臺灣博碩士論文加值系統

土壤中有機質之含量是評估地力的重要指標之一，而其長期分解趨勢及相關機制一向是土壤研究者的重要課題。如何以現有土地利用下的有機質含量預知最終可能的平衡含量及所需平衡時間是解決此一問題的方法之一。本研究引用特徵值與特徵向量的觀念以及修改碳轉化模式來探討長期7種不同施肥處理且水旱輪作系統下，土壤有機質的變化趨勢。其中，將碳轉化模式的模擬分成兩種不同的週期，分別是依照年度與栽種期而劃分。並在以栽種期為週期之模式中加入作物根影響土壤有機質累積的機制。然後再分別對兩模式作參數鑑定與動態模擬。最後，以年度為週期之模式在參數鑑定後，將其碳轉化方程式線性化為平衡模式，用來比較動態模式與平衡模式對預估平衡含量的差異。
研究結果顯示，矩陣構成時段內有機質含量測值所組成的數據方陣，其主特徵值可代表7種不同施肥處理之土壤有機質的共同轉化趨勢。而特徵向量權重值則可反映各施肥處理間採樣樣品平均值之比例關係，且此關係隨時間的延續依然存在。碳轉化模式分為兩種週期模擬土壤有機質動態達穩定時，兩種週期間各施肥處理之平衡順序有極顯著相關。而各添加有機質處理的最終穩定含量大小順序為泥炭＞堆肥＞綠肥＞化肥＞無施肥。因此使用何種週期模擬則可依所需的目標或收集資料的多寡來決定。將動態模式轉化為平衡式對各施肥處理之平衡順序亦有極顯著相關，這說明計算較方便之平衡式可取代動態模式之預估值。土壤有機質達穩定所需的時間則依不同週期模擬方法與對穩定所採取的定義不同而有明顯的差異。根據上述結果，本研究所提出之三種分析方法皆可有效掌握土壤有機質的變動特徵，且反應出不同土地利用型態之有機質穩定趨勢。

Content of soil organic matter is one of the important indicators in evaluation of soil fertility. The decomposition processes and mechanisms of soil organic matters have been one of the main researches for soil scientists. One of the topics is to know the soil organic matter content in equilibrium and how many years it will achieve under present land use. This study applied the concept of eigenvalue and eigenvector and modified a transformation model of organic carbon to analyze the transformation of soil organic matter for the experiments under paddy-upland crop rotations. The experiments had 7 treatments with long-term application of organic matter with different decomposition rate. Among the total, we separated transformation model into two different time sequence to identify the parameters and run the simulations respectively. One was for annual simulation; the other separated a year into four periods according to the sequence of autumn maize —fallow -spring rice -fallow rotations. In the four periods of simulation, we added the mechanism of roots of crops to influence the accumulation of soil organic matter. After identified the parameters for the annual simulation, we compared the eventual equilibrium tendencies of soil organic carbon content of the dynamic model with the equilibrium model transferred from linear transformation function of organic carbon.
The result showed that the soil organic matter in the same plot with 7 treatments shared a corporate transformation ratio, as known as the major eigenvalue, which was derived from the square matrix constructed by the measured data of soil organic matter content. The weighting values of eigenvector can refer to the simple ratios of the averages of sampled data between 7 treatments, and the relationship still exist with successive time period. When the final equilibrium tendencies of soil organic matter content was obtained by two models, the relationship between the orders of the equilibrium content of 7 treatments were significant. At equilibrium, the contents of soil organic matter follows the order (from high to low) of treatments amended with peat, compost, green manure and chemical fertilizers respectively. The relationship between the orders of the equilibrium content of 7 treatments calculated by dynamic model and equilibrium model was also significant. The years required to reach equilibrium of soil organic matter content were very different with different time sequence and the definition of equilibrium. It was concluded that three analytic methods provided in this study could usefully grasp the changes of soil organic matter, and could indicate the eventual equilibrium tendencies of soil organic matter contents with difference land use.

目錄
壹、前言……………………………………………………………….. 1
貳、文獻回顧………………………………………………………….. 3
一、土壤有機質的來源與組成………………………………….. 3
二、土壤有機物的累積與分解………………………………….. 5
三、土壤有機質達平衡時之含量與所需時間………………….. 6
四、土壤有機物質的合適含量及台灣土壤有機質含量現況….. 8
五、水旱輪作制度對土壤有機質含量的影響………………….. 9
六、有機質轉化模式之發展…………………………………….. 10
參、原理與方法……………………………………………………….. 17
一、田間資料的收集…………………………………………….. 17
二、數據的系統化與分析─矩陣特徵值之原理與應用……….. 26
三、碳轉化模式之引用與修飾………………………………….. 40
肆、結果與討論……………………………………………………….. 56
一、特徵值與特徵向量………………………………………….. 56
（一）、驗證主特徵值與伴隨主特徵值之特徵向量權重對有機質的關係……………………………………… 56
（二）、不同維度矩陣的分析……………………………… 60
（三）、連續時段主特徵值變化與全區有機碳平均含量關係之探討…………………………………………... 62
（四）、連續時段特徵向量權重值變動與矩陣列平均關係之探討………………………………....................... 64
（五）、矩陣中，時間為列、重複數為行的分析…………… 68
二、兩種不同時序模式的參數鑑定與動態模擬……………….. 73
〈一〉、模式一的參數鑑定與動態模擬…………………… 73
（二）、模式二的參數鑑定與動態模擬…………………… 78
三、模式一的兩種不同線性化平衡模式推估有機質之穩定趨向…………………………………………………………… 88
（一）、設變動斜率為零，穩定土壤有機質的預估……….. 88
（二）、轉化方程式藉歐拉法轉成線性特徵向量方程式求取平衡值…………………………………………… 89
伍、結論……………………………………………………………….. 96
陸、參考文獻………………………………………………………….. 98
表次
一、耕種前試驗區土壤的各項分析值…………………………… 22
二、0─15公分內，七種不同施肥處理下，土壤有機態碳含量…… 23
三、不同栽種時期，玉米和水稻根之有機碳含量測值…………… 25
四、84年與85年，七種不同施肥處理下，土壤有機態碳含量…… 31
五、表四構成之數據矩陣，列互換後所有主特徵值與伴隨主特徵值之特徵向量權重值的分布範圍表……………………… 59
六、不同維度矩陣之主特徵值與特徵向量以及特徵向量與列平均之相關係數………………………………………………… 61
七、連續時段，矩陣之行列為時間與處理其特徵向量權重值之修正………………………………………………………….... 65
八、以時間為列(八個採樣時間)，八個重複採樣點為行構成矩陣
(以對照組數據為例)………………………………………….. 70
九、連續時段下，部分矩陣之特徵向量權重值(以對照組為例)……………………………………………………………... 71
十、連續時段下，部分矩陣之改良特徵向量權重值(以對照組為例)……………………………………………………………... 72
十一、模式一之參數鑑定值………………………………………….. 76
十二、模式一對土壤有機質達平衡所需時間與穩定含量之預估….. 77
十三、模式二，七種施肥四種耕種期的實測值與模擬值間相關係數……………………………………………………………… 84
十四、模式二對土壤有機質達平衡所需時間與穩定含量之預估….. 86
十五、兩動態模式預估土壤有機質穩定值之比較………………….. 87
十六、土壤有機質達平衡時，動態模式與平衡模式及特徵樣量權重值之相關比較……………………………………………… 92
十七、模式一之平衡值與轉移矩陣特徵向量之相關性…………….. 93
圖次
一、田間試驗處理平面圖………………………………………….. 21
二、有機碳平均含量與權重值之關係圖………………………...... 33
三、特徵值之Gershgorin定理示意圖……………………………... 38
四、表四所構成之數據矩陣的特徵值Gershgorin定理…………... 39
五、CERES-玉米生長模式中土壤碳氮轉化次模式示意圖……… 42
六、連續時段之特徵值變化與其有機碳含量關係圖…………….. 63
七、連續時段下，修正特徵向量權重值與列平均之相關圖……… 67
八、自84年秋作玉米開始種植到90年水稻收獲後之土壤有機態碳的動態模擬結果與相關係數…………………………… 75
九、土壤有機態碳對日期圖 (以CK組為例)……………………. 80
十、以Logistic方程式模擬玉米根重……………………………… 81
十一、以Logistic方程式模擬水稻根重……………………………… 82
十二、模式二土壤有機態碳模擬值與實測值之比較(以對照組為例)……………………………………………………………... 83
十三、長期模擬下，土壤有機質的變動趨勢圖……………………… 85
十四、修正過之特徵向量權重值隨時間的變動趨勢圖…………….. 94
十五、改良過之特徵向量權重值隨時間的變化圖………………….. 95

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