Performance evaluation of weeder by number of blades per flange in chilli crop

Devojee, B.; Meena, SS; Sharma, Ashutosh; Agarwal, Chiti

doi:10.22271/chemi.2020.v8.i2k.8855

Cited by 5 publications

(8 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It helps the non-rotary blade for more penetration. Similar depth of operation was found for power weeder having six rotary blades was 4.6 cm [11,23]. Better penetration was obtained for furrow like non-rotary blades generating more draft along with more power requirement [24].…”

Section: Depthsupporting

confidence: 68%

Performance Evaluation of Power Weeder with Different Blade Mechanism in Intra-row Weeding Operation

Khayer,

Patel,

Rahman

et al. 2024

ACRI

View full text Add to dashboard Cite

Aims: Weeding operation is one of the most laborious and time-consuming operation in agriculture. Weeds basically an unwanted plant which competes with crop for light, moisture, and nutrient along with lowering the overall yield. Mechanical weed control methods are preferred among all weeding methods due to many reasons such as timeliness, safety, drudgery and cost effective. Study Area and Duration: The experiment was conducted in the farmer’s field of Abhayapuri, Bongaigaon, Assam in the year 2021 to 2023. Methodology: This study employed a 5.75 hp self-propelled diesel engine with three blade sets—rotary, non-rotary, and a combination of both, designed for weeding in vegetable fields with row spacing up to 75 cm. One-way ANOVA analysis compared group means for statistical significance. Results: Results showed that the field efficiency (90%), fuel consumption (7.7 l/ha), cost of operation (Rs 1217.7 per ha) and plant damage factor (0.01%) was better for rotary blade than non-rotary and combined blade. Whereas effective field capacity (0.07 ha/h), performance index (155.7) and man-hour/ha (14.3) was better for non-rotary blade and the parameters such as depth (4.4 cm) and weeding efficiency (94.2%) was better for combined blade mechanism. From the one-way ANOVA analysis, it showed that blade mechanism showed significant difference on parameters like weeding efficiency, field efficiency, fuel consumption, effective field capacity, cost of operation, man-h/ha and performance index at p<0.05 and non-significant for depth and plant damage factor at P<0.05. Conclusion: Study concluded that for intra-row weeding operation, rotary blade along with non-rotary blade was suitable economically whereas combined blade was suitable for weeding performance only besides high cost.

show abstract

Section: Depthsupporting

confidence: 68%

Performance Evaluation of Power Weeder with Different Blade Mechanism in Intra-row Weeding Operation

Khayer,

Patel,

Rahman

et al. 2024

ACRI

View full text Add to dashboard Cite

show abstract

“…Rotary power weeders consume less draught and perform better in fields. Two, four and six blades per flange of a 25-centimetre-wide portable backpack power weeder were put to the test in a chilli crop [20][21][22][23][24][25][26].…”

Section: Related Workmentioning

confidence: 99%

Machine Learning based Disease and Pest detection in Agricultural Crops

Nelson,

et al. 2024

EAI Endorsed Trans IoT

View full text Add to dashboard Cite

INTRODUCTION: Most Indians rely on agricultural work as their primary means of support, making it an essential part of the country’s economy. Disasters and the expected loss of farmland by 2050 as a result of global population expansion raise concerns about food security in that year and beyond. The Internet of Things (IoT), Big Data and Analytics are all examples of smart agricultural technologies that can help the farmers enhance their operation and make better decisions. OBJECTIVES: In this paper, machine learning based system has been developed for solving the problem of crop disease and pest prediction, focussing on the chilli crop as a case study. METHODS: The performance of the suggested system has been assessed by employing performance metrics like accuracy, Mean Squared Error (MSE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). RESULTS: The experimental results reveals that the proposed method obtained accuracy of 0.90, MSE of 0.37, MAE of 0.15, RMSE of 0.61 CONCLUSION: This model will predict pests and diseases and notify farmers using a combination of the Random Forest Classifier, the Ada Boost Classifier, the K Nearest Neighbour, and Logistic Regression. Random Forest is the most accurate model.

show abstract

“…Performance of the weeder was assessed through performance index (PI) by using the following relation [13] p…”

Section: Performance Index Of Weedermentioning

confidence: 99%

On Farm Performance Evaluation of Back Pack Weeder for Weed Control in Cassava: A Case of Busia County, Kenya

Susan

Wawire

2021

JERR

View full text Add to dashboard Cite

This research work involved performance evaluation of back pack weeder in four representative cassava planted farms in Busia County. The main objective of the research study was to test the performance of the mechanical back pack weeder in cassava crop and comparing it with manual weeding. This was done in four test plots which were sampled in different sub counties based on the condition of small scale farmer accessibility and also a representative of each sub-county. In all the plots cassava was planted using the right agronomic requirements. The choice of the crop was depended on farmers and stakeholders preference to the most profitable and mechanizable crop in the county. This was done using the ranking method in order to achieve the crop with the highest interest in terms of profitability and mechanization need. Machinery evaluation is always very significant as it gives the performance rate of agricultural machinery and quality of operation based on the farm in which they are used. It is for this reason that the back pack weeder was preferred and evaluated against manual weeding for the farmer to understand the use and maintenance as well as its benefits compared to manual weeding using a jembe. The use of a back pack weeder for weeding in cassava as opposed to manual weeding using a jembe proved that it can improve weeding quality and also reduces elapsed time and the costs involved in the weeding operation. The evaluated parameters were weeding efficiency, fuel consumption, operation time, plant damage, effective field capacity and field efficiency. The results show that efficiencies for test plots 1, 2 and 4 were high ranging from 97.1%, 98%, 97% with bit lower fuel consumption of 0.4l/hr and operational cost of 1360kes/ha, 1366kes/ha and 1361kes/ha respectively due to the nature of soils texture which was equally sandy loam. The plant damage for all plots were found to be the same for both machine and manual weeding. The operational cost of manual was equally the same since the same number of casuals were used but the machine was a bit higher for the case of test plot 3 since it consumed a high amount of fuel. The weeding efficiency was depicted as 97.1 %, 98%, 86% and 97% for machine weeding for the four test plots respectively and 78%, 78%, 72% and 77% for hand weeding, since the human labour removes the weeds hence the efficiency of weeding was highest.

show abstract

Performance evaluation of weeder by number of blades per flange in chilli crop

Cited by 5 publications

References 0 publications

Performance Evaluation of Power Weeder with Different Blade Mechanism in Intra-row Weeding Operation

Performance Evaluation of Power Weeder with Different Blade Mechanism in Intra-row Weeding Operation

Machine Learning based Disease and Pest detection in Agricultural Crops

On Farm Performance Evaluation of Back Pack Weeder for Weed Control in Cassava: A Case of Busia County, Kenya

Contact Info

Product

Resources

About