The effects of five weed management techniques and a weed free control on weed infestation andon the growth and yield of a plantain landrace (Musa spp. AAB Agbagba) were evaluated during the twocropping seasons of 2005 and 2006 at Nsukka, Nigeria. The experiment was laid out in randomisedcomplete block design (RCBD) with six treatments and replicated four times. The treatments comprised sixweed management techniques, which consisted of slashing at 8-weekly intervals, mulching with sawdustalone, use of glyphosate + intermittent slashing, use of sawdust mulching + glyphosate, use of glyphosate
alone and a weed-free (by hoeing) control.
Results of the study showed that there was a significant(P<0.05) difference in the effectiveness of the various weed management techniques on weed control.Mulching + glyphosate treatment was the most effective weed control technique compared to othertreatments. The result also showed a significant (P<0.05) difference in the suckering ability as a result ofthe mulching effect. This was such that mulched plots produced the highest number of suckers with a meanvalue of 4.2 and glyphosate alone treated plots produced the least number of suckers with a mean value ofl.7 at 36 WAT. Plant heights, number of leaves, leaf area and fruit yield were also significantly (P <0.05)affected by the treatments. The result showed that mulching + glyphosate weed management strategysupported the best plant growth with mean values of 139.7 cm, 4.3 and 12348.8 cm2 for plant height,number of leaves and leaf area respectively without any lodging. The treatment also supported the best fruityield of 12.1t/ha with the highest benefit/cost ratio of 3.87 and gross margin of 74.2 as compared to the rest of the other treatments.
The effects of five weed management techniques and a weed free control on weed infestation andon the growth and yield of a plantain landrace (Musa spp. AAB Agbagba) were evaluated during the two cropping seasons of 2005 and 2006 at Nsukka, Nigeria. The experiment was laid out in randomized complete block design (RCBD) with six treatments and replicated four times. The treatments comprised sixweed management techniques, which consisted of slashing at 8-weekly intervals, mulching with sawdustalone, use of glyphosate + intermittent slashing, use of sawdust mulching + glyphosate, use of glyphosate
alone and a weed-free (by hoeing) control.
Results of the study showed that there was a significant(P<0.05) difference in the effectiveness of the various weed management techniques on weed control.Mulching + glyphosate treatment was the most effective weed control technique compared to othertreatments. The result also showed a significant (P<0.05) difference in the suckering ability as a result ofthe mulching effect. This was such that mulched plots produced the highest number of suckers with a meanvalue of 4.2 and glyphosate alone treated plots produced the least number of suckers with a mean value ofl.7 at 36 WAT. Plant heights, number of leaves, leaf area and fruit yield were also significantly (P <0.05)affected by the treatments. The result showed that mulching + glyphosate weed management strategysupported the best plant growth with mean values of 139.7 cm, 4.3 and 12348.8 cm2 for plant height,number of leaves and leaf area respectively without any lodging. The treatment also supported the best fruityield of 12.1t/ha with the highest benefit/cost ratio of 3.87 and gross margin of 74.2 as compared to the rest
of the other treatments.
📚 Over 50,000 Research Thesis
📱 100% Offline: No internet needed
📝 Over 98 Departments
🔍 Thesis-to-Journal Publication
🎓 Undergraduate/Postgraduate Thesis
📥 Instant Whatsapp/Email Delivery
The project titled "Utilizing Internet of Things (IoT) Technology for Precision Agriculture in Forestry Management" aims to explore the application of...
The project titled "Implementation of Precision Agriculture Techniques for Enhanced Crop Yield and Resource Management in Forestry Plantations" aims t...
The project titled "Automation of Crop Monitoring and Management Using IoT Technology in Agriculture" aims to revolutionize the agricultural sector by...
The project titled "Utilizing Artificial Intelligence for Precision Agriculture in Forestry Management" aims to explore the integration of cutting-edg...
The research project titled "Utilizing Internet of Things (IoT) technology for precision agriculture in optimizing crop production and resource management&...
The project titled "Utilizing Machine Learning for Predicting Crop Yields and Pest Outbreaks in Agricultural Fields" aims to leverage advanced machine...
The project titled "Utilizing Machine Learning Algorithms for Improved Crop Yield Prediction in Agricultural Farms" aims to leverage advanced machine ...
The project titled "Utilizing Artificial Intelligence for Precision Agriculture in Forestry Management" aims to explore the integration of artificial ...
The project titled "Implementation of Precision Agriculture Techniques for Improved Crop Yield and Resource Management in Forestry Plantations" aims t...