2019
DOI: 10.20546/ijcmas.2019.801.001
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Physiological Growth Parameters of Rabi Rice (Oryza sativa L.) under Alternate Wetting and Drying Irrigation with Varied Nitrogen Levels

Abstract: A field experiment was conducted during rabi 2016-17 and 2017-18 at Agricultural Research Institute Main Farm, Rajendranagar, Hyderabad, on a clay loam soil to study the effect of alternate wetting and drying irrigation on rabi rice under varied nitrogen levels. The experiment consisted of three irrigation regimes (recommended submergence of 2 to 5 cm water level as per crop growth stage, AWD irrigation of 5 cm when water level drops to 3cm in water tube, AWD irrigation of 5cm when water level drops to 5 cm in… Show more

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Cited by 7 publications
(4 citation statements)
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“…Nutrients and growth enhancers plays a key role in chlorophyll synthesis and helps in transfer of solar energy through photosynthesis in leaves. Thus the application of nutrients influences the leaf soluble protein content which leads to enhancement of leaf area in rice [19]. These results are in line with the results reported by Pillai et al [20] and Goutam et al [21].…”
Section: Leaf Areasupporting
confidence: 90%
“…Nutrients and growth enhancers plays a key role in chlorophyll synthesis and helps in transfer of solar energy through photosynthesis in leaves. Thus the application of nutrients influences the leaf soluble protein content which leads to enhancement of leaf area in rice [19]. These results are in line with the results reported by Pillai et al [20] and Goutam et al [21].…”
Section: Leaf Areasupporting
confidence: 90%
“…Among the herbicides, the value of LAI under treatment with bispyribac sodium at 25 g/ha was observed to be significantly higher (3.60) and at par with the plot treated with fenoxaprop-p-ethyl + penoxsulam at 60+26.7 g/ha and cyhalofop + penoxsulam at 135+26.7 g/ha as compared to other treatments. The weed-free environment provides more chance for leaves to expand and cover the area by their canopy in an appreciable manner (Sridhar et al, 2019).…”
Section: Growth Parametersmentioning
confidence: 99%
“…The regression for SPSS model is Y = 15.266 + (0.292 x Z21 of prediction year) + (0.066 x time) Here, Z21 is the sum product of minimum temperature. The yield obtained in treatment 9 with NDR-359 + Vermicompost (5 t/ha) + Panchagavya 3% (5.6 t/ha) showed 44.62% increase over the predicted yield through SPSS model (2.88 t/ha) [19][20][21][22][23][24][25][26][27][28].…”
Section: Yield Validation Using Spss Modelmentioning
confidence: 99%