By Donald L. Sparks (Ed.)
Advances in Agronomy is still famous as a number one reference and a major resource of the newest and top examine in agronomy. As consistently, the subjects coated are different and exemplary of the panoply of material handled by means of this long-running serial. quantity sixty seven includes 4 finished and well timed reports on subject matters within the crop and soil sciences. bankruptcy 1 addresses some of the most lively components in agronomic research--precision agriculture. bankruptcy 2 is a considerate overview on floor cost and solute interactions in soils. bankruptcy three completely covers advances within the use of molecular genetics to reinforce abiotic/edaphic tension resistance in turfgrass. bankruptcy four is an invaluable evaluate on a subject matter that's of serious curiosity to agronomists--allelopathy.
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The crop production process ia more complex than this deterministic assertion would suggest. However, within a given climate regime, we should expect crop performance to generally correspond to differences among soils and landscapes. Yield mapping has supported this general relationship. The value of the soil survey to precision agriculture could be improved by intensifying map scales to ﬁne scale resolutions needed in detailed en- 20 FRANCIS J. , 1993). Accomplishing this is no small task. , 1993).
For successful implementation, the concept of precision soil fertility management requires that within-ﬁeld variability exists and is accurately identiﬁed and reliably interpreted (fertilizer recommendations are site speciﬁc), that the variability inﬂuences crop yield, crop quality, and/or the environment, and that inputs can be applied accurately (Sawyer, 1994; Pierce, 1995). We hypothesize that the ease with which precision management is accomplished and its value vary with speciﬁc nutrients or lime.
Additionally, it is not physically or economically possible to accurately map certain soil properties, crop condition, or pest status without the use of high-resolution sensing. The lower cost and ease of measure of high-resolution sensors will be critical to the future success of precision agriculture. d. , 1995a). Models have been developed and calibrated for speciﬁc purposes but have not been used extensively in spatial prediction. A major problem of models is the availability of inputs needed to run them.