Shreeya Adhikari, S. Sah, Sasmita Gautam, Dikshya Subedi, Shambhu Katel
{"title":"基于叶片颜色图的春稻氮素管理","authors":"Shreeya Adhikari, S. Sah, Sasmita Gautam, Dikshya Subedi, Shambhu Katel","doi":"10.5455/faa.99074","DOIUrl":null,"url":null,"abstract":"A field experiment on LCC-based N management was carried out at Rajapur, Bardiya during the spring season of 2021 to determine the growth and productivity of spring rice varieties. The experiment was laid out in strip plot design with three replications. The treatment consisted of four varieties (Chaite-5, Hardinath-1, Hardinath 1-F1, and Hardinath-3) in horizontal plots and five levels of LCC-based N management practices (Pure LCC, 25% N (basal) + LCC, Recommended dose of fertilizer in three splits, Farmer’s dose, and no nitrogen) in vertical plots. The results showed that Pure LCC-based nitrogen management produced the highest grain yield (6.24 t ha-1) followed by 25% N basal +LCC (5.77 t ha-1). LCC-based treatments produced a significantly higher yield than recommended dose applied in three splits. The higher yield in pure LCC was because of higher yield attributes like effective tillers m-2, higher thousand-grain weight, lower sterility percentage, longer panicle length, and higher panicle weight. Hardinath-3 and Hardinath 1-F1 with pure LCC produced significantly higher yields than other treatment combinations. The spring rice varieties Hardinath 1-F1 and Hardinath-3 were high yielders than Hardinath-1 and Chaite-5. The higher yield of Hardinath-3 was due to higher number of effective tillers m-2, longer panicle length, and higher panicle weight. Similarly, the higher yield of Hardinath1-F1 was mainly due to higher thousand-grain weight and higher number of effective tillers m-2 as compared to other varieties except for Hardinath-3. 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引用次数: 0
摘要
为确定春稻品种的生长和生产力,于2021年春季在巴迪亚省拉贾布尔进行了基于lcc的氮素管理田间试验。试验采用条形小区设计,3个重复。在水平区采用柴特5号、哈迪纳特1号、哈迪纳特1-F1号和哈迪纳特3号4个品种,在垂直区采用5个低碳氮肥管理水平(纯低碳、25%氮(基础)+低碳、三次推荐施量、农民施量和不施氮)。结果表明,以纯LCC为基础的氮肥处理籽粒产量最高(6.24 t ha-1),其次为25%基施+LCC (5.77 t ha-1)。以lcc为基础的治疗产生的产率明显高于三次应用的推荐剂量。纯LCC的高产是由于有效分蘖数m-2高、千粒重高、不育率低、穗长长、穗重高等产量性状的提高。纯LCC处理的hardath 3和hardath 1-F1产量显著高于其他处理组合。春稻品种hardath 1-F1和hardath 3的产量高于hardath 1和chae -5。哈迪纳斯-3的高产是由于有效分蘖数m-2较多、穗长和穗重较长所致。除hardath3外,hardath1 - f1的高产主要是由于其千粒重和有效分蘖数(m-2)高于其他品种。在类似巴地亚气候条件下,纯lcc氮管理的品种hardath 1-F1和hardath 3是高产品种。
Leaf color chart based Nitrogen Management in spring Rice
A field experiment on LCC-based N management was carried out at Rajapur, Bardiya during the spring season of 2021 to determine the growth and productivity of spring rice varieties. The experiment was laid out in strip plot design with three replications. The treatment consisted of four varieties (Chaite-5, Hardinath-1, Hardinath 1-F1, and Hardinath-3) in horizontal plots and five levels of LCC-based N management practices (Pure LCC, 25% N (basal) + LCC, Recommended dose of fertilizer in three splits, Farmer’s dose, and no nitrogen) in vertical plots. The results showed that Pure LCC-based nitrogen management produced the highest grain yield (6.24 t ha-1) followed by 25% N basal +LCC (5.77 t ha-1). LCC-based treatments produced a significantly higher yield than recommended dose applied in three splits. The higher yield in pure LCC was because of higher yield attributes like effective tillers m-2, higher thousand-grain weight, lower sterility percentage, longer panicle length, and higher panicle weight. Hardinath-3 and Hardinath 1-F1 with pure LCC produced significantly higher yields than other treatment combinations. The spring rice varieties Hardinath 1-F1 and Hardinath-3 were high yielders than Hardinath-1 and Chaite-5. The higher yield of Hardinath-3 was due to higher number of effective tillers m-2, longer panicle length, and higher panicle weight. Similarly, the higher yield of Hardinath1-F1 was mainly due to higher thousand-grain weight and higher number of effective tillers m-2 as compared to other varieties except for Hardinath-3. The varieties Hardinath 1-F1 and Hardinath-3 with pure LCC-based N management were high-yielders in Bardiya-like climatic conditions.