• 《中国科学引文数据库(CSCD)》来源期刊
  • 中国科技期刊引证报告(核心版)期刊
  • 《中文核心期刊要目总览》核心期刊
  • RCCSE中国核心学术期刊

稻米饭粒延伸性的研究进展

符雨, 赵宏源, 肖梦楠, 张桂权, 王少奎

符雨, 赵宏源, 肖梦楠, 等. 稻米饭粒延伸性的研究进展[J]. 华南农业大学学报, 2023, 44(5): 670-678. DOI: 10.7671/j.issn.1001-411X.202302012
引用本文: 符雨, 赵宏源, 肖梦楠, 等. 稻米饭粒延伸性的研究进展[J]. 华南农业大学学报, 2023, 44(5): 670-678. DOI: 10.7671/j.issn.1001-411X.202302012
FU Yu, ZHAO Hongyuan, XIAO Mengnan, et al. Research progress on elongation of cooked rice[J]. Journal of South China Agricultural University, 2023, 44(5): 670-678. DOI: 10.7671/j.issn.1001-411X.202302012
Citation: FU Yu, ZHAO Hongyuan, XIAO Mengnan, et al. Research progress on elongation of cooked rice[J]. Journal of South China Agricultural University, 2023, 44(5): 670-678. DOI: 10.7671/j.issn.1001-411X.202302012

稻米饭粒延伸性的研究进展

基金项目: 广东省基础与应用基础研究重大项目(2019B030302006);岭南现代农业科学与技术广东省实验室开放课题(NT2021001);国家自然科学基金(32072040);海南省自然科学基金(320MS079)
详细信息
    作者简介:

    符 雨,博士研究生,主要从事水稻饭粒延伸性研究,E-mail: fy18279499075@163.com

    通讯作者:

    王少奎,教授,博士,主要从事水稻重要农艺性状功能基因的鉴定、功能研究以及设计育种应用等研究,E-mail: shaokuiwang@scau.edu.cn

  • 中图分类号: S511;S330.2;Q37

Research progress on elongation of cooked rice

Article Text (iFLYTEK Translation)
  • 摘要:

    水稻饭粒延伸性是指米粒蒸煮时的延伸特性,用蒸煮后米粒长度增加值与蒸煮前米粒长度的比值来衡量,是评价稻米蒸煮食味品质的重要指标之一。随着现代遗传学及基因组学相关理论和育种技术的发展,人们对水稻饭粒延伸性的遗传研究也日趋深入。本文综述了影响水稻饭粒延伸性的相关因素及其遗传研究进展,指出了水稻饭粒延伸性遗传研究目前存在的主要问题,分析了水稻饭粒延伸性遗传研究的应用前景。

    Abstract:

    Cooked rice elongation (CRE) refers to the elongation characteristics of rice grains during cooking, is evaluated by the ratio of the added value of rice grain length after cooking to the length of rice grain before cooking. It is one of the important indicators of cooking and eating quality. With the development of modern genetics and genomics related theories and breeding technology, the genetic research of CRE has also become increasingly in-depth. In this paper, the related factors affecting CRE and the main progress of genetic research on CRE were summarized, the existing problems of genetic research on CRE were also pointed out, and the prospects of genetic research on CRE were analyzed.

  • 甲烷(CH4)是一种主要的温室气体,稻田CH4排放量占全球温室气体总产生量的19%[]。合理的灌溉和施肥等管理技术对稻田CH4减排有重要作用。目前稻田节水灌溉方式有“薄浅湿晒”灌溉、干湿交替灌溉等,干湿交替灌溉稻田的CH4排放量较常规灌溉和“薄浅湿晒”灌溉低[]。与常规灌溉相比,“薄浅湿晒”灌溉可使稻田CH4排放量显著减少12.6%~44.9%[],干湿交替灌溉可使稻田CH4累积排放量显著降低37%[]。施氮量也会影响稻田CH4排放[],但是施氮量对稻田CH4排放量影响的研究结果不一致。有研究表明,相对于不施氮肥,高无机氮处理(249 kg·hm−2)稻田CH4排放量降低15%[];但也有研究发现,随着尿素用量的增加,稻田CH4排放量随之增加[]。除了施氮量,不同生育时期施氮比例也会影响稻田CH4排放,基肥、分蘖肥、穗肥和粒肥施氮比例为4.5∶2∶1.5∶2的稻田CH4排放量低于施氮比例为5∶2.5∶1∶1.5和4∶2∶2∶2的[]。不同灌溉方式及施氮量条件下,土壤易氧化有机碳、微生物量碳以及甲烷氧化菌可直接影响稻田CH4排放[],且稻田CH4排放通量与土壤可溶性有机碳和微生物量碳含量呈正相关关系[],而甲烷氧化菌则会降低稻田CH4排放量[]。本研究通过3种灌溉方式和3种氮肥处理(氮肥用量与基、追肥比例结合)早、晚稻田间试验,研究双季稻不同生育期稻田CH4排放通量、土壤有机碳组分含量以及甲烷氧化菌数量的变化,分析稻田CH4排放通量与土壤有机碳组分含量和甲烷氧化菌数量之间的关系,以期获得稻田CH4减排的水氮管理模式,并揭示土壤有机碳组分含量和甲烷氧化菌数量对稻田CH4排放通量的影响规律。

    2016年7月至2017年7月在南宁市灌溉试验站(N22°52′58.33″,E108°17′38.86″)进行双季稻大田试验。试验所用土壤为第四纪红色黏土发育的水稻土,土壤理化特征如下:饱和含水率49.2%,容重1.2 g·cm−3,有机碳26.9 g·kg−1,全氮1.3 g·kg−1,碱解氮113.6 mg·kg−1,有效磷50.0 mg·kg−1,速效钾110.6 mg·kg−1,pH 7.6。试验期间早稻在分蘖期、孕穗期、乳熟期和成熟期的降雨量分别为186.3、83.0、97.7和222.3 mm,晚稻分别为619.2、6.4、81.0和7.8 mm。早稻和晚稻品种均为‘内5优8015’,为广西本地优良三系杂交水稻品种。

    试验设3种灌溉方式和3种氮肥处理,完全随机设计,共9个处理。每个处理设3个小区,共27个小区。每个小区面积25 m2,小区之间用25 cm厚红砖水泥墙隔离分开,以保证小区之间水分相互不侧渗和各小区独立灌排水,并安装水表记录每次灌溉量。

    3种灌溉方式包括常规灌溉、“薄浅湿晒”灌溉和干湿交替灌溉。常规灌溉是在移栽返青期以及分蘖期到乳熟期田间均保持20~30 mm水层,但分蘖后期和成熟期仅保持土壤湿润。“薄浅湿晒”灌溉在移栽返青期保持20~40 mm水层,分蘖前期仅保持土壤湿润,分蘖后期由湿润状态自然落干至土壤干燥状态并继续晒田,孕穗期及乳熟期仅保持10 mm左右水层,成熟期晒田。干湿交替灌溉是在各小区均安装TEN45水分张力计(南京土壤仪器公司)监测土壤水势的变化,移栽后10 d内田间保持10~20 mm水层,7 d后进行干湿交替灌溉,即当土壤水势为−15 kPa时,灌溉20 mm,再自然落干至土壤水势为−15 kPa,再灌溉20 mm,如此循环,至水稻成熟。详细水分控制方法见本研究的前期工作报道[, ]

    3种施氮处理包括N1:120 kg·hm−2氮(20%基肥80%追肥),N2:120 kg·hm−2氮(50%基肥50%追肥),N3:90 kg·hm−2氮(50%基肥50%追肥)。所用肥料为:尿素(氮质量分数为46%)、过磷酸钙(P2O5质量分数为12%)和氯化钾(K2O质量分数为60%)。各处理P2O5用量为60 kg·hm−2,K2O用量为120 kg·hm−2,其中,全部过磷酸钙和50%氯化钾作基肥,在插秧前1 d耕地时施入土壤中,余下的50%氯化钾分别以分蘖肥和穗肥均按25%的比例施入土壤中。

    晚稻试验于2016年7月4日播种,8月1日选取长势均匀的秧苗单株栽培,株行距为20 cm×20 cm,8月16日施分蘖肥,9月13日开始晒田,9月22日复水后施穗肥,11月8日收割。生育期内“薄浅湿晒”灌溉、干湿交替灌溉和常规灌溉平均灌溉量分别为157.8、130.8和227.9 mm。整个生育期为99 d。

    早稻试验于2017年3月10日播种,4月12日选取长势均匀的秧苗单株栽培,株行距为20 cm×20 cm,4月16日施分蘖肥,5月27日开始晒田,6月3日复水后施穗肥,7月18日收割。生育期内“薄浅湿晒”灌溉、干湿交替灌溉和常规灌溉平均灌溉量分别为107.3、79.6和157.4 mm。整个生育期为95 d。

    分别于晚稻移栽后37(分蘖期)、63(孕穗期)、77(乳熟期)和98 d(成熟期),早稻移栽后24(分蘖期)、64(孕穗期)、74(乳熟期)和94 d(成熟期)用静态箱法采集稻田CH4气体[]。稻田CH4排放通量的测定用Agilent 7890A气相色谱仪(美国安捷伦科技有限公司),检测器为氢火焰离子检测器(FID),采用填充柱,当检测器温度升至350 ℃且基线平稳时,开始测样。CH4通量的计算参考王明星[]的方法。

    在晚稻和早稻各生育期采集稻田CH4,同时在各小区按五点法采集0~20 cm耕层土壤样品,测定土壤微生物量碳、可溶性有机碳、易氧化有机碳含量和甲烷氧化菌数量。

    微生物量碳含量测定用氯仿熏蒸–硫酸钾浸提法–总有机碳法[],可溶性有机碳含量测定用无氯仿熏蒸–硫酸钾浸提–总有机碳法[],易氧化有机碳含量测定用高锰酸钾氧化–分光光度计法[],甲烷氧化菌数量测定用培养基–滚管法[]

    数据整理和分析采用DPS 12.26和ExceL 2003软件,结果用3次重复的平均值±标准误表示。用Duncan’s多重比较法分析各处理指标间的差异显著性(P<0.05),将稻田CH4排放通量与土壤有机碳组分含量和甲烷氧化菌数量进行相关性分析。

    不同处理下双季稻田CH4排放通量随生育期的变化如图1所示,CH4排放通量在分蘖期较高,在孕穗期和乳熟期较低,在成熟期几乎为0。3种灌溉方式下,CH4在晚稻分蘖期集中排放,不同氮肥处理间CH4排放通量为N1>N2>N3。N3处理下,干湿交替灌溉稻田CH4排放通量在晚稻分蘖期、孕穗期和乳熟期较常规灌溉分别降低53.5%、99.4%和99.2%,在早稻分蘖期、孕穗期和乳熟期较常规灌溉分别降低19.9%、29.2%和63.9%。从图1可看出,在N1、N2和N3处理下,干湿交替灌溉双季稻田CH4排放通量均低于“薄浅湿晒”灌溉和常规灌溉,而在相同灌溉方式下,N3处理稻田CH4排放通量较N1、N2降低;因此,干湿交替灌溉N3处理稻田CH4排放通量最低。

    图 1 不同处理各生育期双季稻田CH4排放通量
    图  1  不同处理各生育期双季稻田CH4排放通量
    N1:120 kg·hm−2氮(20%基肥80%追肥),N2:120 kg·hm−2氮(50%基肥50%追肥),N3:90 kg·hm−2氮(50%基肥50%追肥);TS:分蘖期,BS:孕穗期,MS:乳熟期,RS:成熟期
    Figure  1.  CH4 emission fluxes from double-cropping paddy field at each growth stage in different treatments
    N1: 120 kg·hm−2 nitrogen (20% basal fertilizer and 80% topdressing), N2: 120 kg·hm−2 nitrogen (50% base fertilizer and 50% topdressing), N3: 90 kg·hm−2 nitrogen (50% basal fertilizer and 50% topdressing); TS: Tillering stage, BS: Booting stage, MS: Milk stage, RS: Ripening stage

    表1可知,不同处理下双季稻田整个生育期土壤微生物量碳在0.08~0.23 g·kg−1范围内变化,以乳熟期较高。在“薄浅湿晒”灌溉下,晚稻分蘖期、孕穗期和乳熟期以及早稻4个生育期N2处理土壤微生物量碳均较高于N1和N3处理。干湿交替灌溉下,晚稻孕穗期和成熟期以及早稻4个生育时期N2处理土壤微生物量碳均高于N1和N3处理,其中早稻孕穗期、乳熟期和成熟期N2处理较N1处理分别增加23.5%、27.8%和20.0%,早稻孕穗期和乳熟期N2处理较N3处理分别增加23.5%和27.8%。常规灌溉下,晚稻土壤微生物量碳在分蘖期、孕穗期和乳熟期以N2处理较高,乳熟期N2处理较N1和N3处理均增加21.0%。早稻分蘖期、乳熟期和成熟期N2处理均高于N1和N3处理,其中乳熟期和成熟期较N1处理分别增加50.0%和75.0%,成熟期较N3处理增加27.3%。3种氮肥处理下,常规灌溉早稻土壤微生物量碳均低于“薄浅湿晒”灌溉及干湿交替灌溉。因此在相同灌溉方式下,N2处理稻田土壤微生物量碳高于N1和N3处理;在相同氮肥处理下,常规灌溉早稻土壤微生物量碳低于“薄浅湿晒”灌溉和干湿交替灌溉。

    表  1  不同处理各生育期土壤微生物量碳含量1)
    Table  1.  Soil microbial biomass carbon contents at each growth stage in different treatments w/(g·kg−1)
    施氮处理
    Nitrogen treatment
    灌溉方式
    Irrigation method
    晚稻 Late rice 早稻 Early rice
    TS BS MS RS TS BS MS RS
    N1 BG 0.15±0.01b 0.17±0.01ab 0.17±0.01b 0.17±0.01ab 0.16±0.01ab 0.17±0.01bc 0.18±0.01bc 0.15±0.01b
    GG 0.17±0.02ab 0.17±0.01ab 0.17±0.01b 0.17±0.01ab 0.17±0.02ab 0.17±0.01bc 0.18±0.01bc 0.15±0.01b
    CG 0.17±0.04ab 0.19±0.01ab 0.19±0.01b 0.16±0.01ab 0.14±0.02b 0.12±0.01d 0.12±0.01d 0.08±0.01c
    N2 BG 0.18±0.01ab 0.18±0.01ab 0.19±0.01b 0.17±0.01ab 0.19±0.01a 0.19±0.01ab 0.20±0.01b 0.18±0.01a
    GG 0.19±0.01ab 0.18±0.01ab 0.18±0.01b 0.20±0.03a 0.20±0.01a 0.21±0.01a 0.23±0.01a 0.18±0.01a
    CG 0.21±0.02a 0.21±0.02a 0.23±0.02a 0.15±0.02bc 0.17±0.01ab 0.14±0.01cd 0.18±0.01bc 0.14±0.02b
    N3 BG 0.17±0.01ab 0.18±0.01ab 0.18±0.01b 0.17±0.01ab 0.17±0.02ab 0.17±0.01bc 0.18±0.01b 0.16±0.01ab
    GG 0.19±0.01ab 0.18±0.01ab 0.17±0.01b 0.17±0.01ab 0.18±0.01a 0.17±0.01bc 0.18±0.01bc 0.16±0.01ab
    CG 0.17±0.01ab 0.20±0.01ab 0.19±0.01b 0.11±0.02c 0.16±0.01ab 0.14±0.02cd 0.16±0.01c 0.11±0.02c
     1)N1:120 kg·hm−2氮(20%基肥80%追肥),N2:120 kg·hm−2氮(50%基肥50%追肥),N3:90 kg·hm−2氮(50%基肥50%追肥);BG:“薄浅湿晒”灌溉,GG:干湿交替灌溉,CG:传统灌溉;TS:分蘖期,BS:孕穗期,MS:乳熟期,RS:成熟期;同列数据后不同小写字母表示处理间差异显著(P<0.05,Duncan’s法)
     1) N1: 120 kg·hm−2 nitrogen (20% basal fertilizer and 80% topdressing), N2: 120 kg·hm−2 nitrogen (50% base fertilizer and 50% topdressing), N3: 90 kg·hm−2 nitrogen (50% basal fertilizer and 50% topdressing); BG: “Thin-shallow-wet-dry” irrigation, GG: Alternate drying and wetting irrigation, CG: Conventional irrigation; TS: Tillering stage, BS: Booting stage, MS: Milk stage, RS: Ripening stage; Different lowercase letters in the same column indicate significant differences among different treatments (P<0.05, Duncan’s method)
    下载: 导出CSV 
    | 显示表格

    表2可知,不同处理双季稻田整个生育期土壤可溶性有机碳含量在45.6~106.3 mg·kg−1范围内变化。“薄浅湿晒”灌溉下,晚稻4个生育期及早稻孕穗期、乳熟期和成熟期N3处理土壤可溶性有机碳含量均大于N1和N2处理,其中晚稻乳熟期N3处理较N1和N2处理分别增加23.8%和22.5%。干湿交替灌溉下,晚稻分蘖期、乳熟期和成熟期N3处理土壤可溶性有机碳含量较N1处理分别增加12.0%、12.6%和13.3%,同时较N2处理分别增加12.9%、18.0%和11.8%;早稻乳熟期和成熟期N3处理土壤可溶性有机碳含量较N1处理分别增加36.2%和42.1%,较N2处理分别增加25.4%和36.4%。常规灌溉方式下,晚稻乳熟期和成熟期N3处理土壤可溶性有机碳含量较N1处理分别增加9.6%和21.3%,乳熟期较N1、N2处理分别增加9.6%和6.6%。在3种氮肥处理下,不同灌溉方式对稻田土壤可溶性有机碳含量影响顺序为干湿交替灌溉>“薄浅湿晒”灌溉>常规灌溉,早稻田在分蘖期及孕穗期以干湿交替灌溉土壤可溶性有机碳含量最高,在乳熟期及成熟期以“薄浅湿晒”灌溉土壤可溶性有机碳含量最高。因此,相同灌溉方式下,双季稻田N3处理土壤可溶性有机碳含量均大于N1和N2处理;相同氮肥处理下,干湿交替灌溉土壤可溶性有机碳含量较高。

    表  2  不同处理各生育期土壤可溶性有机碳含量
    Table  2.  Soil soluble organic carbon contents at each growth stage in different treatments w/(mg·kg−1)
    施氮处理
    Nitrogen
    treatment
    灌溉方式
    Irrigation
    method
    晚稻 Late rice 早稻 Early rice
    TS BS MS RS TS BS MS RS
    N1 BG 80.1±5.2d 83.2±3.5abc 82.3±1.2c 61.1±2.0bc 86.9±5.6a 84.8±4.9ab 88.5±6.3abc 64.2±8.6abc
    GG 92.8±1.2bc 89.5±3.4a 89.0±2.2b 61.1±3.1bc 89.5±11.6a 84.9±21.9ab 77.1±6.4c 54.9±10.4c
    CG 92.6±5.5bc 73.6±5.4c 73.6±2.0e 45.6±3.2d 85.0±15.5a 74.9±15.9b 83.1±4.9bc 62.9±5.0abc
    N2 BG 84.6±2.0cd 82.7±4.9abc 83.2±4.4c 58.9±3.1bc 88.2±10.3a 70.9±6.1b 97.2±13.5ab 71.6±4.7ab
    GG 92.0±0.1bc 84.2±3.1ab 84.9±3.1bc 61.9±1.3bc 94.7±38.3a 87.6±13.9ab 83.7±2.4bc 57.2±1.9bc
    CG 90.6±3.0bc 76.4±2.2bc 75.7±1.9de 46.9±4.8d 92.5±13.9a 77.6±4.2ab 70.4±8.1c 49.8±5.1c
    N3 BG 85.4±4.1cd 87.2±6.7a 101.9±3.0a 66.6±5.0ab 71.3±31.4a 87.6±4.8ab 106.3±6.7a 78.3±6.2a
    GG 103.9±2.4a 89.5±2.3a 100.2±3.9a 69.2±2.5a 102.9±19.2a 99.1±17.2a 105.0±6.2a 78.0±4.7a
    CG 99.2±6.7ab 79.5±2.0abc 80.7±4.3cd 55.3±3.1c 96.6±9.6a 93.7±3.7ab 89.1±5.8abc 71.1±4.6ab
     1) N1:120 kg·hm−2氮(20%基肥80%追肥),N2:120 kg·hm−2氮(50%基肥50%追肥),N3:90 kg·hm−2氮(50%基肥50%追肥);BG:“薄浅湿晒”灌溉,GG:干湿交替灌溉,CG:传统灌溉;TS:分蘖期,BS:孕穗期,MS:乳熟期,RS:成熟期;同列数据后不同小写字母表示处理间差异显著(P<0.05,Duncan’s法)
     1) N1: 120 kg·hm−2 nitrogen (20% basal fertilizer and 80% topdressing), N2: 120 kg·hm−2 nitrogen (50% base fertilizer and 50% topdressing), N3: 90 kg·hm−2 nitrogen ( 50% basal fertilizer and 50% topdressing); BG: “Thin-shallow-wet-dry” irrigation, GG: Alternate drying and wetting irrigation, CG: Conventional irrigation; TS: Tillering stage, BS: Booting stage, MS: Milk stage, RS: Ripening stage; Different lowercase letters in the same column indicate significant differences among different treatments (P<0.05, Duncan’s method)
    下载: 导出CSV 
    | 显示表格

    表3可以看出,不同处理晚稻田土壤易氧化有机碳含量在1.08~7.10 g·kg−1范围内变化。N1处理下,晚稻分蘖期和孕穗期以及早稻分蘖期、孕穗期和成熟期常规灌溉土壤易氧化有机碳含量均大于“薄浅湿晒”灌溉和干湿交替灌溉;常规灌溉土壤易氧化有机碳含量在早稻孕穗期较“薄浅湿晒”灌溉增加47.7%,在成熟期较“薄浅湿晒”灌溉和干湿交替灌溉方式分别增加93.5%和61.3%。N2处理下,除晚稻乳熟期外,常规灌溉双季稻各生育期土壤易氧化有机碳含量均大于“薄浅湿晒”灌溉和干湿交替灌溉;常规灌溉土壤易氧化有机碳含量在晚稻孕穗期和成熟期较“薄浅湿晒”灌溉分别增加50.2%和34.5%,在早稻乳熟期增加27.1%。N3处理下,常规灌溉土壤易氧化有机碳含量在早稻分蘖期较干湿交替灌溉增加115.9%,在早稻孕穗期较“薄浅湿晒”灌溉和干湿交替灌溉分别增加38.8%和40.9%;在“薄浅湿晒”和干湿交替灌溉下,不同氮肥处理之间土壤易氧化有机碳含量没有明显变化规律,在常规灌溉下,除早稻孕穗期、乳熟期及成熟期外,土壤易氧化有机碳含量均是N2>N1>N3。因此,相同氮肥处理下,常规灌溉土壤易氧化有机碳含量较“薄浅湿晒”灌溉和干湿交替灌溉增加。

    表  3  不同处理各生育期土壤易氧化有机碳含量
    Table  3.  Soil readily oxidizable organic carbon contents at each growth stage in different treatments w/(g·kg−1)
    施氮处理
    Nitrogen
    treatment
    灌溉方式
    Irrigation
    method
    晚稻 Late rice 早稻 Early rice
    TS BS MS RS TS BS MS RS
    N1 BG 4.53±1.66ab 3.55±0.21ab 4.65±0.58a 5.74±0.60a 2.41±0.39d 3.08±0.29d 4.48±0.42abc 1.70±0.44b
    GG 1.08±0.13b 3.82±0.34ab 5.30±0.38a 4.70±0.20bc 2.81±0.17d 3.82±0.34bcd 5.11±0.36a 2.04±0.48b
    CG 6.48±1.65ab 4.33±0.28ab 5.13±0.31a 5.31±0.12ab 3.67±1.17bcd 4.55±0.23abc 5.06±0.26a 3.29±0.61a
    N2 BG 4.18±2.84ab 3.05±0.25b 5.27±0.40a 4.12±0.37c 4.74±1.33abcd 4.13±0.12abcd 3.95±0.25bc 1.86±0.32b
    GG 3.08±1.52ab 4.34±0.65ab 5.57±0.35a 4.52±0.10bc 4.62±1.00abcd 4.15±0.24abcd 4.84±0.20ab 2.23±0.34ab
    CG 7.10±0.79a 4.58±0.66a 5.51±0.32a 5.54±0.18ab 7.25±0.67a 5.12±0.18a 5.02±0.12a 2.71±0.37ab
    N3 BG 3.68±1.89ab 4.34±0.65ab 5.94±0.51a 4.79±0.40abc 5.65±1.23abc 3.40±0.86cd 5.15±0.08a 1.55±0.21b
    GG 5.02±1.79ab 4.34±0.25ab 4.76±0.18a 4.10±0.17c 2.96±0.15cd 3.35±0.29cd 3.77±0.56c 1.74±0.19b
    CG 6.27±1.95ab 3.62±0.18ab 4.59±0.51a 4.73±0.32abc 6.39±0.28ab 4.72±0.41ab 4.24±0.20abc 2.31±0.16ab
     1) N1:120 kg·hm−2氮(20%基肥80%追肥),N2:120 kg·hm−2氮(50%基肥50%追肥),N3:90 kg·hm−2氮(50%基肥50%追肥);BG:“薄浅湿晒”灌溉,GG:干湿交替灌溉,CG:传统灌溉;TS:分蘖期,BS:孕穗期,MS:乳熟期,RS:成熟期;同列数据后不同小写字母表示处理间差异显著(P<0.05,Duncan’s法)
     1) N1: 120 kg·hm−2 nitrogen (20% basal fertilizer and 80% topdressing), N2: 120 kg·hm−2 nitrogen (50% base fertilizer and 50% topdressing), N3: 90 kg·hm−2 nitrogen (50% basal fertilizer and 50% topdressing); BG: “Thin-shallow-wet-dry” irrigation, GG: Alternate drying and wetting irrigation, CG: Conventional irrigation; TS: Tillering stage, BS: Booting stage, MS: Milk stage, RS: Ripening stage; Different lowercase letters in the same column indicate significant differences among different treatments (P<0.05, Duncan’s method)
    下载: 导出CSV 
    | 显示表格

    图2所示,不同处理晚稻各生育期土壤甲烷氧化菌数量变化范围为1.64×106~12.98×106 cfu·g−1,早稻为1.63×106~23.50×106 cfu·g−1。在N1处理下,常规灌溉土壤甲烷氧化菌数量在晚稻成熟期以及早稻孕穗期、乳熟期和成熟期均大于干湿交替灌溉和“薄浅湿晒”灌溉。在N3处理下,常规灌溉土壤甲烷氧化菌数量在早稻孕穗期和乳熟期较“薄浅湿晒”灌溉分别增加419.2%和457.8%。在N2处理下,干湿交替灌溉土壤甲烷氧化菌数量在双季稻4个生育期均低于“薄浅湿晒”灌溉和常规灌溉,在晚稻分蘖期较“薄浅湿晒”灌溉方式减少76.0%,在孕穗期和乳熟期较常规灌溉方式分别减少77.2%和77.3%;在早稻分蘖期较“薄浅湿晒”灌溉减少76.6%,在孕穗期、乳熟期和成熟期较常规灌溉方式分别减少87.7%、86.2%和57.9%。在N1处理下,“薄浅湿晒”灌溉土壤甲烷氧化菌数量在晚稻分蘖期、孕穗期和乳熟期均大于干湿交替灌溉和常规灌溉,其中在孕穗期较干湿交替灌溉方式增加136.5%;在早稻分蘖期和乳熟期也较干湿交替灌溉和常规灌溉大。在3种灌溉方式下,3种氮肥处理土壤甲烷氧化菌数量没有明显变化规律。因此,相同氮肥处理下,干湿交替灌溉土壤甲烷氧化菌数量较“薄浅湿晒”灌溉和常规灌溉低。

    图 2 不同处理各生育期土壤甲烷氧化菌数量
    图  2  不同处理各生育期土壤甲烷氧化菌数量
    N1:120 kg·hm−2氮(20%基肥80%追肥),N2:120 kg·hm−2氮(50%基肥50%追肥),N3:90 kg·hm−2氮(50%基肥50%追肥);TS:分蘖期,BS:孕穗期,MS:乳熟期,RS:成熟期
    Figure  2.  Soil methane oxidizing bacteria population amounts at each growth stage in different treatments
    N1: 120 kg·hm−2 nitrogen (20% basal fertilizer and 80% topdressing), N2: 120 kg·hm−2 nitrogen (50% base fertilizer and 50% topdressing), N3: 90 kg·hm−2 nitrogen (50% basal fertilizer and 50% topdressing); TS: Tillering stage, BS: Booting stage, MS: Milk stage, RS: Ripening stage

    表4可知,晚稻田CH4排放通量与土壤可溶性有机碳含量之间呈极显著正相关(r=0.55,P<0.01),早稻田CH4排放通量与土壤可溶性有机碳和土壤易氧化有机碳含量之间呈显著正相关,双季稻田CH4排放通量与土壤微生物量碳和甲烷氧化菌数量之间的关系均不显著;因此,土壤可溶性有机碳是影响稻田CH4排放通量的主要因素。

    表  4  双季稻田CH4排放通量与土壤有机碳组分和甲烷氧化菌相关性分析1)
    Table  4.  Correlation analyses of CH4 emission flux with soil organic carbon fraction and methane oxidizing bacteria
    稻季
    Rice season
    微生物量碳含量
    Microbial biomass
    carbon content
    可溶性有机碳含量
    Soluble organic
    carbon content
    易氧化有机碳含量
    Readily oxidizable organic
    carbon content
    甲烷氧化菌数量
    Methane oxidizing
    bacteria number
    晚稻 Late rice 0.31 0.55** 0.25 0.12
    早稻 Early rice 0.22 0.34* 0.42* −0.04
     1)“*”、“**”分别表示在0.05、0.01水平显著相关
     1)“*”, “**” indicate significant correlation at 0.05 and 0.01 levels respectively
    下载: 导出CSV 
    | 显示表格

    在水稻整个生育期内稻田CH4集中在分蘖期排放,原因可能是在水稻生长初期,刚淹水后土壤中的有机质剧烈分解,导致土壤中有较多的CH4产生[],而后期随着有效氮素的消耗减少,微生物缺乏基质和能源使稻田CH4排放减少。有研究认为,水层深度和CH4排放通量有很强的负相关关系,水层深度通过影响厌氧环境和水温水量控制水稻根系和根系分泌物数量,而这些物质将为CH4产生提供底物[]

    相同氮肥处理下,相对于干湿交替灌溉,常规灌溉和“薄浅湿晒”灌溉稻田CH4排放通量降低时间较晚;是因为干湿交替灌溉破坏土壤产甲烷菌的生存环境,CH4产生土层随水分降低而下降,待重新灌溉后需一段时间恢复[],而且干湿交替灌溉灌溉频率较低,导致稻田CH4排放通量降低时间较早。成熟期土壤中CH4的产生可能与根系渗出物和根系的腐烂有关[]

    氮肥施入增加土壤中氮素有效性,会相应地提高产甲烷菌所需有机底物有效性,使得产甲烷菌有较多可利用底物,增加CH4排放量[]。总体来说,在相同灌溉方式下,N3处理稻田CH4排放通量较N1和N2处理低,可能是因为N1和N2处理能刺激更多微生物生长繁殖,改变土壤有机质含量,增加根系分泌物数量等,为CH4生成提供底物[]。但有研究表明施入尿素使稻田CH4排放通量减少[],可能与稻田土壤理化性质有关,因为低氮水平增施氮肥刺激土壤有机底物生成,高氮会形成长期氮肥输入,增加土壤酸度,抑制微生物活性和CH4的产生[]

    不同灌溉、氮肥处理下土壤微生物量碳含量在分蘖期较低,在孕穗期较高,之后降低,与Banerjee等[]在单施氮、磷、钾肥处理的结果一致。相同灌溉方式下,N2处理土壤微生物量碳较N3高,史登林等[]在减量施氮40%条件下有相似的结果;这是因为增施氮肥可以为土壤微生物提供营养物质,促进其生长,进而增加土壤微生物量碳含量[]

    3种灌溉方式和3种氮肥处理下,双季稻田土壤可溶性有机碳含量在分蘖期、孕穗期及乳熟期没有明显差异,但是在成熟期均减少;原因可能是土壤可溶性有机碳是土壤中微生物生活的重要物质及能量来源,当水稻生长前期淹水灌溉时,土壤中可溶性有机质分解,导致土壤可溶性有机碳含量升高,从而微生物数量增多,相应所需的土壤可溶性有机碳更多,土壤可溶性有机碳含量减少,因而形成一个稳定的体系[]。在成熟期,追施氮肥较多,再加上甲烷氧化菌呼吸作用增强,充分利用剩余碳素,使土壤可溶性有机碳相对减少。相同灌溉方式下,N3处理双季稻田土壤可溶性有机碳含量大于N1及N2处理,说明相同灌溉方式下,低氮较高氮更有利于提高稻田土壤可溶性有机碳含量,这与前人在减量施氮40%处理下得到的结果相似[]。相同施氮处理下,虽然不同灌溉方式的稻田土壤可溶性碳含量在不同生育期内有波动,但总体上以干湿交替灌溉较高。

    N1处理干湿交替灌溉晚稻田土壤易氧化有机碳含量较少,可能是因为干湿交替灌溉土壤通透性高,微生物活性增强,加之易分解,所以含量较少[]。N2处理常规灌溉土壤易氧化有机碳含量较高,可能是因为常规灌溉使微生物活性减弱,土壤易氧化有机碳被利用量减少,从而为土壤易氧化有机碳的移动提供便利条件。

    土壤可溶性有机碳含量和稻田CH4排放通量有相同的变化趋势,因此,双季稻田CH4排放通量与土壤可溶性有机碳含量呈显著正相关,表明稻田土壤可溶性有机碳含量的高低可以间接反映稻田CH4排放量大小。

    干湿交替灌溉土壤甲烷氧化菌数量较“薄浅湿晒”灌溉和常规灌溉少,原因可能是干湿交替灌溉土壤环境不适合甲烷氧化菌生存。N1和N2处理下,总体上“薄浅湿晒”灌溉土壤甲烷氧化菌数量较大,因为“薄浅湿晒”灌溉不仅满足稻田水分需求,且比常规灌溉有良好的土壤通气性,有利于土壤甲烷氧化菌的生存[]。但也有研究表明CH4氧化过程也可能在厌氧环境中,是产CH4过程的逆向代谢[]

    晚稻分蘖期N3(90 kg·hm−2氮,50%基肥和50%追肥)处理干湿交替灌溉稻田CH4排放通量较其他灌溉方式低,而土壤可溶性有机碳含量较其他灌溉方式高。双季稻田CH4排放通量仅与土壤可溶性有机碳含量呈显著正相关,其中,晚稻田相关系数为0.55,早稻田相关系数为0.34。因此,土壤可溶性有机碳含量显著影响双季稻田CH4排放通量,且在供试土壤和栽培管理条件下,干湿交替灌溉N3处理稻田CH4排放通量较低。

  • 图  1   稻米饭粒延伸性

    Figure  1.   Cooked rice elongation

    图  2   部分已鉴定的水稻饭粒延伸性QTLs

    Chr.:染色体;黑色、红色和绿色条块分别代表饭粒延伸性、饭粒伸长率和米粒延伸指数的QTL,条块位置代表QTL的估计位置;蓝色为已克隆淀粉相关基因的物理位置

    Figure  2.   Partial identified QTLs for cooked rice elongation

    Chr.: Chromosome; The bars in black, red, and green represent QTLs for cooked rice elongation, cooked rice elongation rate, and rice grain elongation index, respectively, the location of the bar represents the estimated location of the QTL; Blue is the physical location of the cloned starch-related genes

    图  3   水稻饭粒延伸性QTL聚合系

    Figure  3.   Pyramiding lines of cooked rice elongation QTL

  • [1]

    SINGH N, KAUR L, SODHI N S, et al. Physicochemical, cooking and textural properties of milled rice from different Indian rice cultivars[J]. Food Chemistry, 2005, 89(2): 253-259. doi: 10.1016/j.foodchem.2004.02.032

    [2] 张桂权. 5G水稻的演变和发展[J]. 华南农业大学学报, 2019, 40(5): 211-216. doi: 10.7671/j.issn.1001-411X.201905075
    [3] 袁隆平. 超级杂交水稻育种研究新进展[J]. 中国农村科技, 2010(Z1): 24-25. doi: 10.3969/j.issn.1005-9768.2010.02.006
    [4] 方志强, 陆展华, 王石光, 等. 稻米品质性状研究进展与应用[J]. 广东农业科学, 2020, 47(5): 11-20. doi: 10.16768/j.issn.1004-874X.2020.05.002
    [5] 莫惠栋. 我国稻米品质的改良[J]. 中国农业科学, 1993, 26(4): 8-14.
    [6] 王慧, 张从合, 陈金节, 等. 稻米品质性状影响因素及相关基因研究进展[J]. 中国稻米, 2018, 24(4): 16-21. doi: 10.3969/j.issn.1006-8082.2018.04.004
    [7] 程鸿燕, 韩渊怀. 大米食味品质的研究及其育种进展[J]. 山西农业大学学报(自然科学版), 2016, 36(12): 890-896. doi: 10.13842/j.cnki.issn1671-8151.2016.12.023
    [8]

    DOU Z, TANG S, CHEN W, et al. Effects of open-field warming during grain-filling stage on grain quality of two japonica rice cultivars in lower reaches of Yangtze River delta[J]. Journal of Cereal Science, 2018, 81: 118-126. doi: 10.1016/j.jcs.2018.04.004

    [9] 何予卿, 邢永忠, 葛小佳, 等. 水稻米饭延伸指数相关性状的基因定位研究[J]. 分子植物育种, 2003, 1(5/6): 613-619. doi: 10.3969/j.issn.1672-416X.2003.05.004
    [10]

    KHUSH G S, PAULE C M, CRUZ N D. Rice grain quality evaluation and improvement at IRRI[M]//Chemical Aspects of Rice Grain Quality. Los Baños, Laguna, Philippines: Proceedings of a Workshop, International Rice Research Institute, 1979: 21-31.

    [11] 汤圣祥. 我国杂交水稻蒸煮与食用品质的研究[J]. 中国农业科学, 1987, 20(5): 17-22.
    [12]

    TAN Y F, XING Y Z, LI J X, et al. Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid[J]. Theoretical and Applied Genetics, 2000, 101(5): 823-829.

    [13]

    TIAN Z, QIAN Q, LIU Q, et al. Allelic diversities in rice starch biosynthesis lead to a diverse array of rice eating and cooking qualities[J]. Proceedings of the National Academy of Sciences of the United States of America, 2009, 106(51): 21760-21765. doi: 10.1073/pnas.0912396106

    [14]

    JULIANO B O, PEREZ C M. Results of a collaborative test on the measurement of grain elongation of milled rice during cooking[J]. Journal of Cereal Science, 1984, 2(4): 281-292. doi: 10.1016/S0733-5210(84)80016-8

    [15]

    VIVEKANADAN P, GIRIDHARAN S. Genetic variability and character association for kernel and cooking quality traits in rice[J]. Oryza, 1998, 35(3): 242-245.

    [16] 包劲松, 谢建坤, 夏英武. 籼稻米粒延伸性的遗传研究[J]. 作物学报, 2001, 27(4): 489-492. doi: 10.3321/j.issn:0496-3490.2001.04.014
    [17]

    LI J M, XIAO J H, GRANDILLO S, et al. QTL detection for rice grain quality traits using an interspecific backcross population derived from cultivated Asian (O. sativa L. ) and African (O. glaberrima S. ) rice[J]. Genome, 2004, 47(4): 697-704. doi: 10.1139/g04-029

    [18] 张光恒, 曾大力, 郭龙彪, 等. 水稻米粒延伸性的遗传剖析[J]. 遗传, 2004, 26(6): 887-892. doi: 10.3321/j.issn:0253-9772.2004.06.021
    [19] 沈圣泉, 庄杰云, 王淑珍, 等. 水稻米粒延伸性QTLs定位和基因型与环境互作分析[J]. 中国水稻科学, 2005, 19(4): 319-322. doi: 10.3321/j.issn:1001-7216.2005.04.006
    [20]

    GE X J, XING Y Z, XU C G, et al. QTL analysis of cooked rice grain elongation, volume expansion, and water absorption using a recombinant inbred population[J]. Plant Breeding, 2005, 124(2): 121-126. doi: 10.1111/j.1439-0523.2004.01055.x

    [21]

    TIAN R, JIANG G, SHEN L, et al. Mapping quantitative trait loci underlying the cooking and eating quality of rice using a DH population[J]. Molecular Breeding, 2005, 15(2): 117-124. doi: 10.1007/s11032-004-3270-z

    [22] 陆贤军, 康海岐, 姜华, 等. 水稻核心种质及成恢448回交后代的稻米延伸性研究[J]. 分子植物育种, 2005, 3(5): 676-680. doi: 10.3969/j.issn.1672-416X.2005.05.014
    [23]

    WANG Y, LI J. Genes controlling plant architecture[J]. Current Opinion in Biotechnology, 2006, 17(2): 123-129. doi: 10.1016/j.copbio.2006.02.004

    [24] 康海岐, 陆贤军, 高方远, 等. 成恢448与Basmati 370回交后代的米粒延伸性遗传和相关分析[J]. 作物学报, 2006, 32(9): 1361-1370. doi: 10.3321/j.issn:0496-3490.2006.09.016
    [25]

    AMARAWATHI Y, SINGH R, SINGH A K, et al. Mapping of quantitative trait loci for basmati quality traits in rice (Oryza sativa L. )[J]. Molecular Breeding, 2007, 21(1): 49-65. doi: 10.1007/s11032-007-9108-8

    [26]

    WANG L Q, LIU W J, XU Y, et al. Genetic basis of 17 traits and viscosity parameters characterizing the eating and cooking quality of rice grain[J]. Theoretical and Applied Genetics, 2007, 115(4): 463-476. doi: 10.1007/s00122-007-0580-7

    [27] 姜树坤, 黄成, 徐正进, 等. 粳稻米粒延伸性的QTL剖析[J]. 植物生理学报, 2008, 44(6): 1091-1094. doi: 10.13592/j.cnki.ppj.2008.06.022
    [28]

    LIU L L, YAN X Y, JIANG L, et al. Identification of stably expressed quantitative trait loci for cooked rice elongation in non-Basmati varieties[J]. Genome, 2008, 51(2): 104-112. doi: 10.1139/G07-106

    [29]

    GOVINDARAJ P, VINOD K K, ARUMUGACHAMY S, et al. Analysing genetic control of cooked grain traits and gelatinization temperature in a double haploid population of rice by quantitative trait loci mapping[J]. Euphytica, 2009, 166(2): 165-176. doi: 10.1007/s10681-008-9808-0

    [30] 沈年伟, 来凯凯, 粘金沯, 等. 稻米出饭特性QTL分析及遗传研究[J]. 中国水稻科学, 2011, 25(5): 475-482. doi: 10.3969/j.issn.1001-7216.2011.05.004
    [31]

    SWAMY B P M, KALADHAR K, RANI N S, et al. QTL analysis for grain quality traits in 2 BC2F2 populations derived from crosses between Oryza sativa cv Swarna and 2 accessions of O. nivara[J]. Journal of Heredity, 2012, 103(3): 442-452. doi: 10.1093/jhered/esr145

    [32]

    HOSSEINI M, HOUSHMAND S, MOHAMADI S, et al. Detection of QTLs with main, epistatic and QTL × environment interaction effects for rice grain appearance quality traits using two populations of backcross inbred lines (BILs)[J]. Field Crops Research, 2012, 135: 97-106. doi: 10.1016/j.fcr.2012.07.009

    [33]

    YANG D, ZHANG Y, ZHU Z, et al. Substitutional mapping the cooked rice elongation by using chromosome segment substitution lines in rice[J]. Molecular Plant Breeding, 2013, 4: 107-115.

    [34]

    CHENG A, ISMAIL I, OSMAN M, et al. Mapping of quantitative trait loci for aroma, amylose content and cooked grain elongation traits in rice[J]. Plant Omics Journal, 2014, 7(3): 152-157.

    [35]

    RATHI S, PATHAK K, YADAV R N S, et al. Association studies of dormancy and cooking quality traits in direct-seeded indica rice[J]. Journal of Genetics, 2014, 93(1): 3-12. doi: 10.1007/s12041-014-0319-6

    [36]

    LI Y, TAO H, XU J, et al. QTL analysis for cooking traits of super rice with a high-density SNP genetic map and fine mapping of a novel boiled grain length locus[J]. Plant Breeding, 2015, 134(5): 535-541. doi: 10.1111/pbr.12294

    [37]

    OKPALA N E, DUAN L, SHEN G, et al. Identification of putative metabolic biomarker underlying cooked rice elongation[J]. Plant Omics, 2017, 10(3): 164-168. doi: 10.21475/poj.10.03.17.pne670

    [38]

    SINGH V, SINGH A K, MOHAPATRA T, et al. Pusa Basmati 1121: A rice variety with exceptional kernel elongation and volume expansion after cooking[J]. Rice, 2018, 11: 19. doi: 10.1038/s41598-019-44856-2

    [39]

    ARIKIT S, WANCHANA S, KHANTHONG S, et al. QTL-seq identifies cooked grain elongation QTLs near soluble starch synthase and starch branching enzymes in rice (Oryza sativa L.)[J]. Scientific Reports, 2019, 9: 8328.

    [40]

    KATO K, SUZUKI Y, HOSAKA Y, et al. Effect of high temperature on starch biosynthetic enzymes and starch structure in japonica rice cultivar ‘Akitakomachi’ (Oryza sativa L.) endosperm and palatability of cooked rice[J]. Journal of Cereal Science, 2019, 87: 209-214. doi: 10.1016/j.jcs.2019.04.001

    [41]

    OKPALA N E, POTCHO M P, AN T Y, et al. Low temperature increased the biosynthesis of 2-AP, cooked rice elongation percentage and amylose content percentage in rice[J]. Journal of Cereal Science, 2020, 93: 102980. doi: 10.1016/j.jcs.2020.102980

    [42] 岳红亮, 赵庆勇, 赵春芳, 等. 江苏省半糯粳稻食味品质特征及其与感官评价的关系[J]. 中国粮油学报, 2020, 35(6): 7-14. doi: 10.3969/j.issn.1003-0174.2020.06.002
    [43]

    QIU X, YANG J, ZHANG F, et al. Genetic dissection of rice appearance quality and cooked rice elongation by genome-wide association study[J]. The Crop Journal, 2021, 9(6): 1470-1480. doi: 10.1016/j.cj.2020.12.010

    [44]

    OKPALA N E, POTCHO M P, IMRAN M, et al. Starch morphology and metabolomic analyses reveal that the effect of high temperature on cooked rice elongation and expansion varied in indica and japonica rice cultivars[J]. Agronomy, 2021, 11(12): 2416. doi: 10.3390/agronomy11122416

    [45]

    POTCHO P M, OKPALA N E, KOROHOU T, et al. Nitrogen sources affected the biosynthesis of 2-acetyl-1-pyrroline, cooked rice elongation and amylose content in rice[J]. PLoS One, 2021, 16(7): e254182.

    [46]

    AB HALIM A A B, RAFII M Y, OSMAN M B, et al. Ageing effects, generation means, and path coefficient analyses on high kernel elongation in Mahsuri Mutan and Basmati 370 rice populations[J]. Biomed Research International, 2021, 2021: 8350136. doi: 10.1155/2021/8350136

    [47] 徐伟清, 王小雷, 刘杨, 等. 稻米蒸煮特性QTL定位及与感官食味品质的相关性分析[J]. 核农学报, 2022, 36(1): 66-74. doi: 10.11869/j.issn.100-8551.2022.01.0066
    [48] 刘宜柏, 黄英金. 稻米食味品质的相关性研究[J]. 江西农业大学学报, 1989, 11(4): 1-5. doi: 10.13836/j.jjau.1989050
    [49]

    AHN S N, BOLLICH C N, MCCLUNG A M, et al. RFLP analysis of genomic regions associated with cooked-kernel elongation in rice[J]. Theoretical and Applied Genetics, 1993, 87(1/2): 27-32.

    [50]

    SANTOS M V, CUEVAS R P O, SREENIVASULU N, et al. Measurement of rice grain dimensions and chalkiness, and rice grain elongation using image analysis[J]. Methods in Molecular Biology, 2019, 1892: 99-108.

    [51]

    SCHNEIDER C A, RASBAND W S, ELICEIRI K W. NIH Image to ImageJ: 25 years of image analysis[J]. Nature methods, 2012, 9(7): 671-675. doi: 10.1038/nmeth.2089

    [52]

    JINOROSE M, PRACHAYAWARAKORN S, SOPONRONNARIT S. A novel image-analysis based approach to evaluate some physicochemical and cooking properties of rice kernels[J]. Journal of Food Engineering, 2014, 124: 184-190.

    [53]

    SUMAN K, MADHUBABU P, RATHOD R, et al. Variation of grain quality characters and marker-trait association in rice (Oryza sativa L.)[J]. Journal of Genetics, 2020, 99(1): 5. doi: 10.1007/s12041-019-1164-4

    [54] 黄发松, 孙宗修, 胡培松, 等. 食用稻米品质形成研究的现状与展望[J]. 中国水稻科学, 1998, 12(3): 172-176. doi: 10.3321/j.issn:1001-7216.1998.03.012
    [55]

    JIANG Y, CHEN Y, ZHAO C, et al. The starch physicochemical properties between superior and inferior grains of japonica rice under panicle nitrogen fertilizer determine the difference in eating quality[J]. Foods, 2022, 11(16): 2489. doi: 10.3390/foods11162489

    [56]

    TESTER R F, KARKALAS J, QI X. Starch-composition, fine structure and architecture[J]. Journal of Cereal Science, 2004, 39(2): 151-165. doi: 10.1016/j.jcs.2003.12.001

    [57]

    RAIGOND P, EZEKIEL R, RAIGOND B. Resistant starch in food: A review[J]. Journal of the Science of Food and Agriculture, 2015, 95(10): 1968-1978. doi: 10.1002/jsfa.6966

    [58]

    WEI C, QIN F, ZHOU W, et al. Comparison of the crystalline properties and structural changes of starches from high-amylose transgenic rice and its wild type during heating[J]. Food Chemistry, 2011, 128(3): 645-652. doi: 10.1016/j.foodchem.2011.03.080

    [59]

    ZHOU H, WANG L, LIU G, et al. Critical roles of soluble starch synthase SSIIIa and granule-bound starch synthase Waxy in synthesizing resistant starch in rice[J]. Proceedings of the National Academy of Sciences of the United States of America, 2016, 113(45): 12844-12849.

    [60]

    PAN T, LIN L, ZHANG L, et al. Changes in kernel properties, in situ gelatinization, and physicochemical properties of waxy rice with inhibition of starch branching enzyme during cooking[J]. International Journal of Food Science and Technology, 2019, 54(9): 2780-2791. doi: 10.1111/ijfs.14193

    [61]

    HE W, LIN L, WANG J, et al. Inhibition of starch branching enzymes in waxy rice increases the proportion of long branch-chains of amylopectin resulting in the comb-like profiles of starch granules[J]. Plant Science, 2018, 277: 177-187.

    [62]

    SHI S, PAN K, ZHANG G, et al. Differences in grain protein content and regional distribution of 706 rice accessions[J]. Journal of the Science of Food and Agriculture, 2023, 103(3): 1593-1599. doi: 10.1002/jsfa.12308

    [63]

    KUMAR P, PRAKASH K S, JAN K, et al. Effects of gamma irradiation on starch granule structure and physicochemical properties of brown rice starch[J]. Journal of Cereal Science, 2017, 77: 194-200. doi: 10.1016/j.jcs.2017.08.017

    [64]

    CHAMPAGNE E T, BETT-GARBER K L, THOMSON J L, et al. Unraveling the impact of nitrogen nutrition on cooked rice flavor and texture[J]. Cereal Chemistry Journal, 2009, 86(3): 274-280. doi: 10.1094/CCHEM-86-3-0274

    [65]

    LYON B G, CHAMPAGNE E T, VINYARD B T, et al. Effects of degree of milling, drying condition, and final moisture content on sensory texture of cooked rice[J]. Cereal Chemistry, 1999, 76(1): 56-62. doi: 10.1094/CCHEM.1999.76.1.56

    [66]

    SHI S, ZHANG G, CHEN L, et al. Different nitrogen fertilizer application in the field affects the morphology and structure of protein and starch in rice during cooking[J]. Food Research International, 2023, 163: 112193. doi: 10.1016/j.foodres.2022.112193

    [67]

    BALINDONG J L, WARD R M, LIU L, et al. Rice grain protein composition influences instrumental measures of rice cooking and eating quality[J]. Journal of Cereal Science, 2018, 79: 35-42. doi: 10.1016/j.jcs.2017.09.008

    [68] 习敏, 季雅岚, 文革, 等. 水稻食味品质形成影响因素研究与展望[J]. 中国农学通报, 2020, 36(12): 159-164.
    [69]

    SHI S, ZHANG G, ZHAO D, et al. Changes in water absorption and morphology of rice with different eating quality during soaking[J]. European Food Research and Technology, 2023, 249(3): 759-766. doi: 10.1007/s00217-022-04173-x

    [70] 张栋昊, 蔡妍培, 劳菲, 等. 大米蛋白质与米饭食味品质关联性研究进展[J]. 食品科学, 2022, 44(9): 270-277.
    [71]

    ZHAN Q, YE X, ZHANG Y, et al. Starch granule-associated proteins affect the physicochemical properties of rice starch[J]. Food Hydrocolloids, 2020, 101: 105504. doi: 10.1016/j.foodhyd.2019.105504.

    [72]

    HU Z, YANG Y, LU L, et al. Kinetics of water absorption expansion of rice during soaking at different temperatures and correlation analysis upon the influential factors[J]. Food Chemistry, 2021, 346: 128912. doi: 10.1016/j.foodchem.2020.128912

    [73]

    SHI J, WU M, QUAN M. Effects of protein oxidation on gelatinization characteristics during rice storage[J]. Journal of Cereal Science, 2017, 75: 228-233. doi: 10.1016/j.jcs.2017.04.013

    [74]

    YANG W, XU P, ZHANG J, et al. OsbZIP60-mediated unfolded protein response regulates grain chalkiness in rice[J]. Journal of Genetics and Genomics, 2022, 49(5): 414-426. doi: 10.1016/j.jgg.2022.02.002

    [75] 廖斌, 张桂莲. 水稻垩白的研究进展[J]. 作物研究, 2015, 29(1): 77-83. doi: 10.3969/j.issn.1001-5280.2015.01.20
    [76]

    LI Y, FAN C, XING Y, et al. Chalk5 encodes a vacuolar H+-translocating pyrophosphatase influencing grain chalkiness in rice[J]. Nature Genetics, 2014, 46(4): 398-404. doi: 10.1038/ng.2923

    [77]

    SINGH N, SODHI N S, KAUR M, et al. Physico-chemical, morphological, thermal, cooking and textural properties of chalky and translucent rice kernels[J]. Food Chemistry, 2003, 82(3): 433-439. doi: 10.1016/S0308-8146(03)00007-4

    [78]

    CHENG F M, ZHONG L J, WANG F, et al. Differences in cooking and eating properties between chalky and translucent parts in rice grains[J]. Food Chemistry, 2005, 90(1/2): 39-46.

    [79]

    CHUN A, SONG J, KIM K, et al. Quality of head and chalky rice and deterioration of eating quality by chalky rice[J]. Journal of Crop Science and Biotechnology, 2009, 12(4): 239-244. doi: 10.1007/s12892-009-0142-4

    [80] 王忠, 顾蕴洁, 陈刚, 等. 稻米的品质和影响因素[J]. 分子植物育种, 2003, 1(2): 231-241. doi: 10.3969/j.issn.1672-416X.2003.02.011
    [81] 卢林, 孙成效, 朱智伟, 等. 我国稻米品质标准及检测技术创新概述[J]. 中国稻米, 2022, 28(1): 1-6.
    [82]

    TONG C, GAO H, LUO S, et al. Impact of postharvest operations on rice grain quality: A review[J]. Comprehensive Reviews in Food Science and Food Safety, 2019, 18(3): 626-640. doi: 10.1111/1541-4337.12439

    [83] 郭桂英, 王青林, 马汉云, 等. 碾磨品质对籼稻食味品质的影响[J]. 天津农业科学, 2017, 23(6): 40-44.
    [84]

    KIM S Y, LEE H. Effects of eating quality on milled rice produced from brown rice with different milling conditions[J]. Journal of the Korean Society for Applied Biological Chemistry, 2013, 56(5): 621-629. doi: 10.1007/s13765-013-3097-6

    [85]

    MOHAPATRA D, BAL S. Cooking quality and instrumental textural attributes of cooked rice for different milling fractions[J]. Journal of Food Engineering, 2006, 73(3): 253-259. doi: 10.1016/j.jfoodeng.2005.01.028

    [86]

    YANG X, BI J, GILBERT R G, et al. Amylopectin chain length distribution in grains of japonica rice as affected by nitrogen fertilizer and genotype[J]. Journal of Cereal Science, 2016, 71: 230-238. doi: 10.1016/j.jcs.2016.09.003

    [87]

    JULIANO B O. Physico-chemical properties of starch and protein and their relation to grain quality and nutritional value of rice[J]. Rice Breeding, 1972, 5: 389-405.

    [88] 袁玉洁, 张丝琪, 王明玥, 等. 蒸煮米水比对不同直链淀粉含量杂交籼稻米粒微观结构和食味特性的影响[J]. 作物学报, 2022, 48(12): 3225-3233.
    [89] 李萍, 周广春, 崔晶, 等. 煮饭水质结合加水量和浸泡时间对粳稻食味的影响[J]. 中国稻米, 2021, 27(6): 74-79. doi: 10.3969/j.issn.1006-8082.2021.06.015
    [90]

    HUSSIAN R A, BROWN D C. Use of two-dimensional grid patterns to limit hazardous ambulation in demented patients[J]. Journal of Gerontology, 1987, 42(5): 558-560. doi: 10.1093/geronj/42.5.558

    [91] 高振宇, 曾大力, 崔霞, 等. 水稻稻米糊化温度控制基因ALK的图位克隆及其序列分析[J]. 中国科学(C辑: 生命科学), 2003, 33(6): 481-487.
    [92] 张桂权. 基于SSSL文库的水稻设计育种平台[J]. 遗传, 2019, 41(8): 754-760. doi: 10.16288/j.yczz.19-105
    [93]

    ZHANG G. Target chromosome-segment substitution: A way to breeding by design in rice[J]. The Crop Journal, 2021, 9(3): 658-668. doi: 10.1016/j.cj.2021.03.001

  • 期刊类型引用(9)

    1. 温雅,顾嘉怡,王超瑞,张瑛,肖治林,张耗. 水稻高产减排的氮肥管理技术及其对稻田温室气体排放影响的研究进展. 中国稻米. 2025(01): 11-17 . 百度学术
    2. 郭高文,齐鹏,王晓娇,甘润,蔡立群,张仁陟. 不同施氮量对旱作春小麦农田土壤温室气体排放的影响. 国土与自然资源研究. 2024(02): 75-81 . 百度学术
    3. 谢先芝,刘奇华,李新华,李维平. 稻田甲烷产生与排放的影响因素及减排措施研究进展. 中国水稻科学. 2024(05): 475-494 . 百度学术
    4. 陈小龙,汪精海,赵玉平,高勇,张荣. 水氮调控对农田土壤温室气体排放的影响研究进展. 水利规划与设计. 2024(11): 95-99 . 百度学术
    5. 常琳溪,梁新然,王磊,李祖然,湛方栋,何永美. 中国稻田土壤有机碳汇特征与影响因素的研究进展. 土壤. 2023(03): 487-493 . 百度学术
    6. 张忠学,薛里,李铁成,齐智娟,王忠波,周欣. 水氮耦合下黑土区稻田生态系统碳源汇效应分析. 农业机械学报. 2023(08): 330-338 . 百度学术
    7. 肖德顺,徐春梅,王丹英,陈松,褚光,刘元辉. 增氧模式对水稻根际微生物多样性和群落结构的影响. 环境科学. 2023(11): 6362-6376 . 百度学术
    8. 唐志伟,张俊,邓艾兴,张卫建. 我国稻田甲烷排放的时空特征与减排途径. 中国生态农业学报(中英文). 2022(04): 582-591 . 百度学术
    9. 彭灯云,杨士红,李伟征,李明,戴惠东,周姣艳. 生物炭施用对节水灌溉稻田甲烷产生菌与氧化菌的影响. 节水灌溉. 2022(05): 54-59 . 百度学术

    其他类型引用(10)

图(3)
计量
  • 文章访问数:  155
  • HTML全文浏览量:  24
  • PDF下载量:  32
  • 被引次数: 19
出版历程
  • 收稿日期:  2022-11-29
  • 网络出版日期:  2023-11-12
  • 发布日期:  2023-06-06
  • 刊出日期:  2023-09-09

目录

Corresponding author: WANG Shaokui, shaokuiwang@scau.edu.cn

  1. On this Site
  2. On Google Scholar
  3. On PubMed

/

返回文章
返回