Spectral reflectance characteristics to distinguish Malva neglecta in wheat (Triticum aestivum)
A field experiment was carried out to distinguishing Malva neglecta from wheat (Triticum aestivum L.) crop based on their spectral reflectance characteristics through remote sensing during rabi seasons of 2010-11and 2011-12. The investigation consists of six treatments each having different populat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Indian Council of Agricultural Research
2014-10-01
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| Series: | The Indian Journal of Agricultural Sciences |
| Subjects: | |
| Online Access: | https://epubs.icar.org.in/index.php/IJAgS/article/view/44208 |
| Summary: | A field experiment was carried out to distinguishing Malva neglecta from wheat (Triticum aestivum L.) crop based on their spectral reflectance characteristics through remote sensing during rabi seasons of 2010-11and 2011-12. The investigation consists of six treatments each having different population levels of Malva neglecta, viz. 0, 3, 6, 9, 12 plants/m2 and a treatment having pure population or solid stand of Malva neglecta. The results indicated a decreasing trend in effective tillers, number of grains/ear, 1000-grain weight and grain yield of wheat with increasing population densities of Malva neglecta from 3 to 12 plants/m2. Highest grain yield of wheat (5.75 tonnes/ha) was recorded under pure wheat treatment (solid stand) and lowest grain yield (3.24 tonnes/ha) was recorded in treatment having 12 plants of Malva neglecta/m2. Higher radiance ratio and NDVI values were recorded in pure wheat treatment and minimum in pure weed treatment. It was observed that by using radiance ratio and NDVI, pure wheat can be distinguished from pure populations of Malva neglecta after 30 DAS and remain distinguished up to 120 DAS and different levels of weed population can be discriminated amongst themselves from 60 DAS onwards. From the study it was concluded that remote sensing technology can be used for identification of different weed species and their infestations in field crops. Weed prescription maps can be prepared with Geographic Information System (GIS), on the basis of which farmers can be advised to take the preventive control measures.
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| ISSN: | 0019-5022 2394-3319 |