EFFECT OF LAND PREPARATION, WATER MANAGEMENT PRACTICES, AND PLANTING OPERATION ON PLANTING QUALITY IN RICE PRODUCTION

  • Mairghany M
  • Elsoragaby S
  • Adam N
  • et al.
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Abstract

This study was conducted at Sungai Burong Tanjung Karang Kuala Selangor, Malaysia to investigate the effects of planting methods and techniques on planting quality. The problem is that the farmers do not follow Rice Check quality points in land preparations for flooding, drainage, and water depth which affects the planting quality (planting density, spacing, and planting losses). The results showed that following standardized practices has a positive effect on planting quality. Soil penetration resistance and soil bulk density decrease with the increase of the field flooding period and increase with the sedimentation period increase. Soil penetration resistance and bulk density have a negative effect on planting losses. The working speed of the transplanting machine was affected by the field condition SPR, Db, and WC affect the transplanting speed which affects the planting quality (planting density, spacing, and planting losses). The flooding period has a positive effect on planting losses, while the sedimentation period has a negative effect. Floating hills and buried hills decrease with the increase of flooding periods, and water depth, and with the decrease of the sedimentation soil penetration resistance, and soil bulk density. Bulk density and soil penetration resistance have a positive effect on planting density and spacing as they decrease, planting density and spacing decreases, and vice versa. The flooding period has a negative effect on planting density and spacing, while the sedimentation period has a positive effect. About 50.5% of the farmers used the right required amount of water for irrigation, and also the right time for irrigation.

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APA

Mairghany, M., Elsoragaby, S., Adam, N. M., & Yahya, A. (2022). EFFECT OF LAND PREPARATION, WATER MANAGEMENT PRACTICES, AND PLANTING OPERATION ON PLANTING QUALITY IN RICE PRODUCTION. Big Data in Water Resources Engineering (BDWRE), 3(1), 21–34. https://doi.org/10.26480/bdwre.01.2022.21.34

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