MODELING THE LONG-TERM YIELD EFFECTS OF COMPENSATION IN INTERCROPPINGUSING DATA FROM A FIELD EXPERIMENT

Citation
S. Morse et al., MODELING THE LONG-TERM YIELD EFFECTS OF COMPENSATION IN INTERCROPPINGUSING DATA FROM A FIELD EXPERIMENT, Experimental Agriculture, 33(3), 1997, pp. 291-299
Citations number
6
Categorie Soggetti
Agriculture
Journal title
ISSN journal
00144797
Volume
33
Issue
3
Year of publication
1997
Pages
291 - 299
Database
ISI
SICI code
0014-4797(1997)33:3<291:MTLYEO>2.0.ZU;2-M
Abstract
Employing data from an intercropping field experiment which measured t he yields achieved by a surviving crop when the other crop failed at 0 , 6 or 10 weeks after sawing, the use of a simple computer model to st udy the long-term yield effects of compensation in intercropping is de scribed. Assuming different probabilities of crop failure for one or b oth of the crops, the model provided a comparison of long-term intercr op and sole crop yields from intercropping systems of oat-mustard, mus tard-bean and oat-bean. It showed that if failure was restricted to on ly one of the crop species, intercropping suffered less yield decline with increasing probability of failure than did sole cropping only if there was a sufficiently high yield of the surviving crop. However, in the more realistic situation where each crop was subjected to the pos sibility of failure, this decline in yield was less in intercropping t han sole cropping for all three combinations because poor yields when one species was the surviving crop were offset by good yields when the other species was the survivor. Mustard-oat and mustard-bean gave no yield advantage in the absence of failure (Land Equivalent Ratios less than 1) but they outyielded sole cropping for failure probabilities a bove about 5% and 15%, respectively. All combinations gave large inter cropping advantages at high probabilities of failure. Oat-bean always had a strong yield advantage, even with no failure. The model is very simplistic but it illustrates the potential for modelling long-term ef fects from field data. Limitations of the model are discussed and it i s emphasized that these can be overcome if information to make the und erlying assumptions more realistic is available.