土壤變異之精準管理
Other Title
Precision Management of Soil Variability
Journal
水稻精準農業(耕)體系之研究
Part Of
水稻精準農業(耕)體系之研究
Pages
53-64
ISBN
957-02-5829-2
Date Issued
2000-04
Date
2000-04
Author(s)
Abstract
土壤變異的精準管理是應用資訊與技術來管理田間土壤的空間與時間變異，以便作物有良好之生長而同時也能維護環境的品質。此種精準管理，通常會利用方格取樣法、基標土壤取樣法或地景導向取樣汰來採取土壤樣本進行土壤分析，而後利用地理統計或地理資訊系統來觀察土壤肥力變異之情形，進而探討出影響產量的重要土壤因子，加以合理解釋與擬定管理的策略。土壤肥力的精準管理主以石灰及氮、磷、鉀肥之定點施用為主要對象。土壤pH、有效性磷及鉀之時問變異性較低，而土壤有效氮在土壤中之空問及時問變異性均較高。在磷鉀肥力之精準管理主以土壤有效性磷、鉀之高低（禾穀類作物）來推荐各不同定點之肥料用量。而精準氮肥管理的問題就比較複雜，氮肥之推荐目前之研究發展包括氮素收支平衡扶、條帶試驗法及作物含氮狀況監測汰。管理區之規劃是精準肥培一項新的理念，不同的統計方法已被應用在管理區之劃分上，包括線性、非線性、非母數分析如PPR、類神經網路等。由於台灣為小農制，管理區之理念在精準農業之利用值得我們加以考慮。
Precision management of soil variability is the application of information and technology to manage spatial and temporal variability of soils associated with crop growth for the purpose of improving crop production and environment quality. Soil collections with grid sampling, benchmark soil sampling or landscape directed soil sampling are usually the first step in assessing the spatial variation. Techniques of geostatistics and/or geographic information system are applied to investigate the soil fertility variability. Reliable interpretation on soil fertility variability affecting Ofl crop yield, crop quality, and/or the environment is needed in order to implement the site-specific inputs. Main category of precision fertility management includes liming and management for N, P and K. For N, the temporal component of variability can be larger than its spatial variability. Soil pH and available P and K in soils tend to have stable spatial variability. The site-specific recommendations for the inputs of P and K usually rely on soil tests; whereas that for N recommendation is more complex. Research on precision N management to date has taken three basic approaches: N budgeting, N strip experiments within fields and crop monitoring of N status. Management zones are a good concept for precision fertility management. Numerous statistical methods, including linear, non-linear, and non-parametric regression analyses such as projection pursuit regression (PPR) and neural network analysis have been used for modeling yields as a function of soil data in identifying management areas within fields. Since Taiwan agriculture belongs to small-holder production, it is suggested that the application of management zone concepts worth us to consider if we want to implement the precision agriculture in Taiwan.
Subjects
精準農業
土壤變異
地理統計
土壤肥力
精準管理
土壤感測器
Precision agriculture
Soil variability
Geostatistics
Soil fertility
Precision management
Soil sensor
Publisher
農業試驗所
Type
book chapter
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