夏玉米籽粒脱水特性及与灌浆特性的关系

【目的】当前,玉米收获期籽粒含水率普遍偏高,限制了中国机械粒收技术的推广应用。玉米籽粒授粉后,灌浆与脱水过程相伴,但二者之间的关系并不明确,本研究通过对不同玉米品种籽粒脱水和灌浆过程的系统观测,明确其籽粒脱水和灌浆特征,探讨二者间的关系,为适宜机械粒收品种的选育和推广提供支持。【方法】试验于2015—2016年在河南新乡进行,累计选用22个供试玉米品种,统一授粉。2015年自授粉后26 d开始至11月14日止、2016年自授粉后11 d开始至10月17日止,连续测定籽粒含水率(MC)、含水量(M)、干重(DW)与鲜重(FW)的动态变化,建立这些指标与授粉后积温(T)之间的回归方程,以此明确籽粒脱水和灌浆特征,并结合籽粒脱水、灌浆参数的相关分析结果,探讨这两个过程的关系。【结果】玉米籽粒含水率、含水量、干重及鲜重的动态变化与授粉后积温均有极显著的非线性关系。22个参试玉米品种籽粒含水率与授粉后积温的关系符合Logistic Power模型。授粉后,参试品种含水率降至28%需要积温1 126—1 646℃·d,平均1 357℃·d;含水率降至25%需要积温1 218—1 810℃·d,平均1 480℃·d。综合分析籽粒干物质和含水量的变化动态,籽粒含水率变化可分为两个阶段。第一个阶段从籽粒建成至线性灌浆期结束为止,干物质的快速积累是含水率快速下降的主导因素;第二阶段自线性灌浆期结束至籽粒收获,含水率下降的主导因素转化为籽粒水分的持续散失。相关分析显示,玉米灌浆期天数、积温与生理成熟期籽粒含水率在2015年达到极显著负相关,2016年相关性不显著;不同品种生理成熟前、后及总脱水速率与灌浆速率之间相关性不显著。【结论】籽粒含水率与授粉后积温建立的Logistic Power回归模型具有良好的预测稳定性。籽粒含水率的变化由籽粒灌浆和籽粒脱水两个关键因素分阶段主导,评价适宜机械粒收的品种,不仅要注意籽粒灌浆特性和熟期,还要关注籽粒脱水特性的选择。

Grain Dehydration Characters of Summer Maize and Its Relationship with Grain Filling

【Objective】 Nowadays, the higher grain moisture content at harvest limits the popularization and application of the mechanical grain harvesting technology. Maize grain filling process is accompanied by grain dehydration process after pollination, however, the relationship between these two processes remains a challenge. We used different maize cultivars to study the characters of the two processes and the relationships between them, which provided support for breeding and promotion of the harvesting technology. 【Method】 Field experiments were conducted in Xinxiang, Henan in 2015 and 2016. A total of 22 cultivars were studied and the controlled pollination was applied in every cultivar. In 2015, the sampling time was from the 26th day after pollination to November 14th. In 2016, the sampling time was from 11th day after pollination to October 17th. We measured dynamic changes of grain moisture content (MC), moisture (M), dry weight (DW) and fresh weight (FW) before and after physiological maturity to establish the relationships between these indexes and the accumulated temperature after pollination (T) by equations. Based on these equations, the grain dehydration process and the filling process were clarified. Then, we developed the relationship between these two processes by the correlation analysis. 【Result】 Results showed that T had the significant non-linear relationships with MC, M, DW and FW. Among them, the relationship between MC and T of 22 maize cultivars could be described by the Logistic Power regression model. The MC dropped to 28% when the T reached average 1 357°C·d, changing from 1 126 °C·d to 1 646 °C·d between cultivars. The average T was 1 480°C·d for 25% MC, changing from 1 218 °C·d to 1 810 °C·d. Dynamic change of MC could be divided into two stages based on the changes of DW and M. The first stage was from the start of grain growth to the end of linear filling process, in which the decreasing MC was mainly decided by the fast dry matter accumulation. The second stage followed the former ending to the harvest time, in which the decreasing MC was owned to the decreasing M. The correlation analysis showed that there was a significant negative correlation between the MC at physiological maturity and the filling days, and the T from pollination to physiological maturity in 2015 while the relationship was not significant in 2016, reflecting the differences among maize cultivars. There was no significant relationship between the filling rate and the grain dehydration rate before physiological maturity, similar to the grain dehydration rate after physiological maturity and the total dehydration rate. 【Conclusion】 Our study found that the Logistic Power regression model had a good predictive stability to establish the relationship between MC and T. We proposed that MC was decided by the grain filling rate and the grain moisture loss rate respectively at different stages. Thus, breeders should not only pay attention to grain filling characters and maturity time, but also concern about the grain dehydration characters when evaluate suitable cultivars for the harvesting technology.