Actual field speed of rice combine harvester and its influence on grain loss in Malaysian paddy field

Mokhtor, Shamilah Ahmad; Pebrian, Darius El; Johari, Nor Azi Asminda

doi:10.1016/j.jssas.2020.07.002

Cited by 26 publications

(16 citation statements)

References 2 publications

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“…According to the equations generated, both the harvesters H SR and H DR , had the lowest frequency of pods even without threshing at speeds of 7.78 and 6.84 km h -1 , respectively. The reduced amount of pods without threshing from the axial harvesters showcase a greater efficiency regarding harvesters with a tangential trail system, according to Mokhtor, El Pebrian and Johari (2020).…”

Section: Ciência E Agrotecnologia 45:e031720 2021mentioning

confidence: 99%

Operational performance and energy efficiency of axial harvesters with single and double rotor systems in soybean seed harvest

et al. 2021

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The decision-making capability of the machine to harvest grains must consider a lower fuel consumption with a higher operating velocity allied to a greater performance of the grain cleaning system, along with lower rates of the damage and waste produced. This study aimed at evaluating the operational performance and the energy efficiency of two axial harvesters, having different trail and separation systems in the soybean seed harvest. The experiment was carried out in a completely randomized block design in 500-m bands, consisting of two factors, namely two axial harvesters (single and double rotor) and six target velocities (3, 4, 5, 6, 7, and 8 km h-1). Regarding the operational energy performance, the hourly fuel consumption, operational speed, operational field capacity, fuel consumption per area and mass of the harvested grain, and the handling capacity of the harvest were evaluated. The harvesting performance parameters, such as the percentage losses in the platform and the trail system, broken grains, impurities, and the pods, which did not undergo threshing, were evaluated. The results obtained showed that the single-rotor harvester had a better energy efficiency, while the double-rotor harvester had a better operational performance. The double-rotor harvester was agronomically more efficient.

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Section: Ciência E Agrotecnologia 45:e031720 2021mentioning

confidence: 99%

Operational performance and energy efficiency of axial harvesters with single and double rotor systems in soybean seed harvest

et al. 2021

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“…In the rice post-production phase, paddy harvesting activities include reaping, stacking, handling, threshing, cleaning, and hauling. Harvesting paddy should be performed efficiently as the speed of paddy harvesting showed a linear relationship with grain loss [11]. When rice is harvested, it will contain up to 25% moisture.…”

Section: Phases and Tasks In Paddy Rice Smart Farmingmentioning

confidence: 99%

“…The current practices, which heavily rely on fertilizers and pesticides to increase productivity are not supporting the sustainable rice yields production because these activities are not environmentally friendly farming systems [10]. In addition to that, the timing for rice yields harvesting also influences the production of rice yields as the best timing for paddy harvesting showed a linear relationship with grain loss [11]. As a result, monitoring the growth of paddy is very crucial to sustain rice yields production.…”

mentioning

confidence: 99%

Towards Paddy Rice Smart Farming: A Review on Big Data, Machine Learning, and Rice Production Tasks

et al. 2021

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Big Data (BD), Machine Learning (ML) and Internet of Things (IoT) are expected to have a large impact on Smart Farming and involve the whole supply chain, particularly for rice production. The increasing amount and variety of data captured and obtained by these emerging technologies in IoT offer the rice smart farming strategy new abilities to predict changes and identify opportunities. The quality of data collected from sensors greatly influences the performance of the modelling processes using ML algorithms. These three elements (e.g., BD, ML and IoT) have been used tremendously to improve all areas of rice production processes in agriculture, which transform traditional rice farming practices into a new era of rice smart farming or rice precision agriculture. In this paper, we perform a survey of the latest research on intelligent data processing technology applied in agriculture, particularly in rice production. We describe the data captured and elaborate role of machine learning algorithms in paddy rice smart agriculture, by analyzing the applications of machine learning in various scenarios, smart irrigation for paddy rice, predicting paddy rice yield estimation, monitoring paddy rice growth, monitoring paddy rice disease, assessing quality of paddy rice and paddy rice sample classification. This paper also presents a framework that maps the activities defined in rice smart farming, data used in data modelling and machine learning algorithms used for each activity defined in the production and post-production phases of paddy rice. Based on the proposed mapping framework, our conclusion is that an efficient and effective integration of all these three technologies is very crucial that transform traditional rice cultivation practices into a new perspective of intelligence in rice precision agriculture. Finally, this paper also summarizes all the challenges and technological trends towards the exploitation of multiple sources in the era of big data in agriculture.

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“…Finally, the mechanical cutting frequency and the forward speed of the wheat harvester are determined. Shamilah et al [13] studied the impact of field speed of combine harvester on paddy fields in Malaysia to obtain appropriate field operation speed. Liu [14] and Lu [15] explored the adaptive control system for the forward speed of the crawler combine and put forward a set of adaptive control system model and theory.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Harvesting Speed and Forward Speed of Harvester Based on Adaptive Control System

Wang

Yang

et al. 2022

Journal of Sensors

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The working efficiency of the combine harvester is still very low. It is an important way to realize mechanization to optimize the cutting speed of the harvester and the forward speed of the cutter without increasing economic input. In view of this, the present study briefly summarized the current structure of combine harvester systems. A new type of adaptive control system of combine harvesters was designed from the angle of cutting speed and forward speed of cutter. The sugarcane test base was taken as the test field, and the best matching speed was obtained with the goal of high efficiency of combine harvester and minimum sugarcane damage rate. In the test of cutting speed and forward speed of combine harvester, the optimal cutting speed under different forward speed conditions was recorded. The test results showed that the designed adaptive control system of the combine harvester could control the cutting speed and forward speed of the cutter well. The cutting speed and forward speed adaptive control system can realize the response to the input parameters and meet the design requirements of the harvester. This study can improve the economic benefits of the combine harvester and the quality of the harvested crops.

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Actual field speed of rice combine harvester and its influence on grain loss in Malaysian paddy field

Cited by 26 publications

References 2 publications

Operational performance and energy efficiency of axial harvesters with single and double rotor systems in soybean seed harvest

Operational performance and energy efficiency of axial harvesters with single and double rotor systems in soybean seed harvest

Towards Paddy Rice Smart Farming: A Review on Big Data, Machine Learning, and Rice Production Tasks

Optimal Design of Harvesting Speed and Forward Speed of Harvester Based on Adaptive Control System

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