26 lines
2.6 KiB
Plaintext
Executable File
26 lines
2.6 KiB
Plaintext
Executable File
TY - JOUR
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T1 - A simple model to predict phenology in malting barley based on cultivar thermo-photoperiodic response
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JO - Computers and Electronics in Agriculture
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VL - 107
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IS -
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SP - 8
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EP - 19
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PY - 2014/9//
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T2 -
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AU - Alzueta, Ignacio
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AU - Arisnabarreta, Sebastián
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AU - Abeledo, L. Gabriela
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AU - Miralles, Daniel J.
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SN - 0168-1699
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DO - http://dx.doi.org/10.1016/j.compag.2014.05.011
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UR - http://www.sciencedirect.com/science/article/pii/S0168169914001343
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KW - Barley
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KW - Heading date
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KW - Photoperiod response
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KW - Phenology prediction
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AB - Abstract
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In the Pampean region of Argentina, farming systems are based on intensive land use, wheat/soybean double cropping being a key component of these agricultural systems. However, during the last years farmers have been replacing wheat for barley due to its earlier maturity date, reducing yield penalization in soybean as a consequence of delays in its sowing date, and improving the economic profits of the double cropping system. To maximize the benefits of barley/soybean double cropping system, the proper timing of key barley ontogenic stages should be easily identifiable by farmers. The objectives of the present study were to (i) characterize crop phenology through thermo-photoperiod models in response to different sowing dates, (ii) use the algorithms calculated in point (i) to generate a simple model for predicting phenology, using historical climatic series, and (iii) validate the model with independent data. Barley cultivars used in the present study did not show vernalization requirements. Variations in phenology, measured in thermal time, were mainly associated with variations in photoperiod sensitivity during the emergence-heading phase. Significant differences in photoperiodic sensitivity, from −65 °Cd h−1 (Scarlett) to −344 °Cd h−1 (Q. Ayelen), were observed among cultivars. However, cultivars did not show significant differences in critical photoperiod or intrinsic earliness. The slope of the relationship between heading time and date of emergence, calculated from the algorithms used to build the model, based on thermo-photoperiodic response, varied between locations and cultivars. When the model was tested with an independent data set, predictions for the sowing-flowering phase showed a root mean square error lower than 4% (similar to that observed using more complex models). The algorithms used in the model were masked into a friendly frame and outputs were shown in a simple and attractive manner for users. The model was uploaded to the web site of the University of Buenos Aires to be used by students, advisors, professionals and farmers barley.
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