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Remote Sensing Techniques to Map Nitrogen Status of Rice Plants within Fields
|關鍵字:||Rice (Oryza sativa L.);Canopy nitrogen status;dR/dλ│735;Remote sensing technique;Hyperspectral image;Narrowband flilter;Leaf anatomy;Canopy reflectance;Total chlorophyll content;水稻;植被(冠)含氮狀態;dR/dλ│735;遙測技術;高光譜影像;窄波段濾片;葉片解剖;植被反射比;葉綠素總量||出版社:||土壤環境科學系所||引用:||Adamsen, F.J., P.J. Pinter, Jr., E.M. Barnes, R.L. LaMorte, G.W. Wall, S.W. Leavitt, and B.A. Kimball. 1999. Measuring wheat senescence using a digital camera. Crop Sci. 39:719-724. Baret, F., S. Jacquemoud, G. Guyot, and C. Leprieur. 1992. Modeled analysis of the biophysical nature of spectral shifts and comparison with information content of broad bands. Remote Sens. Environ. 41:133-142. Blackmer, T.M., J.S. Schepers, and G.E. Varvel. 1994. Light reflectance compared with other nitrogen stress measurements in corn leaves. Agron. J. 86:934-938. Blackmer, T.M., J.S. Schepers, G.E. Varvel, and E.A. Walter-Shea. 1996. Nitrogen deficiency detection using reflected shortwave radiation from irrigated corn canopies. Agron. 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Chen. 2007. Differences in growth estimation and yield prediction of rice crop using satellites data simulated from near ground hyperspectral reflectance. J. Photogram. Remote Sens. 12:93-105.||摘要:||
Nitrogen (N) is the most important nutrient to increase and stabilize yield of paddy rice, and the spatial distribution of N status of rice plants within field is the primary information needed for precision management of N fertilizer. A better yield production and grain quality can be expected by applying suitable amounts of N fertilizer at right time to the right place site-specifically with N map. This research was first to investigate changes in plant N concentration and leaf total chlorophyll content upon applying different rates of N fertilizer during rice (Oryza sativa L. cv. Tainung 67) growth, and then to examine whether the alterations in leaf internal structure and morphology related to variation in N status. The relations of leaf total chlorophyll content, internal structure and morphological characteristics, and plant N concentration to the canopy reflectance behavior were further studied. As the results shown, applying N fertilizer from 0 to 180 kg N ha-1, with 60 kg N ha-1 intervals, changed leaf total chlorophyll and plant N concentration measured in the panicle initiation/formation stage. Plant applied with higher N rates tended to have higher amounts of leaf total chlorophyll and absorbed more light in the visible region of incident solar radiation. The mean reflectance of BLUE (425-490 nm), GREEN (490-560 nm) and RED (640-740 nm) wavebands showed a negative relationship with leaf total chlorophyll, a decreased in reflectance with the increase of chlorophyll content. A diversity of anatomical and morphological characteristics of leaves was observed to be modulated by N concentration in rice plants grown in both first and second cropping seasons. Leaf thickness increased progressively with increasing plant N concentration, and rice plants grown in second crop had a tendency to have thicker leaf blades than those grown in first crop with the same N concentration. The extent of leaf rolling was relieved by the increasing N status and a linear relationship between value of leaf rolling index (LRI) and aboveground N concentration was fitted. Changes in bulliform/mesophyll ratio to aboveground N concentration were a quadratic function, the ratio increased to a plateau and decreased thereafter. Leaf water content (LWC) also changed in a curvilinear trend in the measured range of aboveground N concentration, and leaves of plants grown in first crop had higher LWC than those plants grown in second crop under the same N level. A loose distribution and packing pattern of starch granules was found in the parenchyma cells of plants with higher N status relative to those of lower N ones. Application of varied rates of N fertilizer also affected canopy reflectance behavior of different wavebands. The mean reflectance of waveband at BLUE, GREEN and RED decreased while NIR (740-1100 nm) increased with the increasing aboveground N concentration and LRI. Secondly, as the spatial distribution of canopy N map within a field is the primary information needed for precision management of N fertilizer, this research developed a simple spectral index (SI) using the first derivative values of canopy reflectance spectra at 735 nm (dR/dλ│735) to assess N concentration of rice plants and validated the applicability of a simplified imaging system based on the derived spectral model from the N─dR/dλ│735 to assess N concentration of rice plants and validated the applicability of a simplified imaging system based on the derived spectral model from the N─dR/dλ│735 relationship in mapping canopy N status within fields from two remote sensing platforms. Results showed that values of dR/dλ│735 were linearly related to plant N concentrations measured at the panicle initiation/formation stage of first crop in 2001. The N─dR/dλ│735 relationship (R2 = 0.679, P < 0.001) was better fitted than the N─NDVI (normalized difference vegetation index) relationship (R2 = 0.471, P < 0.010), and remained valid (R2 = 0.514, P < 0.001) when more data from different cropping seasons in varied years and locations were pooled . The composite regression model provided fair results (r = 0.554, P < 0.010) in validation test with another datasets collected from different crops and locations. The ratio-based SIs SRVI (simple ratio vegetation index) (R2 = 0.519, P < 0.001), R810/R560 (R2 = 0.453, P < 0.001), NDVI (R2 = 0.355, P < 0.001), and (R1100-R660)/(R1100+R660) (R2 = 0.111, P < 0.010) were also correlated with plant N concentration to a varied extent. Based on the as aforementioned N─NDVI relationship, a simplified imaging system, including an Electrim EDC-1000L monochrome camera, a Canon PHF6 1.4 lens, a set of Andover bandpass filters (730 nm and 740 nm), and an Advantech PCA6751 single board computer, was finally assembled and mounted on a mobile lifter and a helicopter to take spectral images of rice canopies for mapping the N status within fields. Results indicated that the system unit was able to provide field maps of canopy N status with reasonable accuracy (r = 0.465 to 0.912, RMSE = 0.100 to 0.550) from both remote sensing platforms. It appears that spatial information of N status obtained from this research may have a potential used for variable-rate applications of N fertilizer during the panicle initiation/formation stage. The validation tests on a variety of stress identification indices derived from ground spectroradiometer measurements can also be easily performed with the established simplified imaging system following the process such as this research.
氮素是提高和穩定水稻生產最重要的營養元素之一，田間水稻植株含氮狀態的空間分佈則係精準施用氮肥最主要的圖繪資訊。經由田間稻株含氮狀態空間分佈圖繪，將不等量氮肥於特定時間施用於農田特定位置的精準做法，將可預期獲得較佳之產量與米質。本研究首先調查田間栽培水稻生育期間施用不等量氮肥造成稻株植體含氮濃度及葉片葉綠素總量之改變，接著檢視葉片內部構造及形態隨著含氮狀態變化形成之差異，再進一步探討葉片葉綠素總量、內部構造與形態特徵、以及植體含氮濃度對植被反射比行為之影響。根據試驗結果，發現介於0-180 kg N ha-1氮肥施用範圍，不等氮肥施用量將改變穗啟始期-形成期量測之植體含氮濃度及葉片葉綠素總量，稻株施用高氮肥量者具有較高植體含氮濃度及葉片葉綠素總量，而且吸收較多入射太陽光之可見光波段。在可見光不同波段反射比與葉片葉綠素總量的關係上，藍光(425-490 nm)、綠光(490-560 nm)及紅光(640-740 nm)波段之平均反射比皆與葉綠素總量呈現直線負相關，即各波段反射比隨葉綠素總量上升而下降。無論一、二期作稻株，葉片之許多解剖與形態特徵均顯示受到植體含氮濃度之影響。當植體含氮濃度增加時，葉片厚度隨著增厚，在相同植體含氮濃度下生長於二期作之稻株葉片厚度大於生長於一期作之稻株葉片厚度。高含氮量稻株之葉片捲曲程度較小，具有較高之葉片捲曲指數(LRI)，而LRI與地上部植體含氮濃度之間呈現直線正相關。Bulliform/mesophyll ratio與地上部植體含氮濃度關係適用於一元二次函數，此一比值隨著氮濃度增加而上升，到達一高原期後則下降。葉片水分含量(LWC)亦伴隨地上部植體含氮濃度的增加呈現曲線變化，而在同一含氮濃度水準下，一期作稻株之LWC較二期作稻株之LWC高。高含氮狀態稻株之葉片薄壁細胞的澱粉粒分佈較為鬆散，排列也較不緊密。施用不等量氮肥另影響水稻植被不同波段反射比之表現，藍光、綠光及紅光波段之平均反射比隨著稻株含氮濃度與LRI測值增加而下降，近紅外光(740-1100 nm)波段之平均反射比則反之。由於田間水稻植被含氮狀態提供氮肥精準管理所必需，本研究乃繼續探究水稻植被反射光譜與植體氮營養狀況之關係，以建立適用於評估稻株含氮狀態之簡易光譜指數(spectral index, SI)。經分析2001年一期稻作之幼穗起始期-穗形成期間植被光譜範圍(350-1100 nm)各窄波段反射比與植體含氮濃度之關係，發現735 nm波段反射比之一次微分值(dR/dλ│735)與植體含氮濃度之關係，發現735 nm波段反射比之一次微分值(dR/dλ│735)與植體含氮濃度呈線性正相關(R2 = 0.679, P < 0.001)，可利用作為估測稻株含氮狀態之光譜指數，且其相關性優於標準差植被指數(NDVI)與植體含氮濃度之線性相關(R2 = 0.471, P = 0.0023)。續而納入分別於臺北、臺中、嘉義、屏東等不同地區進行之兩年期量測資料，顯示以N─dR/dλ│735關係建立的稻株含氮狀態遙測模式之決定係數(R2)達到0.514的極顯著水準。經再以臺北、嘉義和屏東三個試區不同期作的735 nm波段一次微分值與稻株含氮濃度做驗證，其相關係數(r)值仍可達到0.554的顯著水準。此外，比值型光譜指數諸如簡易比植被指數(simple ratio vegetation index, SRVI; R2 = 0.519, P < 0.001)、R810/R560 (R2 = 0.453, P < 0.001)、NDVI (R2 = 0.355, P < 0.001)及(R1100-R660)/(R1100+R660) (R2 = 0.111, P < 0.010)等，與植體含氮濃度之間亦發現具有不等程度的相關性。據此試驗結果，顯見本研究所建立的水稻族群含氮狀態分佈遙測模式，確可利用於快速鑑別穗起始期-形成期間稻株氮營養狀態。而以此遙測模式為基礎構建之簡易型影像拍攝系統，則試驗證明可以作為測定及圖繪田間水稻族群含氮狀態分佈等用途。此項簡易型光譜影像拍攝系統由電子式單彩相機(EDC-1000L)、鏡頭(Canon PHF6 1.4 lens)、窄波段濾片(Andover bandpass filters 730 nm及740 nm)及工業用單版電腦(Advantech PCA6751)組成，並內建自行開發需用的軟體程式。將本研究建立之稻株含氮狀態遙測模式及簡易型影像拍攝系統，依照田間作業需求掛載於高空作業車或直昇機上，發現圖繪之田間水稻族群含氮狀態分佈均獲得合理估測之結果(r=0.620 to 0.912, RMSE= 0.100 to 0.151)。顯然的，經由本研究方法圖繪之穗起始期-形成期稻株含氮狀態空間變異分佈具有使用於可變率氮肥施用之應用潛力，所構建之簡易型影像拍攝系統，亦能延伸應用於其他近地面光譜資料建立之逆境鑑別指數驗證之用。
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