利用累積溫度與資通訊技術提升稻作田間管理效率

Abstract

本研究以水稻臺稉9號與臺農71號為參試品種，探討水稻自插秧後生長至分蘗始期、幼穗分化期、始穗期及生理成熟期等四個生育階段之生長日數與溫度之間的關係。本研究採用10 ℃做為水稻生育的基礎溫度，利用生育階段所獲得生育日數與累積溫度計算積溫指標，以積溫指標對生育階段進行回歸分析，針對一、二期作分別進行三次多項式、非線性與多項式非線性等三種回歸模式配適，並依據積溫殘差評估兩品種在各期作的估計效率。結果顯示，多項式非線性模式對兩品種的一、二期作皆有良好的預測能力，均可準確估計四個生育階段所需的累積溫度。為將此研究成果應用於水稻栽培，利用本所與各區農業改良場完成的作物優質生產整合資訊平臺，開發一套水稻電子化栽培管理作業曆，根據前所完成之臺稉9號與臺農71號的積溫模式，建立一、二期作各生育階段所需的累積溫度資料。本作業曆透過農業氣象諮詢系統自動取得距離該農地最近的氣象測站資料，經由系統自動計算累積溫度，便可顯示目前水稻的生育階段，同時配合該生育階段相關的施肥、病蟲害防治、田間管理等工作，提供農民栽培的參考。 Investigate the relationship between growth days and temperature for rice growth stages: tillering, panicle intiation, heading and physiological maturity by TK9 and TNG71 variety. Calculate the growth days and cumulative temperature accumulated temperature index, rice growth and development base temperature by 10 ℃. Regression analysis on the accumulated temperature index and growth stages. Modeling fits of third order polynomial regression, nonlinear regression and polynomial nonlinear regression model for two crops, assessment of two varieties based on accumulated temperature residuals in each period for the estimated efficiency. The result showed that the polynomial nonlinear model for TK9 and TNG71 varieties of two crops for prediction capabilities, can accurately estimate the accumulated temperature of four growth stages. Apply the results of the rice cultivation, we further cooperated with the researchers of all Agricultural Research and Extension Stations of the Council of Agriculture for the joint establishment of the Integrated Information System for High-quality Crop Production. The creation process started from the establishment of the relationship model between plant growth and weather factors. First, we gathered meteorological data from the agricultural weather stations of the Central Weather Bureau and our improvised weather stations. Next, we applied a built-in model to compute and attain the correct growth period in order to create a dynamic cultivation management schedule. Up to now, we have applied the estimation of the accumulated temperature measurements during the growth period to predict the growth period of TK9 and TNG71 varieties. In this way, we can adjust the management work, such as irrigation, drainage, weeding, fertilization, and disease and pest control, at anytime pursuant to different growth periods.