辽粳371特征特性及应用前景

辽粳371是辽宁省稻作研究所选育的水稻新品种,2001年通过辽宁省农作物品种委员会审定。该品种为散穗型,株高105～110cm,生育期为155～156d左右,属中熟品种,抗性较好,其米质经农业部稻米及其制品质量监督检验测试中心化验分析,达部颁一级优质米标准。经生产鉴定试验,平均产量9118.5kg/hm~2。在栽培管理上要注重稀播育壮秧,合理稀植,加强水、肥的管理,并预防病虫害的发生。指出了辽粳371适宜的种植区域及应用前景。     

Nondestructive Estimation of Standing Crop and Fuel Moisture Content in Tallgrass Prairie

Accurate estimation of standing crop and herbaceous fuel moisture content (FMC) are important for grazing management and wildfire preparedness. Destructive sampling techniques have been used to accurately estimate standing crop and FMC, but those techniques are laborious and time consuming. Existing nondestructive methods for estimating standing crop in tallgrass prairie have limitations, and few studies have examined nondestructive estimation techniques for FMC in this environment. Therefore, our objective was to develop robust models for nondestructive estimation of standing crop and FMC in tallgrass prairie. We calibrated and validated stepwise multiple linear regression (SMLR) and artificial neural network (ANN) models for standing crop and FMC using data collected in tallgrass prairies near Stillwater, Oklahoma. Day of year (DOY), canopy height (CH), Normalized Difference Vegetation Index (NDVI), and percent reflectance in five wavelength bands were candidate input variables for the models. The study spanned two growing seasons and nine patches located within three pastures under patch burn management, and the resulting data set with > 3 000 observations was split randomly with 85% for model calibration and 15% withheld for validation. Standing crop ranged from 0 to 852 g m^? 2, and FMC ranged from 0% to 204%. With DOY, CH, and NDVI as predictors, the SMLR model for standing crop produced a root mean squared error (RMSE) of 119 g m^? 2 on the validation data, while the RMSE of the corresponding ANN model was 116 g m^? 2. With the same predictors, the SMLR model for FMC produced an RMSE of 26.7% compared with 23.8% for the corresponding ANN model. Thus, the ANN models provided better prediction accuracy but at the cost of added computational complexity. Given the large variability in the underlying datasets, the models developed here may prove useful for nondestructive estimation of standing crop and FMC in other similar grassland environments.     

高留胚率水稻辽粳294成熟胚组织培养条件的优化

以高留胚率水稻辽粳294成熟胚为外植体,对影响高留胚率水稻愈伤组织诱导、分化的接种方式、培养基中激素水平进行研究。结果表明,用解剖刀在胚上纵切1刀后再将种子接在培养基上,种子灭菌彻底,愈伤组织诱导率高且质量较好。诱导培养基中激素6-BA和KT的浓度对愈伤组织的诱导率有极显著的影响,诱导培养基为N6+2 mg/L 2,4-D+0.3 mg/L 6-BA+0.1 mg/L KT时,诱导率较高,可达90.0%;分化培养基为MS+0.8 mg/L NAA+2 mg/L 6-BA时,绿苗分化效果好,分化率为73.0%。     

辽粳系列水稻新品系农艺性状间灰色关联度分析

针对辽粳系列品系农艺性状,应用灰色理论进行相关的产量分析。结果表明,在株高限定范围内来提高水稻产量,应该重点加强对结实率、着粒密度、分蘖的选择。     

磷肥与土壤类型对水稻秧苗素质的影响

为探明磷肥含量、土壤类型对水稻秧苗素质、根系形态及养分吸收的影响,以中晚熟品种‘辽粳401’为试验材料,选用壤质土、黏质土和砂质土3种土壤类型,采用裂区试验方法研究6种磷肥与土壤组合对水稻秧苗素质的影响。结果表明：低磷黏土与高磷黏土培育的水稻秧苗素质最好,根系形态最佳,更有利于秧苗的生长。磷肥施入量2.5 g/盘能够满足水稻秧苗对磷肥的吸收,说明适量的磷肥有助于培育健壮的秧苗。     

辽粳系列水稻新品种的选育、应用及发展

辽粳系列水稻新品种的繁育和发展，为辽宁水稻生产起到积极促进作用。本文介绍了辽粳系列水稻品种的选育进程、各水稻新品种的主要特点以及推广应用情况，并就如何做好未来品种选育和推广工作提出了对策。     

辽粳系列水稻品种产量性状分析

辽粳系列品种是指辽宁省稻作研究所选育的系列常规水稻品种。辽粳系列水稻品种具有产量高、稳产性好、米质优良和抗病性强等优点。本文选用已审定并在生产上应用面积较大、有代表性的18个辽粳系列水稻新品种,对其产量性状进行分析。结果表明,在产量构成因素中,每穗成粒数的可塑性最大,千粒重的可塑性最小;偏大穗型品种其穗粒数与产量的相关系数大,密切程度高,高生物产量是获得高产的物质基础;多穗型品种其穗数与产量的密切程度相对更高一些;在产量构成因素中,其他因素通过总粒数对产量发挥的作用最大。     

辽粳系列水稻品种米质现状分析

辽粳系列水稻品种具有产量高、稳产性好、米质优良、抗病性强等优点,本文选用已审定并在生产上应用面积较大、有代表性的18个辽粳系列水稻新品种,对其米质理化9项指标进行分析,系统地评价辽粳系列水稻品种米质现状。结果表明,在辽粳系列品种中,品质性状能够达到国家1级优质米标准的品种占总数的27.7%,达到2级优质米的品种占总数的22.2%,达到国家3级优质米的品种占总数的11.1%,未能达到国家优质米标准的占38.8%,垩白度和垩白率为影响目前辽粳系列品种米质的主要因子。