砷污染水稻高光谱特征及水稻籽粒产量光谱预估研究
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摘要
随着人类活动的发展,特别是现代工业的发展,土壤重金属污染呈日趋严重的趋势。土壤中积累过量的砷,会造成植物减产和品质下降,同时可能造成水源和大气污染,通过食物链和水体等途径进入人体。
     研究采用水稻盆栽,进行砷添加温室土培试验。利用地物光谱仪测定水稻生长关键时期的光谱和室内分析植株砷含量,开展了光谱数据预处理技术、砷污染水稻不同生育期不同品种光谱特征、水稻植株砷含量光谱反演,以及水稻籽粒产量光谱预估研究。结果表明:随着水稻的生长,在可见光波段范围,光谱差异值先减少,到抽穗期逐渐增大,而在近红外波段范围,光谱差异值逐渐增大;从不同品种水稻光谱差异看,在可见光波段和近红外波段,籼稻光谱差异均高于杂交稻和粳稻。
     研究中发现,水稻各器官砷含量大小顺序为根>叶>茎>籽粒,不同类型水稻砷含量大小顺序为:杂交稻>籼稻>粳稻。在基于冠层光谱及光谱的变换形式(一阶微分、倒数对数)建立的水稻植株砷含量反演模型中,光谱的一阶微分建立的反演模型效果最佳,模型为Y=19.475+360320.442*b1260,平均相对误差为20.4%。
     受砷污染后,籽粒产量明显降低,其中籼稻产量降低最大,水稻籽粒产量的大小顺序为杂交稻>粳稻>籼稻。在不同生育期的光谱及光谱的变换形式建立的水稻籽粒产量预估模型中,以抽穗期和成熟期光谱的一阶微分建立的水稻籽粒产量效果较好,水稻籽粒产量的预估模型分别为抽穗期Y=17.901-51989.300*b660-102833.825*b1260-1512.368*b700,平均相对误差为20.8%;成熟期Y=18.639-26161.821*b610-19026.811*b760,平均相对误差为22.1%。
Along with more human activities, especially the development of modern industry, soil heavy metal pollution becomes more and more serious.. The accumulation of excess arsenic in soil can decrease the yield and quality of plants, meantime can cause water and atmospheric pollution. It can enter human body through food and water.
     Potted rice was cultivated in the greenhouse by adding arsenic to the soil. Rice spectrum was measured in the key growth period by ASD and arsenic content of plant was analyzed in laboratory. The pretreatment technology of spectral data, spectral features of Arsenic pollution rice of rice varieties at different growth stages, Arsenic content retrieval of rice and rice yield prediction by spectrum were explored. The results shows there was little difference in the visible spectral range for the rice leave in the early growth stage, the difference increased with the rice growth, especially in the heading period. But the difference in the near infrared spectral range increased with the rice growth. In the visible and near infrared bands, spectral differences of indica under pollution were higher than those japonica and hybrid rice. It was found that the Arsenic content in Rice organ is:root>leaf>stem>grain and for different types of rice, it is:regeneration> japonica> hybrid rice. plant arsenic retrieval model by canopy spectrum is the best among spectrum, first-order differential and reciprocal logarithmic model, it is Y=19.475+360320.442*b1260, with the average relative error of 20.4%.
     The grain yield significantly decrease after arsenic polluted and the order of rice grain yield is japonica>hybrid>regeneration. The first-order differential model for estimating of rice grain yield in heading and mature period is the best in different rice growth stages and among different models of spectrum, first-order differential and reciprocal logarithmic model. They are:
     Y=17.901-51989.300*b660-102833.825*b1260-1512.368*b7oo, with the average relative error of 20.8% for heading period, Y=18.639-26161.821*b610-19026.811* b760, with the average relative error of 22.1% for mature period.
引文
[1]林玉锁.土壤环境安全及其污染防治对策[J].环境保护,2007(1):35-38.
    [2]邹声文.我国土壤污染形势相当严峻已对百姓身体健康构成威胁[J].云南日报网,2006,7,18.
    [3]何容,杜佳佳,许波峰等.土壤重金属污染研究概况[J].山东林业科技,2008,174:85-87.
    [4]http://www.china.com.cn/chinese/EC-c/291683.htm 2011年2月10日访问.
    [5]滕应,黄昌勇.重金属污染土壤的微生物生态效应及其修复研究进展[J].土壤与环境,2002,11(1):85-89.
    [6]http://news.hexun.com/2011-02-26/127578401_1.html 2011年2月10日访问.
    [7]邵汉池,陈俊义,沈丹锋.砷污染对水稻的影响及其转化措施[J].上海农业科技,2001,1:81.
    [8]任红艳.宝山矿区农田土壤-水稻系统重金属污染遥感监测[D].南京农业大学,2008.
    [9]陈同斌,刘令更.砷对水稻生长发育的影响及其原因[J].中国农业科学,1993,26(6):50-58.
    [10]刘向蕾.重金属对水稻生长发育影响的研究进展[J].现代化农业,2007,2(331):7-9.
    [11]http://baike.baidu.com/view/3877281.htm 2011年2月10日访问.
    [12]陈述彭,童庆禧,郭华东.高光谱分辨率遥感信息机理与地物识别遥感信息机理研究[M].北京:科学出版社,1998,139-231.
    [13]郑兰芬,王晋年.成像光谱遥感技术及其成像光谱信息提取分析研究[J].环境遥感,1992,7(1):49-58.
    [14]Vane,G etal.Terrestrial Imaging Spectrometry,Current Status,Future Trend[J],Remote Sensing of Environment,1993,44,109-127.
    [15]童庆禧,郑兰芬.高光谱遥感发展现状[J].中科院遥感所遥感信息科学开放研 究实验室年报,1999:246-258.
    [16]童庆禧,张兵,郑兰芬.高光谱遥感-原理、技术与应用[M].高等教育出版社,2006.
    [17]刘厚田,张维平,于亚平.土壤镉污染对水稻叶片光谱反射特性的影响[J].生态学报,1986,2:90-99.
    [18]Jackson R D, Slater P N, Pinter P J. Discrimination of Growth and W ater Stress in Wheat by Various Vegetation Indices Through Clear and Turbid Atmospheres[J]. Remote Sensing of Environment,1983,13:187-208.
    [19]Dunagan S C,Martha S QJohan C V.Effects of Mercury on Visible/near-infrared Reflectance Spectra of Mustard SpinachPlants (Brassica Rapa P.)[J]. Environmental Pollution,2007,148(1):301-311.
    [20]田国良,包佩丽,李建军等.土壤中镉、铜伤害对水稻光谱特性的影响[J].环境遥感,1990,5(2):140-148.
    [21]Jackson R D,Slater P N,Pinter P J.Discrimination of Growthand Water Stress in Wheat by Various Vegetation IndicesThrough Clear and Turbid Atmospheres[J].Remote Sensing of Environment,1983,13:187-208.
    [22]甘甫平,刘圣伟,周强.德兴铜矿矿山污染高光谱遥感直接识别研究[J].地球科学-中国地质大学学报,2004,29(1):119-126.
    [23]任红艳.基于冠层光谱的冬小麦N、P营养和水稻Pb污染监测研究[D].南京农业大学,2005.
    [24]Kooistra L,Leuven R S E W,Wehrens R.A Comparison of Methods to Relate Grass Reflectance to Soil Metal Contamination [J]. International Journal of Remote Sensing,2003,24 (24):4995-5010.
    [25]陈思宁,刘新会,侯娟.重金属锌胁迫的白菜叶片光谱响应研究[J].光谱学与光谱分析,2007,27(9):1797-1801.
    [26]刘素红,刘新会,侯娟等.植物光谱应用于白菜铜胁迫响应研究[J].中国科学,2007,37(5):693-699.
    [27]Liang H,Xiangnan L.Hyperspectral Analysis of Leaf Copper Accumulation in Agronomic Crop Based on Artificial NeuralNetwork[Z].International Workshop on Earth Observationand Remote Sensing Applications,2008.
    [28]迟光宇,刘新会,刘素红等.Cu污染与小麦特征光谱相关关系研究[J].光谱学与光谱分析,2006,26(7):1272-1276.
    [29]Kooistra L,Salas E A L,Clevers J G P W.Exploring Field Vegetation Reflectance as an Indicator of Soil Contaminationin River Floodplains[J].Environmental Pollution,2004,127:281-290.
    [30]Clevers J G P W,Kooistra L,Salas E A L.Study of HeavyMetal Contamination in River Floodplains Using the Red-edgePosition in Spectroscopic Data[J].International Joural of Remote Sensing,2004,25(19):883-3895.
    [31]Milton N M,Ager M,Eiswerth B A,etal.Arsenic-andselenium-induced changes in spectral reflectance and morphology of soybean plants [J].Remote Sens Environ,1989,30:263-269.
    [32]Font R,Del Rio M,Velez D.Use of near-infrared spectroscopy for determining the total arsenic content in prostrate amaranth[J].Sci Total Environ,2004,327:93-104.
    [33]刘湘南,曹珊.成熟期水稻砷污染胁迫光谱诊断空间模型研究[J].中国生态农业学报,2010,18(4):843-846.
    [34]刘湘南,刘慕霞.基于高光谱指数的水稻砷污染胁迫多重判别模型[J].环境科学,2010,10:2462-2468.
    [35]Kooistra L, Wehrens R, Leuven R S EW, etal Possibilities of visible near-infrared spectroscopy for the assessment of soil contamination in river floodplains[J].Analytica Chimica Acta,2001,446:97-105.
    [36]Kemper,T.;Sommer,S.Estimate of heavy metal contamination in soils after a mining accident using reflectance spectro scopy[J].Environmental science and technology,2002,36:2742-2747.
    [37]Y Z Wu, J Chen, J F J,i et al Feasibility of Reflectance Spectroscopy for Soil Mercury Contamination[J].Environment Science Technology,2005,39:873-878.
    [38]李巨宝,田庆久,吴昀昭.滏阳河两岸农田土壤Fe, Zn, Se元素光谱响应研究[J].遥感信息,2005(3):10-13.
    [39]王玉.磁化率及光谱方法对成都经济区土壤污染指示性的研究[D].北京:中国地质大学,2006.
    [40]任红艳,庄大方,邱冬生等.矿区农田土壤砷污染的可见-近红外反射光谱分析研究[J].光谱学与光谱分析,2009(1):114-118.
    [41]陈翠华,倪师军,何彬彬等.基于污染指数法和GIS技术评价江西德兴矿区土壤重金属污染[J].吉林大学学报(地球科学版),2008,1(38):105-111.
    [42]陈翠华,江西德.兴地区重金属污染现状评价及时空对比研究[D].成都理工大学博士学位论文.2008.
    [43]黄长干,邱业先.江西德兴铜矿铜污染状况调查及植物修复研究[J].土壤通报.2005,6(36):991-992.
    [44]翟丽梅,陈同斌,廖晓勇.广西环江铅锌矿尾砂坝坍塌对农田土壤的污染及其特征[J].环境科学学报,2008,6(28):1206-1210.
    [45]谢华,廖晓勇,陈同斌等.污染农田中植物的砷含量及其健康风险评估——以湖南郴州邓家塘为例[J].地理研究,2005,1:151-159.
    [46]曾敏,廖柏寒,曾清如.湖南郴州、石门、冷水江3个矿区As污染状况的初步调查[J].农业环境科学学报2006,25(2):418-421.
    [47]林杰藩,赖启宏,方敬文.珠江三角洲土壤Hg污染区生态地球化学评价[J].生态环境,2007,16(1):41-46.
    [48]郭利敏.珠江三角洲镉污染菜田土壤改良剂筛选及其应用技术研究[D].西北农林科技大学硕士学位论文,2010.
    [49]卢休祥.论珠江三角洲土壤受重金属污对农业生产的危害与防治措施[J].中国地质灾害与防治学报,1991,4(2):89-93.
    [50]王伟,栾进华,黄波等.重庆东北脐橙主产区土壤重金属含量分析及污染评价[J].微量元素与健康研究,2011,2(25):30-32.
    [51]李其林.重庆市土壤-作物系统重金属特征研究[D].西南大学博士学位论文,2008.
    [52]毛岭峰,彭培好,陈文德.重庆地区主要作物重金属富集特征[J].生态学杂志2009,28(6):1117-1122.
    [53]范昆仑,范先禄.重金属元素对重庆近郊作物污染状况调查[J].重庆工商大学学报(自然科学版),2004,6(21):549-551.
    [54]马成玲,周健民,王火焰.农田土壤重金属污染评价方法研究-以长江三角洲典型县级市常熟市为例[J].生态与农村环境学报.2006,22(1):48-53.
    [55]葛敏霞,袁旭音,叶宏萌.长江三角洲农灌区沉积物中重金属的污染特征及生态评价[J].农业环境科学学报2010,29(12):2398-2405.
    [56]邵学新,黄标,赵永存.长江三角洲典型地区土壤中重金属的污染评价[J]环境化学.2008,2(27):218-221.
    [57]钟晓兰,周生路,李江涛.长江三角洲地区土壤重金属污染的空间变异特征-以江苏省太仓市为例[J].土壤学报,2007,1(44):33-40.
    [58]曹淑萍.重金属污染元素在天津土壤剖面中的纵向分布特征[J].地质找矿论丛,2004,4(19):270-274.
    [59]王祖伟,张辉.天津污灌区土壤重金属污染环境质量与环境效应[J].生态环境,2005,14(2):211-213.
    [60]马传鑫,汪志荣,高琼.天津市典型污灌区冬小麦各生育期的重金属分析[J].环境化学,2010,1(29):44-47.
    [61]蒋丽婷.河北省唐山市丰润区土壤中重金属分布及土壤质量评价[D].中国地质大学(北京),2006.
    [62]李晓燕,陈同斌,谭勇壁.北京市小麦籽粒的重金属含量及其健康风险分析[J].地理研究,2008,6(27):1340-1345.
    [63]弓成,王海燕,黄丽.北京市土壤重金属形态分析[J].城市环境与城市生态,2006,5(19):38-40.
    [64]植满枝,陈杰,张学雷.北京市边缘区土壤重金属污染的初步研究[J].土壤通 报.2005,1(36):96-100.
    [65]霍霄妮,李红,孙丹峰.北京耕作土壤重金属含量的空间自相关分析[J].环境科学学报.2009,29(6):1339-1344.
    [66]孙雷,赵烨,李强.北京东郊污水与清水灌区土壤中重金属含量的比较研究[J].安全与环境学报.2008,8(3):29-33.
    [67]国家土壤环境质量二级标准值.(GB 15612-1995)
    [68]黄应丰,刘腾辉.华南主要土壤类型的光谱特性与土壤分类[J].土壤学报,1995,2:58-64.
    [69]祝建国,柴自渊,毛振才.还原气化-原子荧光光谱法快速测定绿色食品基地土壤中的砷与汞[J].分析测试技术与仪器,2002,8(2):103-106.
    [70]李民赞.光谱分析技术及其应用[M].北京:科学出版社,2006,115-125.
    [71]Kemper,T.S.Sommer.Estimate of Heavy Metal Contamination in Soils after a Mining Accident Using Reflectance Spectroscopy[J].Environmental Science & Technology,2002,36(12):2742-2747.
    [72]Goetz,A.F.H,Herring,M. The high resolution imaging spectrometer(HIRIS) for Eos[J].IEEE transaction on geosciences and remote sensing (S0196-2892), 1989,27:136-144.
    [73]万余庆,谭克龙,周日平著.高光谱遥感应用研究[M].科学出版社,2006:133.
    [74]浦瑞良,宫鹏.高光谱遥感及其应用[M].高等教育出版社,2000:89.
    [75]周清.土壤有机质含量高光谱预测模型及其差异性研究[D].浙江大学博士学位论文,2004.
    [76]王渊.不同水平油菜氮素含量遥感信息提取方法研究[D].浙江大学博士学位论文,2008.
    [77]赵英时等编著.遥感应用分析原理与方法[M].北京:科学出版社,2003.
    [78]魏建宏,罗琳,范美蓉等.赤泥不同施用量在土壤-水稻系统中生态效应的研究[J].湖南农业科学,2009,(10):39-42.
    [79]仲维功,杨杰,陈志德.水稻品种及其器官对土壤重金属元素Pb、Cd、Hg、As 积累的差异[J].江苏农业学报,2006,22(4):331-338.
    [80]徐永明.基于实验室光谱的土壤营养元素的反演研究[D].中国科学院遥感应用研究所硕士学位论文,2005.
    [81]丁国香.基于神经网络的土壤有机质及全铁含量的高光谱反演研究[D].南京信息工程大学硕士学位论文,2008.

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