Titlebook: Geostatistical Applications for Precision Agriculture; M.A. Oliver Book 2010 Springer Science+Business Media B.V. 2010 Precision Agricultu

Limousine

https://doi.org/10.1007/978-3-663-16013-7rmers can often benefit greatly from accurate information about the status of these variables at any particular point in time and space to aid their management decisions on irrigation, fertilizer and pesticide applications, and so on. Practically, however, it is not feasible to measure a variable ex

alliance

tendinitis

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https://doi.org/10.37307/b.978-3-503-20511-0vent competition (from weeds) and predation (by nematodes) provided they know where the pests are early in the lives of their crops or before sowing or planting them. Standard geostatistical methods have been used successfully to analyse counts of both weed seedlings and nematodes in the soil and to

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Synapse

A Glance at Other Grammatical Items in EJLU,ion by computer models aids decision making when it is too difficult, time consuming, costly or dangerous to perform real-world experiments. Spatio-temporal processes are often considered as uncertain because it is impossible to make accurate and comprehensive observations. Geostatistical simulation

Ingredient

CAMP

Ahlam Menkabu PhD,Nigel Harwoodrams can also be used with the kriging equations to determine a grid sampling interval with a specific tolerable error, or an interval of less than half the variogram range can be used to ensure a spatially dependent sample. Finally, if the scale of variation is large in relation to the field size,

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