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江淮地区稻-麦周年产量差及其与资源利用关系

本站小编 Free考研考试/2021-12-26

杜祥备,1, 习敏2, 孔令聪,1,*, 吴文革,2,*, 陈金华3, 许有尊2, 周永进21安徽省农业科学院作物研究所, 安徽合肥 230031
2安徽省农业科学院水稻研究所, 安徽合肥 230031

Yield gaps of rice-wheat double cropping and its relationship with resource utilization in Yangtze-Huaihe Rivers region

DU Xiang-Bei,1, XI Min2, KONG Ling-Cong,1,*, WU Wen-Ge,2,*, CHEN Jin-Hua3, XU You-Zun2, ZHOU Yong-Jin21Crop Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, Anhui, China
2Rice Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, Anhui, China, 3 Anhui Province Meteorological Research Institute, Hefei 230031, Anhui, China

通讯作者: * 孔令聪, E-mail: konglingcong@126.com; 吴文革, E-mail: aaasrri@163.com

收稿日期:2020-04-26接受日期:2020-08-19网络出版日期:2020-09-21
基金资助:国家重点研发计划项目.2017YFD0301306
国家重点研发计划项目.2018YFD0300906
国家重点研发计划项目.2016YFD0300503


Received:2020-04-26Accepted:2020-08-19Online:2020-09-21
Fund supported: National Key Research and Development Program of China.2017YFD0301306
National Key Research and Development Program of China.2018YFD0300906
National Key Research and Development Program of China.2016YFD0300503

作者简介 About authors
E-mail: duxiangbei@126.com









摘要
江淮地区是我国水稻和小麦重要的生产基地, 明确该地区不同产量水平之间的差异特征及形成机制, 探索区域粮食生产的限制因子, 可为缩减江淮地区周年产量差的技术途径提供科学依据和参考。本研究以稻-麦周年生产体系为研究对象, 定量分析不同产量水平田块之间的产量差与气候影响因素。结果表明, 江淮地区水稻、小麦及周年农户水平与试验水平和高产纪录间存在显著的产量差, 分别为3315.9、1537.5、4645.6 kg hm-2和7498.6、3977.9、9840.9 kg hm-2。水稻、小麦及周年农户水平较试验水平还有46.2%、29.7%和37.3%的增产潜力, 较高产纪录还有104.5%、77.0%和79.0%的增产潜力。每穗粒数是造成水稻产量差的主要因子, 穗数和每穗粒数是造成小麦产量差的主要因子。与农户水平相比, 水稻试验水平和高产纪录的穗粒数分别增加30.4%和116.1%; 小麦试验水平和高产纪录的穗数和每穗粒数平均分别增加40.9%、70.0%和21.8%、19.6%。缩小产量差水稻主要依赖于增加每穗粒数, 小麦靠穗数和每穗粒数的协同提高。生育期累积辐射和积温较低是导致水稻产量差异的主要气候因素, 而生育期降雨过多是导致小麦产量差异的主要气候因素。根据研究提出了“强稻稳麦”是提升江淮地区周年粮食生产的有效途径。
关键词: 江淮地区;稻麦两熟;产量差;产量潜力;资源截获

Abstract
The Yangtze-Huaihe rivers region is an important production base of rice and wheat in China. It is necessary to clarify the differences and formation mechanism between different yield levels in the region, and to explore the limiting factors for regional grain production, which can provide scientific basis and reference for the management practices to reduce the annual yield gap in the Yangtze-Huaihe rivers region. Based on annual rice-wheat production situation, crop yield was divided into three different levels, farmer yields, experimental yields and high record yields. Yield gaps and the climate factors of different yield levels were quantified. Results showed that there were significant differences between farmer yields and experimental yields, high record yields of rice, wheat and annual in the Yangtze-Huaihe rivers region, which were 3315.9, 1537.5, and 4645.6 kg hm-2, 7498.6, 3977.9, and 9840.9 kg hm-2, respectively. Compared with the experimental yields, the farmer yields of rice, wheat and annual had yield increase potential of 46.2%, 29.7% and 37.3%, and 104.5%, 77.0% and 79.0% in comparison with the high record yields, respectively. The number of grains per spike was the main factor resulting in the yield difference in rice, and the grain numbers per spike and the number of spikes contributed to the yield difference in wheat. Compared with the farmer average yield, the grain numbers per spike of rice in experimental yields and high record yields were increased by 30.4% and 116.1%, respectively; the spikes and grain numbers per spike of wheat were increased by 40.9%, 70.0% and 21.8%, 19.6%, respectively. Reducing the yield gaps mainly depended on increasing the grain numbers per spike for rice, and synergistic improvement in the number of spikes and the grain numbers per spike for wheat. Cumulative radiation and low accumulated temperature during the growth period were the main climatic factors affected rice production, while excessive rainfall was the main climatic factor affected wheat production. The results suggested that in order to strengthen rice production and stabilize wheat production was an effective way to increase the annual grain production in the Yangtze-Huaihe rivers region.
Keywords:Yangtze-Huaihe Rivers region;rice-wheat double cropping;yield gap;yield potential;resources capture


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本文引用格式
杜祥备, 习敏, 孔令聪, 吴文革, 陈金华, 许有尊, 周永进. 江淮地区稻-麦周年产量差及其与资源利用关系[J]. 作物学报, 2021, 47(2): 351-358. doi:10.3724/SP.J.1006.2021.02028
DU Xiang-Bei, XI Min, KONG Ling-Cong, WU Wen-Ge, CHEN Jin-Hua, XU You-Zun, ZHOU Yong-Jin. Yield gaps of rice-wheat double cropping and its relationship with resource utilization in Yangtze-Huaihe Rivers region[J]. Acta Agronomica Sinica, 2021, 47(2): 351-358. doi:10.3724/SP.J.1006.2021.02028


在当前全球人口膨胀的背景下, 粮食安全问题日益严峻, 预测到2030年全球每年粮食需求将达到28亿吨。为满足这一需求, 提升粮食总产量是未来农业领域研究的热点问题[1]。我国人口对粮食供给的压力尤为巨大, 在有限的耕地资源背景下, 唯有提高作物单产水平才是确保粮食安全的唯一途径。安徽江淮地区地处我国南北气候过渡带, 是我国粮食的主要生产基地之一。稻-麦两熟种植是区域粮食生产的主要种植制度, 通常水稻于5月10月至20日播种, 小麦收获后移栽, 10月中下旬收获, 生育期140~160 d, 平均单产7135.5 kg hm-2; 小麦10月下旬至11月初播种, 5月底至6月初收获, 生育期200~215 d, 平均单产5365.5 kg hm-2。江淮地区常年稻麦轮作面积120万公顷, 占全国稻麦轮作25%以上, 为保障国家粮食安全做出了重要贡献[2]

近年来, 安徽粮食生产技术取得长足进步, 连续十六连丰。但受气候变化、自然灾害及栽培管理技术等影响, 安徽稻麦单产水平、稳定性与粮食总产提高面临重大的挑战。现有的生产管理条件下作物生长潜力仍没有得到充分挖掘, 不同生产主体产量差距较大, 甚至同一地区不同农户田块之间作物产量的差距也较大。在当前作物单产潜力提升有限的情况下, 通过提高单位土地上的粮食产量来缩减区域内的产量差变得越来越重要[3]。实际生产中江淮地区稻麦大面积的平均产量还处于较低水平, 单产还有很大的增长潜力。因此, 缩减区域产量差, 是全面提高区域粮食生产的关键[4]

产量差研究一直是国际作物学研究的热点。产量差的研究能够揭示产量的提升空间, 及区域产量提高的限制因子[1,5-7]。国内外一些****从不同侧面对我国不同区域主要粮食作物产量差及增产潜力进行了研究[5,6,7,8]。但以往研究多是针对单一作物进行, 对周年粮食生产和气候资源利用的研究鲜见报道。同时, 针对江淮地区稻麦周年产量差的研究尚未见报道。本研究结合农户调研和大田试验示范, 定量分析江淮地区稻-麦周年生产的产量差, 明确区域粮食产量提升的主要限制因素, 以期为缩减江淮地区稻-麦周年产量差和粮食总产的持续稳定提高提供科学依据。

1 材料与方法

1.1 区域概况

以安徽省江淮地区稻麦两熟主产区为研究区域, 主要包括凤台、寿县、颍上、怀远、定远、凤阳、天长、霍邱、巢湖、庐江等地区。江淮地区年平均气温在14~17℃之间, 平均日照1800~2500 h, 平均无霜期200~250 d, 平均降水量800~1800 mm。主要种植模式是水稻-小麦一年两熟轮作。

1.2 数据来源

产量数据主要来源于“十一五”、“十二五”和“十三五”国家粮食丰产科技工程安徽省代表性地点田间试验、高产攻关示范和农户生产对照的稻-麦周年产量数据。其中, 田间试验和高产攻关示范产量数据水稻季166个、小麦季80个、周年72个, 农户生产对照产量数据水稻季76个、小麦季85个、周年60个。气象数据来源于安徽省气象局, 包括上述研究区域的9个站点2008—2019年逐日的平均温度、辐射量、降水量等气象资料。

1.3 产量差的确定

为比较不同的产量水平, 根据Lobell等[1]的分类方法, 从数据集中选取田间试验和高产攻关示范产量前5%的均值作为高产纪录, 中间80%的均值作为试验水平, 农户产量中间80%的均值作为农户水平。确定3个不同产量水平: 高产纪录、试验水平和农户水平。其中水稻高产纪录、试验水平和农户水平数据分别为8、133和61个, 小麦分别为4、64和68个, 周年分别为4、58和48个。根据产量的不同标准水平定义了2个产量差距: 以高产纪录为基础的产量差(YG1)和基于试验水平为基础的产量差(YG2)。

YG1 = 高产纪录-农户水平, YG2 = 试验水平-农户水平。

1.4 数据处理

采用Microsoft Excel 2019对数据进行统计与整理, 用Origin 2018进行分析及作图, SPSS 20.0软件进行方差分析, Duncan’s法检验显著性。

2 结果与分析

2.1 江淮地区稻-麦周年产量水平

江淮地区稻-麦两熟种植模式下, 水稻、小麦和周年农户水平分别为6205.5~9390.0、4177.5~7098.0和11,145.2~16,335.6 kg hm-2, 变幅分别为7.8%、11.7%和10.8%; 水稻、小麦和周年试验水平分别为9306.4~12,603.0、6000.5~7731.8和15,120.0~19,631.4 kg hm-2, 变幅分别为8.7%、7.9%和6.3%; 水稻、小麦和周年高产纪录分别为14,379.0~15,307.5、8904.0~9501.3和21,562.5~22,896.0 kg hm-2, 变幅分别为2.7%、1.4%和2.5% (图1)。3个不同产量层次中, 高产纪录变幅较小, 农户水平变异较大。

图1

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图1江淮地区稻-麦周年产量分析

不同小写字母表示在5%水平差异显著。
Fig. 1Descriptive statistics of the rice-wheat annual yield in Yangtze-Huaihe rivers region

Values marked with different lowercase letters indicate significant differences at P < 0.05.


2.2 江淮地区稻-麦周年产量差

江淮地区稻-麦两熟种植高产纪录、试验水平与农户水平之间均存在显著差距(表1)。其中, 水稻、小麦和周年产量农户水平分别为7175.4、5168.2和12,463.3 kg hm-2, 相比试验水平的产量差(YG2)分别为33,315.9、1537.5和4645.6 kg hm-2, 相当于试验水平的68.4%、77.1%和72.8%, 还有46.2%、29.7%和37.3%的增产潜力; 相比高产纪录的产量差(YG1)分别为7498.6、3977.9和9840.9 kg hm-2, 相当于高产纪录的48.9%、56.5%和55.9%, 还有104.5%、77.0%和79.0%的增产潜力。

Table 1
表1
表1江淮地区稻-麦周年产量、产量差和增产潜力
Table 1Actual yield, yield potential and yield gaps among different yield levels in Yangtze-Huaihe rivers region
项目
Item
产量水平
Different yield level
水稻
Rice
小麦
Wheat
周年
Annual
产量
Yield (kg hm-2)
高产纪录Highest recorded yield14,674.1 a9146.1 a22,304.3 a
试验水平Experimental yield10,491.3 b6705.8 b17,108.9 b
农户水平Farmer yield7175.4 c5168.2 c12,463.3 c
产量差
Yield gap (kg hm-2)
高产纪录-农户水平 Highest recorded yield-Farmer yield (YG1)7498.63977.99840.9
试验水平-农户水平 Experimental yield-Farmer yield (YG2)3315.91537.54645.6
增产潜力
Increase potential (%)
农户水平-高产纪录 Farmer yield-Highest recorded yield104.577.079.0
农户水平-试验水平 Farmer yield-Experimental yield46.229.737.3
表中同列不同小写字母表示在0.05水平差异显著。
Values followed by different lowercase letters indicate significant differences in the same column at P < 0.05.

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江淮地区稻-麦两熟种植季节间产量差、增产潜力和增产绝对量均以水稻最高, 小麦相对较小。同时, 高产记录、试验水平与农户水平下水稻产量占周年产量比重分别为65.8%、61.3%和57.6%, 显著高于小麦的34.2%、38.7%和42.4%。周年总产量越高, 水稻产量所占比重也越高。因此, 提升水稻季产量是进一步提高周年产量的关键所在。

2.3 稻-麦产量与其构成因子间的关系

将不同产量群体稻麦产量与其构成因子进行相关分析(图2)发现, 水稻产量与每穗粒数呈极显著正相关, 而与穗数和千粒重呈弱的负相关关系。小麦产量与穗数呈极显著正相关, 与每穗粒数呈显著正相关, 而与千粒重呈弱的正相关关系。进一步分析与不同产量群体稻麦显著相关的产量构成因子发现, 水稻高产纪录和试验水平均具有显著高的每穗粒数, 较农户水平分别增加116.1%和30.4% (表2)。小麦高产纪录和试验水平具有显著高的穗数和每穗粒数, 较农户水平分别增加70.0%、40.9%和19.6%、21.8%。

图2

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图2稻-麦产量与其构成因子间相关性分析

A、B、C为水稻, D、E、F为小麦。
Fig. 2Relationship between grain yield and its components for different yield levels in Yangtze-Huaihe rivers region

A, B, C are responsible for rice; D, E, F are responsible for wheat.


Table 2
表2
表2江淮地区稻麦不同产量群体主要产量构成因子差异
Table 2Differences of key yield components of rice and wheat among different yield levels in Yangtze-Huaihe rivers region
项目
Item
水稻Rice小麦Wheat
每穗粒数
Grain number per spike
相对比例
Relative ratio (%)
穗数
Spike number
(×104 hm-2)
相对比例
Relative ratio
(%)
每穗粒数
Grain number
per spike
相对比例
Relative ratio
(%)
高产纪录Highest recorded yield276.8 a216.143.7 a170.034.1 a119.6
试验水平Experimental yield167.1 b130.436.2 b140.934.7 a121.8
农户水平Farmer yield128.1 c100.025.7 c100.028.5 b100.0
表中同列不同小写字母表示在0.05水平差异显著。
Values followed by different lowercase letters indicate significant differences in the same column at P < 0.05.

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2.4 江淮地区稻-麦生育期气候资源截获

水稻生育期的总辐射和积温与产量间的变化趋势明显(图3-A, C)。相关分析表明, 不同产量群体之间水稻季总辐射和积温差异显著, 表现为高产纪录>试验水平>农户水平。说明辐射和积温的高低对水稻产量起正相关作用。高产记录、试验水平和农户水平水稻生育期总辐射和积温平均分别为2791、2562、2443 MJ m-2和4295、4114、3971℃ d。不同产量群体水稻生长季的降水无显著变化, 说明水稻产量与降水相关性不大。

图3

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图3江淮地区不同稻-麦产量群体生育期气候资源截获

A、C、E为水稻, B、D、F为小麦。不同小写字母表示在0.05水平差异显著。
Fig. 3Accumulated radiation, growth degree-days and precipitation in rice and wheat seasons under different yield levels in Yangtze-Huaihe rivers region

A, C, E are responsible for rice; B, D, F are responsible for wheat. Values marked with different lowercase letters indicate significant differences at P < 0.05.


小麦生育期的总辐射与产量间的变化趋势明显(图3-B), 不同产量群体之间差异显著, 表现为高产纪录>试验水平>农户水平。高产纪录、试验水平和农户水平小麦生育期总辐射平均分别为3064、2851、2759 MJ m-2, 说明辐射的高低对小麦产量起到正效应作用。不同产量群体小麦生育期的总积温与产量间的变化趋势表现为农户水平>试验水平>高产纪录(图3-D), 降水则表现为农户水平>高产纪录>试验水平(图3-F), 总积温和降水均与产量呈负相关关系。

对不同产量群体稻麦生育期进一步分析发现,高产纪录和试验水平水稻和小麦均具有显著长的生育期, 水稻季较农户水平分别增加了8.0 d和5.9 d, 小麦季分别增加了6.4 d和3.3 d (表3)。

Table 3
表3
表3江淮地区不同稻-麦产量群体生育期
Table 3Growth period of rice, wheat and annual year under different yield levels in Yangtze-Huaihe rivers region
项目Item水稻Rice小麦Wheat
高产纪录Highest recorded yield150.3 a212.6 a
试验水平Experimental yield148.2 a209.5 ab
农户水平Farmer yield142.3 b206.2 b
表中同列不同小写字母表示在0.05水平差异显著。
Values followed by different lowercase letters indicate significant differences in the same column at P < 0.05.

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3 讨论

3.1 江淮地区稻-麦产量差及增产潜力

分析研究作物产量差与形成特征, 对制定针对性提高作物产量措施、保障国家粮食安全具有重要意义[7]。本研究通过对安徽江淮地区粮食主产区多年稻麦生产分析, 定量化了农户水平周年产量相对于试验水平和高产纪录有4645.6 kg hm-2和9840.9 kg hm-2的增产空间。本研究结果证明了在当前农户生产条件下, 稻麦产量仍然具有较大的增产空间。试验水平产量是多年粮丰项目进行试验示范, 是可以复制, 完全能够达到的产量, 通过进一步缩小农户水平与试验水平之间的产量差对于整体提高地区粮食产量有重要的现实意义。本研究结果发现, 农户水平水稻产量相对于试验水平仍有46.2%的增产潜力, 而小麦仅有29.7%的增产潜力。与小麦比, 水稻具有较高的产量差、增产潜力和增产绝对量。同时, 水稻产量占周年产量比重显著高于小麦。因此, 提高稻麦周年产量应首先提高水稻产量, “强稻稳麦”是进一步提高江淮地区稻麦周年粮食生产的主要途径。

3.2 江淮地区稻-麦产量差的构成因子分析

稻麦产量是由穗数、每穗粒数和千粒重3个构成因子共同作用的结果。其中单位面积穗数和每穗粒数被认为是产量形成最重要的决定因素[9,10,11,12]。本研究中, 不同产量水平稻麦产量构成因子差异较大。与前人研究有所不同的是, 本研究发现每穗粒数是造成水稻产量差异的主要因子。水稻穗数和千粒重对产量的增加效应较小, 甚至呈负效应, 而每穗粒数的贡献比较大。这主要是因为在当前生产条件下, 水稻栽培技术不断优化与改进, 水稻育秧及机插水平和种植方式的不断提高, 实际生产中已基本能够保障基本苗, 改变了以往因穗数不足限制产量提高的根本因素。同时, 科学合理的肥水管理利于优化群体质量, 成穗率较高, 穗数已不是限制产量提高的主要因子[11,13-14]。本研究中农民水平已达到7175.4 kg hm-2较高水平, 穗数与试验水平无显著差异, 但每穗粒数显著低于试验水平。通过合理的水肥管理, 提高水稻群体颖花量和结实率, 即每穗粒数成为高产的关键[15,16]。我们前期研究同样发现, 甬优1540实现高产到超高产是保障足够有效穗数的基础上, 通过增加每穗粒数来实现[17]

江淮地区小麦产量差异的主要原因是穗数和每穗粒数的不同, 其中穗数与产量间相关系数高于每穗粒数, 说明穗数对产量的增加效应要高于每穗粒数。千粒重受品种影响较大, 且与总粒数相互制约, 其对产量的贡献较弱。这与前人研究发现在英国、阿根廷、墨西哥、澳大利亚等地区, 小麦产量增加主要归于每穗粒数的提高结果不同[18,19]。主要是江淮地区稻茬小麦生产水平较低, 常常因为播种期降雨过多, 播期推迟影响出苗质量, 导致冬前有效分蘖少, 造成群体穗数较小, 大穗数少, 产量低下。通常增加1个或多个产量构成因子可以增产[20,21]。当前江淮地区不同产量水平水稻增产途径均依靠增加每穗粒数, 在足穗的基础上壮大穗, 提高每穗粒数是产量提高的有效途径。小麦增加穗数和每穗粒数均能增加产量, 但穗数具有优先性。

3.3 气候条件对江淮地区稻-麦生产潜在产量的影响

农业生产中光、温、水等气候资源对作物产量形成有非常重要的作用。前人研究发现, 辐射降低是华北地区冬小麦夏玉米潜在产量下降的主要因素[22]; 东北地区春玉米在年降水量小于500 mm的地区, 水分是限制玉米产量的主要限制因子[23]。本研究表明辐射和积温是影响江淮地区水稻产量的重要气象因素, 降雨不是造成江淮地区水稻产量差异的原因。水稻只有在最适宜温度下生长才能发挥出最大的潜在产量, 其产量与生育期累积截获辐射量呈显著正相关[24]。我们前期研究发现, 江淮地区水稻季辐射大于2387.0 MJ m-2, 累积积温达4003.4~4317.8℃ d, 总降水量在466.4~1588.9 mm范围内可获得10,000 kg hm-2以上的产量[25]。本研究中农户生产条件下, 降水平均为767 mm已满足需求, 辐射平均为2443 MJ m-2、积温平均为3919℃ d, 均处于比较低的范围内。可见, 水稻生育期累积辐射和积温较低是限制其产量进一步提高的关键因子。我们前期研究发现, 小麦季辐射在2685.0~3235.2 MJ m-2、积温在1925.0~ 2522.6℃ d、降水在245.5~439.5 mm范围内, 可获得8000 kg hm-2以上的产量[25]。本研究中农户生产条件下, 小麦季辐射和积温均已满足高产需求, 但降水达474.4 mm超过最适范围, 可见降水量过大、渍害严重是江淮地区稻茬小麦产量较低的主要原因。

3.4 江淮地区缩小稻-麦产量差的实现途径

大量的研究表明, 农户水平相对于试验水平有较大的产量差主要是由于农户在生产中缺乏理论指导和调控的针对性, 导致了较差的栽培管理水平和实际生产的盲目性, 这大大限制了作物产量的提高[26,27]。虽然过去栽培管理措施和技术进步对提高作物产量贡献巨大, 目前栽培管理措施改善的增产空间依然巨大[5,28]。本研究结果同样证明了江淮地区稻麦的产量潜力仍有较大的增长空间。因此, 如何进一步缩小产量差, 应作为当前粮食增产的主要途径[4]。根据本研究结果, 缩小水稻产量差主要依赖于增加每穗粒数, 解决小麦产量差靠穗数和每穗粒数的协同提高。合理高效的水肥管理、不同种植方式均能调控资源能促进作物群体结构优化, 增加花后物质生产, 提高收获指数和每穗粒数, 最终实现增产[29,30]。采用优化的种植模式、耕作和播种技术改进、适宜的播期和播量、抗逆栽培模式能有效提高小麦出苗质量, 提高最终穗数[31,32,33,34]

在周年生产条件下合理调配季节间的资源优化配置组合, 从而使温光资源利用最大化, 也是提升潜在产量的途径之一[2,35]。根据本研究结果, “强稻稳麦”是进一步提高江淮地区稻麦周年粮食生产的最有效途径, 如何发挥水稻季的高光效和高增产潜力成为关键[2]。通过选用生育期较长的水稻品种, 提高光温资源截获量[24], 采用周年适宜的稻麦品种搭配组合[36]、尤其是生育期长的晚熟高产水稻品种与耐迟播早熟高产小麦品种搭配, 均可优化周年光温水资源配置, 实现温光资源高效利用。同时水稻和小麦农耗期立足“抢收”、“抢种”, 保证茬口顺利衔接与温光资源“满负荷”利用, 实现稻麦产量和资源利用效率双提升。

4 结论

江淮地区稻-麦周年生产存在显著的产量差, 稻麦的产量潜力仍有较大的增长空间, 其中水稻的增产潜力大于小麦, 明确了“强稻稳麦”是提升地区粮食生产的有效途径。缩小水稻产量差主要依赖于增加穗粒数, 缩小小麦产量差靠穗数和穗粒数的协同提高。生育期累积辐射和积温较低是影响水稻产量差异的主要气候因素, 而生育期降水过多是影响小麦产量差异的主要气候因素。

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