生態農業：農業精準栽培管理技術開發【土壤環境科學系申雍教授】
| 論文篇名 | 英文：Estimation of nitrogen status of paddy rice at vegetative phase using unmanned aerial vehicle based multispectral imagery 中文：應用無人機多光譜影像估算水稻營養期氮素狀況 |
| 期刊名稱 | Precision Agriculture |
| 發表年份,卷數,起迄頁數 | 2021 on line published but still in queue for printing |
| 作者 | Wang, Yi-Ping; Chang, Yu-Chieh; Shen, Yuan(申雍)* |
| DOI | 10.1007/s11119-021-09823-w |
| 中文摘要 | 精確施用氮肥取決於能否對作物氮含量進行準確的估計。由於背景（例如浸水、裸土、藻類等）對波段反射率的複合影響，通過遙感影像評估水稻早期生長階段的植物氮含量變得複雜。此外，營養階段作物氮含量的快速變化，也使得開發可操作的預測模型的工作變得非常困難。本研究應用配備多光譜傳感 器的四旋翼無人機獲取的航拍影像，估計水稻在營養階段的氮含量狀態。試驗於 2018 年至 2020 年在農業試驗所的試驗農場進行，並引入變量 N 指數（待 評估植物的 N 含量與未施氮肥的植物之間的比率）來解決與植物營養階段氮含量快速變化相關的問題。從航拍圖像中去除背景對波段反射的干擾後，確定 了最合適的植被指數和能夠捕捉水稻 N 指數變化的時期。發現基於標準化差異紅邊指數 (NDRI) 和紅邊葉綠素指數 (RECI) 的模型與來自移栽後 30 天（DAT）至 55 DAT 期間（即水稻產量和籽粒質量的最關鍵時期）的 N 指數值相關性良好。本研究也將開發的模型用於顯示實驗田內植物氮狀態的時空異 質性，作為案例說明如何使用該模型。在該案例中，應用 SPAD 測值作為各種 DAT 下植物氮含量的替代物，以建立將 N 指數圖轉換為 SPAD 分佈圖以實現 進行可變率的精準施肥管理。 |
| 英文摘要 | Precision nitrogen fertilizer application depends on accurate estimation of plant nitrogen content. However, the assessment of plant nitrogen content at early growth stages of paddy rice through remote sensed images is complicated by the compound effects of backgrounds (e.g. flood water, bare soil, algae, etc.) on the band reflectance. The rapid changing of plant nitrogen content during the vegetative phase makes the development of an operational prediction model very difficult. In this study, aerial images acquired by a quadcopter unmanned aerial vehicle (UAV) equipped with a multispectral sensor were used to estimate plant nitrogen content at vegetative phase of rice crops. The experiments were conducted at the experimental farm of Taiwan Agricultural Research Institute (TARI) from 2018 to 2020. A variable, N-index (ratio between N content of plants to be evaluated and plants not receiving N fertilizers), was introduced to resolve the issues related to rapid changing of plant N content during the vegetative phase. After removing the interference on band reflectance by background from the aerial images, the most appropriate vegetation indices and period that can capture the variations of N-index of rice plants were identified. It was found that a normalized difference red edge index (NDRI) and red edge chlorophyll index (RECI) based model correlated well with the N-index values from c.a. 30 days after transplanting (DAT) to 55 DAT (i.e., the most crucial period for rice yield and grain quality). The developed model was then used to display the spatial and temporal heterogeneity in plant nitrogen status within an experimental field as an example to illustrate how to use the model. In the example, soil plant analysis development (SPAD) meter values at locations of various levels of estimated N-index were collected as surrogates of plant nitrogen content at various DATs to build relationships for converting N-index maps to SPAD maps for potential variable rate fertilizer application management. |
| 發表成果與本中心研究主題相關性 | 本研究以無人機拍攝水稻生育狀態影像，建立偵測水稻插秧期至抽穗期間稻株氮營養狀態的遙測推估技術，可用於水稻精準施肥，減少氮肥的過量施用，降低過量施肥對環境生態所造成的危害。 |
