间的相关性。结果表明,4种溶剂保持力品种间差异达极显著水平。相关分析显示:乳酸SRC与蛋白质和湿面筋呈显著正相关,相关系数分别为0.61和0.60,同时与粉质仪参数5项指标也具有相关性;碳酸钠溶剂保持力与硬度和吸水率呈极显著正相关,相关系数分别为0.75和0.88,与峰值粘度、稀懈值和糊化温度呈极显著负相关,相关系数分别为-0.64、-0.74和-0.66;水溶剂保持力与硬度、吸水率和粉质质量数呈显著正相关,与稀懈值呈极显著负相关,相关系数分别为0.57、0.75、0.47和-0.65;蔗糖溶剂保持力与蛋白质、湿面筋和吸水率均呈均有正相关性,相关系数分别为0.60、0.52和0.65。溶剂保持力变化趋势分析表明,4种溶剂保持力随筋力的增强数值相对提高。由此说明在本试验不同筋力品种中4种溶剂中,水溶剂保持力和碳酸钠溶剂保持力与籽粒硬度关系最为密切;蔗糖和乳酸溶剂保持力能够反映面粉中蛋白含量的多少和蛋白特性,而水溶剂保持力则是一个综合指标,能够反映面粉所有组分特性。SRC多用于软质小麦品质评价,在中强筋小麦品质评价中应用较少报道。通过本文的试验研究分析,为SRC法在中强筋小麦品种品质评价中应用提供依据,并作为品质分析的一项指标,也为小麦育种后代选择提供依据。
本文同时还通过“3414”施肥试验即3个因素、4个水平和14组处理,研究分析氮磷钾三种肥料环境因素在四种不同施肥水平下对4种溶剂保持力的影响。通过回归分析得出三元二次回归方程Y=b_0+b_1x_1+b_2x_1~2+b_3x_2+b_4x_2~2+b_5x_3+b_6x_3~2+b_7x_1x_2+b_8x_1x_3+b_9x_2x_3,并计算出四种溶剂保持力的各自回归方程。分析结果显示:除水溶剂保持力回归分析的F值 F_(0.01),方程均具有(可靠)拟合性。说明溶剂保持力受施肥水平的影响。通过对三种因素的单因素在同条件下的方差分析,即N在P_2K_2条件下的0、1、2、3四种水平、P在N_2K_2条件下的0、1、2、3四种水平和K在N_2P_2条件下的0、1、2、3四种水平,结果显示:在磷钾施肥水平不变条件下,氮元素对水溶剂保持力影响不大,但对其他三种溶剂保持力影响达极显著水平,试验中随着氮水平的不断提高,乳酸SRC、蔗糖SRC和碳酸钠SRC数值呈现较大幅度提高;而磷钾元素分别在其他元素条件不变情况下,对四种溶剂保持力的影响均不显著。表明了三种肥料环境因素中氮对小麦品质的影响较大,其他两种因素对品质影响不明显。
Four solvent retention capacities (SRCs) as lactic acid SRC (LASRC), sodium carbonate SRC (SCSRC), water SRC (WSRC) and sucrose SRC (SSRC), were analyzed among nineteen high yield wheat (Triticum aestivum L.) cultivars with middle or strong gluten content grown in Huanghuai region, and correlation analyses were made with quality traits such as volume weight, protein, wet gluten content, farinograph parameters and starch paste viscosity. Results showed significant differences in LASRC, SCSRC, WSRC and SSRC levels between cultivars (p < 0.01). Analyses showed positive correlation between LASRC and protein and wet gluten content (r = 0.61 and 0.60, respectively). LASRC was also correlated to five farinograph parameters. SCSRC was shown to be significantly correlated to grain hardness and water absorption rate (r = 0.75 and 0.88, respectively). However, it showed negative correlation to peak viscosity, breakdown and gelatinization temperature (r = -0.64, -0.74 and -0.66). WSRC was positively correlated to grain hardness, water absorption rate and farinogram quality number (r = 0.57, 0.75 and 0.47, respectively) and negatively correlated to breakdown value (r = -0.65). Positive correlation was also found between SSRC and protein, wet gluten content and water absorption rate with correlation coefficient r = 0.60,0.52 and 0.65, respectively. Results showed that SRCs could be the indicators of wheat quality. Among four SRCs studied, the relatedness of WSRC and SCSRC to wheat grain hardness was the strongest; SCSRC could directly reflect the level of damaged starch and indirectly reflect the grain hardness; SSRC could be used as indicator of glutenin and pentosan content; LASRC linked to glutenin traits and WSRC was a comprehensive parameter demonstrating all traits of flour components. Previously, SRCs were commonly used to evaluate the quality of soft wheat cultivars; less work had been done on cultivars with middle to strong gluten content. The current work demonstrates the possibility and feasibility of using SRC parameters into quality evaluation of wheat cultivars with middle to strong gluten content. This work is also helpful for breeding selection during early generations.
Furthermore, a '3414' fertilizing model, i.e. 3 factors, 4 levels and 14 treatments, was used to study the effects of N, P_2O_5 and K_2O fertilizers on these SRCs. A regression model of Y=b_0+b_1x_1+b_2x_1~2+b_3x_2+b_4x_2~2+b_5x_3+b_6x_3~2+b_7x_1x_2+b_8x_1x_3+b_9x_2x_3 was obtained and the regression of each SRC was calculated. The F value of the regression of each SRC was >F_(0.05) or >F_(0.01) except the WSRC which had an F value
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