Abstract
ABSTRACT Efficient utilization of agricultural resources requires a better understanding of crop growth and development. Current modeling efforts aimed at predicting the response of plants to environmental conditions lack the ability to relate results to basic characteristics observed in the field. The ability to reliably evaluate both photometric and morphometric parameters for individual plants would not only improve existing models but also create a database from which new models may be generated. A vision-based data collection system was developed to study the growth and development of com plants. Slide photographs were taken of field specimens at given intervals throughout the 1989 growing season. These images were scanned into the system and processed using software developed for this project. This article outlines both the plant collection procedures as well as the analysis techniques included in the software package. Software supplied with the slide scanner and internally developed image processing algorithms were evaluated prior to data analyses. From 64 to 320 attributes were obtained for each plant and later combined with associated meteorological information to form a developmental database. Results from the analyses involving these databases will be detailed in later publications.
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