本文選題：春玉米 + 密度　； 參考：《石河子大學(xué)》2017年碩士論文

【摘要】：【目的】通過分析新疆地區(qū)不同密度下春玉米冠層結(jié)構(gòu)特征,冠層葉面積指數(shù)、產(chǎn)量與冠層高光譜相關(guān)關(guān)系,建立不同密度下春玉米冠層葉面積指數(shù)和產(chǎn)量的高光譜估算模型,為新疆地區(qū)春玉米長勢和產(chǎn)量估算提供依據(jù)�！痉椒ā吭谛陆煌河衩灼贩N、不同密度水平條件下開展大田試驗,測定了冠層光譜反射率、葉面積指數(shù)、分層葉面積、生物產(chǎn)量、株高、穗位、經(jīng)濟(jì)產(chǎn)量等數(shù)據(jù),分析在不同密度下累積葉面積指數(shù)、相對葉面積密度、生物產(chǎn)量、經(jīng)濟(jì)產(chǎn)量與高光譜的相關(guān)性,建立了葉面積指數(shù)、相對葉面積密度、生物產(chǎn)量、經(jīng)濟(jì)產(chǎn)量的相關(guān)模型并進(jìn)行模型精度的檢驗�！窘Y(jié)果】通過開展試驗研究,得到如下結(jié)果:(1)隨著密度的增大,玉米最長和最寬葉片葉位保持大致不變,葉寬隨著密度的增大而顯著減小,葉長隨著密度的增大先增大后減少;單株葉面積減小,基部葉片(1-6葉)葉面積變化不大,下部葉片(7-12葉)葉面積先增大后減小,中部葉片(13-16葉)不同年際間表現(xiàn)出不同差異,上部葉片(17葉及以上)葉面積逐漸減小;群體葉面積增加,中部及上部相對葉面積差異較大;莖干重差異較大,葉干重差異較小。在D3密度下,經(jīng)濟(jì)產(chǎn)量與穗位高、相對葉面積密度呈正相關(guān),與生物產(chǎn)量呈現(xiàn)負(fù)相關(guān),顯著性均少于0.05。(2)不同密度下,春玉米葉面積指數(shù)和相對葉面積密度的估算模型不同。葉面積指數(shù)的高光譜估算模型在D1,D2,D3密度下分別以RVI[497,935],DVI[720,936],DVI[551,724]為參數(shù)擬合的估算模型y=-0.0014x2+0.1201x+2.1747(R2=0.65),y=-30.405x2+10.122x+6.2617(R2=0.49),y=965.98x2-285.68x+29.929(R2=0.65)最好,RMSE分別為0.73、0.34、0.10。相對葉面積密度的高光譜估算模型在D1,D2,D3密度下分別以RVI[1143,947],R945,RDVI[712,552]擬合的估算模型y=-19.588x2+31.649(R2=0.61),y=-26.266x2+20.746x+10.726(R2=0.42),y=-2207.436x2+538.426x-17.601(R2=0.96)精度最高,RMSE分別為0.82,2.45,0.41。(3)不同密度下,春玉米產(chǎn)量的估算模型不同。生物產(chǎn)量的高光譜估算模型在D1,D2,D3密度下分別以NDVI[719,1080],R615,DVI[1020,671]擬合的估算模型y=75.205e2.668x(R2=0.62),y=-13894.287x2+1651.835x+110.938(R2=0.22),y=120.438x2-44.535x+95.499(R2=0.34)精度最高,RMSE分別為1.99,3.61,2.37。經(jīng)濟(jì)產(chǎn)量的高光譜估算模型在D1,D2,D3密度下分別以DVI[691,401],DVI[1102,533],NDVI[1122,780]擬合的估算模型y=1004.37e-0.716x(R2=0.58),y=21255.197x2-22028.232x+6757.953(R2=0.54),y=1122.356+19.933lnx(R2=0.39)精度最高,RMSE分別為1.24,1.13,2.37�！窘Y(jié)論】利用高光譜遙感可以對不同密度下春玉米冠層結(jié)構(gòu)參數(shù)及產(chǎn)量估算。
[Abstract]:[objective] to establish a hyperspectral estimation model of canopy leaf area index and yield of spring maize under different densities by analyzing the correlation between canopy structure, canopy leaf area index, yield and canopy hyperspectral spectrum of spring maize under different densities in Xinjiang. [methods] the field experiments were carried out in different spring maize varieties and different density levels in Xinjiang. The spectral reflectance of canopy, leaf area index and stratified leaf area were measured. Based on the data of biological yield, plant height, ear position and economic yield, the correlation of cumulative leaf area index, relative leaf area density, biological yield and economic yield with hyperspectral data was analyzed, and the leaf area index was established. Relative leaf area density, biological yield, economic yield, and model accuracy were tested. [results] through the experimental study, the following results were obtained: 1) with the increase of density, The leaf position of the longest and widest leaves of maize remained approximately unchanged, the leaf width decreased significantly with the increase of density, the leaf length increased first and then decreased with the increase of density, and the leaf area of single plant decreased, but the leaf area of basal leaf increased slightly. The leaf area of the lower leaves increased first and then decreased, the middle leaves showed different differences among different years, the upper leaves of 17 leaves and more) leaf area gradually decreased, and the population leaf area increased. The difference of relative leaf area between middle and upper part was great, the difference of stem dry weight and leaf dry weight was large, and the difference of leaf dry weight was small. Under D _ 3 density, the economic yield was positively correlated with ear height and relative leaf area density, and negatively correlated with biological yield (< 0.05. 2) under different densities, the estimation models of leaf area index and relative leaf area density of spring maize were different. The hyperspectral estimation model of leaf area index was fitted by RVI [497935] DVI [720936] DVI [551724] at D _ (1) C _ (2) D _ (2) D _ (3) densities, respectively. The estimated model y=-0.0014x2 0.1201x 2.1747R _ (2) O _ (2) 0.65 ~ (0.405x) 10.122x 6.26405x2 10.122x 6.2617R20.495.98x2-285.68x 29.929R2O _ (0.65) was the best one. The hyperspectral estimation model of relative leaf area density was fitted with RVI [1143947] R945N RDVI [712552] at D _ (1) C _ (2) D _ (2) density, respectively. The estimation model y=-19.588x2 31.649 ~ (9) ~ (2) ~ (0.61) ~ (1) ~ 0.61 ~ (1) ~ (1) -26.266x ~ (2) 20.746x 10.726x 10.726x ~ (2 +) R20.42y-2207.436x2 538.426x-17.601C ~ (0.96) the estimation models of spring maize yield were different at different densities. The hyperspectral estimation model of biological yield was fitted with NDVI [719C1080] R615DVI [1020671] under the density of D1C D2D3, respectively. The estimation model yt75.205e2.668xR2ON0. 62OUYYU -13894.287x2 165535x 110.93835x 110.938R2n 0.34) had the highest precision of RMSE of 1.99105e2.61kW 2.37. The hyperspectral estimation model of economic yield was fitted with DVI [691401] DVI [1102533] and NDVI [1122780] respectively under the density of D _ (1) O _ (2) D _ (2) C _ (3). [conclusion] the structural parameters and yield of spring maize canopy under different densities can be estimated by using hyperspectral remote sensing, respectively, at 212555.197x2-22028.232x 6757.953 R20.54 (R2122.356 19.933lnx / R20.39). [conclusion] using hyperspectral remote sensing, we can estimate the structure parameters and yield of spring maize canopy in different density.
【學(xué)位授予單位】：石河子大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S513;S127

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