施氮量对杂交水稻叶片光谱特征、SPAD值和光能拦截率关系的影响
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摘要
为探究不同氮肥处理对两系杂交稻叶片光谱特征、叶绿素含量(SPAD)、光能拦截率之间关系的影响,本试验以全两优1号和全两优681杂交稻品种为供试材料,设置N0(0 kg·hm~(-2))、N1(150kg·hm~(-2))和N2(250 kg·hm~(-2))3个氮肥处理,研究不同氮肥施用量下杂交稻群体的光能截获率(IPAR)、SPAD和叶片光谱特性。结果表明,不同氮肥处理下水稻叶片光谱特征差异明显,全两优1号和全两优681的光谱反射率随氮肥施用量的增加在可见光范围内降低,在近红外区域增高。施氮量的增加能够提高叶片SPAD值以及光化学植被指数值(PRI),PRI与IPAR相关系数达到0.64。齐穗期的光谱参数中的差值植被指数(DVI)、垂直植被指数(PVI)与2个杂交稻品种的实际产量均呈极显著正相关,相关系数分别为0.82和0.86。综上,齐穗期水稻群体高光谱指数能够预测水稻群体IPAR以及实际产量,本研究利用高光谱数据反演水稻关键生育期内的氮素营养信息,为氮肥精确化管理,提高氮肥利用率,实现水稻高产高效提供了理论指导。
In order to study the effects of different nitrogen treatments on the relationship between spectral features of flag leaves and the SPAD,and IPAR in hybrid rice,this experiment was conducted with two-line hybrid rice cultivars,Quanliangyou 1 and Quanliangyou 681 with three application levels of nitrogen fertilizer including N0( 0 kg·hm~(-2)),N1( 150 kg·hm~(-2)) and N2( 250 kg·hm~(-2)),respectively. The results showed that there was significant difference in the flag leaves spectral features of the two varieties under different nitrogen treatments. The spectral reflectance of the flag leaves was gradually getting bigger in the visible region and smaller in the near infrared region at full heading stage. The SPAD value,PRI and IPAR of the two varieties significantly increased with the improvement of nitrogen rates,and the correlation index between PRI and IPAR was significant,at 0. 64. Additionally,both the spectral index DVI and PVI were positively correlated with grain yield,at 0. 82 and 0. 86,respectively. Given this situation,these spectral indexes of flag leaves in hybrid rice mentioned in our studies could be used to predict grain yield and IPAR. In this study,the acquisition of reflectance spectra based monitoring of nitrogen nutrition in leaf can be applied to precise nitrogen management,and to improve nitrogen use efficiency,thereby providing theoretical guidance for achieving high yield and efficiency in production.
In order to study the effects of different nitrogen treatments on the relationship between spectral features of flag leaves and the SPAD,and IPAR in hybrid rice,this experiment was conducted with two-line hybrid rice cultivars,Quanliangyou 1 and Quanliangyou 681 with three application levels of nitrogen fertilizer including N0( 0 kg·hm~(-2)),N1( 150 kg·hm~(-2)) and N2( 250 kg·hm~(-2)),respectively. The results showed that there was significant difference in the flag leaves spectral features of the two varieties under different nitrogen treatments. The spectral reflectance of the flag leaves was gradually getting bigger in the visible region and smaller in the near infrared region at full heading stage. The SPAD value,PRI and IPAR of the two varieties significantly increased with the improvement of nitrogen rates,and the correlation index between PRI and IPAR was significant,at 0. 64. Additionally,both the spectral index DVI and PVI were positively correlated with grain yield,at 0. 82 and 0. 86,respectively. Given this situation,these spectral indexes of flag leaves in hybrid rice mentioned in our studies could be used to predict grain yield and IPAR. In this study,the acquisition of reflectance spectra based monitoring of nitrogen nutrition in leaf can be applied to precise nitrogen management,and to improve nitrogen use efficiency,thereby providing theoretical guidance for achieving high yield and efficiency in production.
引文
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[8]李彩虹,冯美臣,王超,尹超.不同播期冬小麦叶绿素含量的冠层光谱响应研究[J].核农学报,2014,28(2):309-316
[9]刘小军,田永超,姚霞,曹卫星,张玉森,朱艳.基于高光谱的水稻叶片含水量监测研究[J].中国农业科学,2011,45(3):435-442
[10]李永梅,张学俭,张立根.水稻氮素高光谱遥感估测模型研究[J].江苏农业科学,2016,44(8):435-439
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[12]王人潮,陈铭臻,蒋亨显.水稻遥感估产的农学机理研究-Ⅰ.不同氮素水平的水稻光谱特征及其敏感波段的选择[J].浙江农业大学学报,1993,19(S1):7-14
[13]张金恒,王珂,王人潮,郑洪福,周斌.水稻叶片反射光谱诊断氮素营养敏感波段的研究[J].浙江大学学报(农业与生命科学版),2004,30(3):340-346
[14]贺佳,刘冰峰,郭燕,王来刚,郑国清,李军.冬小麦生物量高光谱遥感监测模型研究[J].植物营养与肥料学报,2017,23(2):313-323
[15]Dechant B,Cuntz M,Vohland M,Schulz E,Doktor D.Estimation of photosynthesis traits from leaf reflectance spectra:correlation to nitrogen content as the dominant mechanism[J].Remote Sensing of Environment,2017,196:279-292
[16]田永超,杨杰,姚霞,曹卫星,朱艳.利用叶片高光谱指数预测水稻群体叶层全氮含量[J].作物学报,2010,36(9):1529-1537
[17]程建峰,沈允钢.作物高光效之管见[J].作物学报,2010,36(8):1235-1247
[18]郑丕尧.作物生理学导论[M].北京:中国农业大学出版社,1992
[19]Gu J,Chen Y,Zhang H,Li Z,Zhou Q,Yu C,Kong X,Liu L,Wang Z,Yang J.Canopy light and nitrogen distributions are related to grain yield and nitrogen use efficiency in rice[J].Field Crops Research,2017,206:74-85
[20]邹江石,姚克敏,吕川根,胡雪琼.水稻两优培九株型特征研究[J].作物学报,2003,29(5):652-657
[21]贾良良,范明生,张福锁,陈新平,吕世华,孙彦铭.应用数码相机进行水稻氮营养诊断[J].光谱学与光谱分析,2009,29(8):2176-2179
[22]屈卫群,王绍华,陈兵林,王友华,周治国.棉花主茎叶SPAD值与氮素营养诊断研究[J].作物学报,2007,33(6):1010-1017
[23]杨绍锷,杜鑫.基于光谱信息的作物氮素营养诊断研究进展[J].湖南农业科学,2017(2):127-130
[24]黄敬峰,王福民,王秀珍.水稻高光谱遥感试验研究[M].杭州:浙江大学出版社,2001
[25]王景旭,丁丽霞,程乾.湿地植被叶面积指数对光化学指数和光能利用率关系的影响——基于实测数据和PROSPECT-SAIL模型[J].自然资源学报,2016,31(3):514-525
[26]郑腾飞,郭建茂,于鑫,王琦,吴玮.基于氮处理的不同生育期冬小麦光能利用率和光化学植被指数的关系[J].干旱气象,2012,30(4):623-629
[27]薛利红,曹卫星,罗卫红.基于冠层反射光谱的水稻产量预测模型[J].遥感学报,2005,9(1):100-105
[28]谢晓金,李映雪,李秉柏,申双和,程高峰.高温胁迫下水稻产量的高光谱估测研究[J].中国水稻科学,2010,24(2):196-202
[29]周启发,王人潮.水稻氮素营养水平与光谱特性的关系[J].浙江农业大学学报,1993,19(S1):40-45
[30]吴蕾,柏军华,肖青,杜永明,柳钦火,徐丽萍.作物生长模型与定量遥感参数结合研究进展与展望[J].农业工程学报,2017,33(9):155-166
[2]花劲,周年兵,张军,张洪程,霍中洋,周培建,程飞虎,李国业,黄大山,陈忠平,陈国梁,戴其根,许轲,魏海燕,高辉,郭保卫.双季晚稻甬优系列籼粳杂交稻超高产结构与群体形成特征[J].中国农业科学,2015,48(5):1023-1034
[3]岳玉波,沙之敏,赵峥,陆欣,张金秀,赵琦,曹林奎.不同水稻种植模式对氮磷流失特征的影响[J].中国生态农业学报,2014,22(12):1424-1432
[4]曹小闯,李晓艳,朱练峰,张均华,禹盛苗,吴良欢,金千瑜.水分管理调控水稻氮素利用研究进展[J].生态学报,2016,36(13):3882-3890
[5]曾水生,李艳大,舒时富,陈立才,叶春,贺志远,张晨,曾一凡.光谱技术在水稻生长监测中的应用研究进展[J].农学学报,2015,5(2):100-104
[6]姜庆虎,童芳,余明珠,章影,廖畅,刘峰.高光谱技术——生态学领域研究的新方法[J].植物科学学报,2015,33(5):633-640
[7]张浩,胡昊,陈义,唐旭,吴春艳,刘玉学,杨生茂,郑可锋.水稻叶片氮素及籽粒蛋白质含量的高光谱估测模型[J].核农学报,2012,26(1):135-140
[8]李彩虹,冯美臣,王超,尹超.不同播期冬小麦叶绿素含量的冠层光谱响应研究[J].核农学报,2014,28(2):309-316
[9]刘小军,田永超,姚霞,曹卫星,张玉森,朱艳.基于高光谱的水稻叶片含水量监测研究[J].中国农业科学,2011,45(3):435-442
[10]李永梅,张学俭,张立根.水稻氮素高光谱遥感估测模型研究[J].江苏农业科学,2016,44(8):435-439
[11]陈光辉,唐文帮.水稻高光谱变化特征与叶绿素含量监测研究[J].激光生物学报,2017,26(4):326-333
[12]王人潮,陈铭臻,蒋亨显.水稻遥感估产的农学机理研究-Ⅰ.不同氮素水平的水稻光谱特征及其敏感波段的选择[J].浙江农业大学学报,1993,19(S1):7-14
[13]张金恒,王珂,王人潮,郑洪福,周斌.水稻叶片反射光谱诊断氮素营养敏感波段的研究[J].浙江大学学报(农业与生命科学版),2004,30(3):340-346
[14]贺佳,刘冰峰,郭燕,王来刚,郑国清,李军.冬小麦生物量高光谱遥感监测模型研究[J].植物营养与肥料学报,2017,23(2):313-323
[15]Dechant B,Cuntz M,Vohland M,Schulz E,Doktor D.Estimation of photosynthesis traits from leaf reflectance spectra:correlation to nitrogen content as the dominant mechanism[J].Remote Sensing of Environment,2017,196:279-292
[16]田永超,杨杰,姚霞,曹卫星,朱艳.利用叶片高光谱指数预测水稻群体叶层全氮含量[J].作物学报,2010,36(9):1529-1537
[17]程建峰,沈允钢.作物高光效之管见[J].作物学报,2010,36(8):1235-1247
[18]郑丕尧.作物生理学导论[M].北京:中国农业大学出版社,1992
[19]Gu J,Chen Y,Zhang H,Li Z,Zhou Q,Yu C,Kong X,Liu L,Wang Z,Yang J.Canopy light and nitrogen distributions are related to grain yield and nitrogen use efficiency in rice[J].Field Crops Research,2017,206:74-85
[20]邹江石,姚克敏,吕川根,胡雪琼.水稻两优培九株型特征研究[J].作物学报,2003,29(5):652-657
[21]贾良良,范明生,张福锁,陈新平,吕世华,孙彦铭.应用数码相机进行水稻氮营养诊断[J].光谱学与光谱分析,2009,29(8):2176-2179
[22]屈卫群,王绍华,陈兵林,王友华,周治国.棉花主茎叶SPAD值与氮素营养诊断研究[J].作物学报,2007,33(6):1010-1017
[23]杨绍锷,杜鑫.基于光谱信息的作物氮素营养诊断研究进展[J].湖南农业科学,2017(2):127-130
[24]黄敬峰,王福民,王秀珍.水稻高光谱遥感试验研究[M].杭州:浙江大学出版社,2001
[25]王景旭,丁丽霞,程乾.湿地植被叶面积指数对光化学指数和光能利用率关系的影响——基于实测数据和PROSPECT-SAIL模型[J].自然资源学报,2016,31(3):514-525
[26]郑腾飞,郭建茂,于鑫,王琦,吴玮.基于氮处理的不同生育期冬小麦光能利用率和光化学植被指数的关系[J].干旱气象,2012,30(4):623-629
[27]薛利红,曹卫星,罗卫红.基于冠层反射光谱的水稻产量预测模型[J].遥感学报,2005,9(1):100-105
[28]谢晓金,李映雪,李秉柏,申双和,程高峰.高温胁迫下水稻产量的高光谱估测研究[J].中国水稻科学,2010,24(2):196-202
[29]周启发,王人潮.水稻氮素营养水平与光谱特性的关系[J].浙江农业大学学报,1993,19(S1):40-45
[30]吴蕾,柏军华,肖青,杜永明,柳钦火,徐丽萍.作物生长模型与定量遥感参数结合研究进展与展望[J].农业工程学报,2017,33(9):155-166