[关键词]
[摘要]
子粒破碎率高是当前中国玉米机械收获子粒的重要限制因素,解析破碎率变化原因,建立其简便预测模型是需要解决的重要问题。本文采集7个玉米品种在3个种植密度下组合的果穗,在不同子粒含水率梯度条件下开展单穗脱粒试验。种植密度在6万~9万株/hm2范围内对子粒破碎率没有影响,品种、子粒的含水率、抗侧压碎力和穿刺强度等的影响均达到统计显著水平。品种对破碎率变化的偏贡献率为12.7%,且品种的偏贡献率 < 子粒含水率的偏贡献率 < 抗侧压碎力的偏贡献率 < 穿刺强度的偏贡献率,种植密度的偏贡献率接近于零。破碎率的最优预测因子是穿刺强度,预测模型:破碎率=10.25×0.990穿刺强度,满足破碎率不高于5%约束的穿刺强度值不得低于60 MPa。研究结果可为玉米破碎率预测、宜机收玉米新品种培育与鉴定、脱粒机具设计与制造提供数据支撑和技术参考。
[Key word]
[Abstract]
High broken rates of machine-harvested kernels are one of the most important limiting factors for maize product quality in China. This paper aimed at evaluating biophysical factors influencing the broken rates of kernels under mechanical shelling and building single factor models for the prediction of broken rates. Ears with an assign set of different moisture levels, from 7 maize cultivars grown at 3 plant densities, were subject to shelling tests using the same machine. Plant densities from 60 000 to 90 000 plant/ha didn't influence broken rates, but maize cultivar, kernel moisture, kernel side crushing forces, and kernel puncture strength did at statistically significant levels. In respect of effect sizes of different factors for broken rates, the total contribution of maize cultivars was smaller than that of kernel moisture to variations in kernel broken rates. Kernel moisture contributed less than both of side crushing forces and puncture strength, and side crushing forces did less than puncture strength. The contribution of plant densities to broken rate variation was close to zero. Kernel puncture strength was the optimum predictor to estimate broken rates, their relation reads as:broken rate=10.25*0.990(puncture strength). Value 60 MPa of puncture strength is a lower limit to reach a broken rate of no more than 5%. To sum up, t kernel strength affected kernel broken rate more than cultivar did, and plant density didn' t. The study provides useful information and an approach for broken rate estimation, screening of new maize cultivars suitable to mechanical kernel harvesting, shelling machine design, and manufacture.
[中图分类号]
S513.091
[基金项目]
国家重点研发计划项目(2016YFD0300306)