Dynamical partition of photosynthates in tillers of rice (Oryza sativa L.) during late growth period and its correlation with feeding value of rice straw at harvest

2011 ◽  
Vol 123 (3) ◽  
pp. 273-280 ◽  
Author(s):  
Chen Fei Dong ◽  
Xin Bao Liu ◽  
Hui Qu ◽  
Yi Xin Shen
Keyword(s):  
Oryza Sativa ◽  
Rice Straw ◽  
Oryza Sativa L ◽  
Growth Period ◽  
Feeding Value ◽  
Late Growth

scholarly journals Preparation of wastelage with poultry droppings and rice straw (Oryza sativa L.) as a cattle feed

2018 ◽  
Vol 4 (3) ◽  
pp. 251-258
Author(s):  
Obydul Islam ◽  
Somaya Akter ◽  
Md Ahidul Islam ◽  
Dewan Kamruzzaman Jamee ◽  
Rokibul Islam Khan
Keyword(s):  
Organic Matter ◽  
Oryza Sativa ◽  
Rice Straw ◽  
Oryza Sativa L ◽  
Fungal Growth ◽  
Metabolizable Energy ◽  
Organic Matter Digestibility ◽  
Ph Level ◽  
Poultry Droppings

The use of poultry droppings as a feed ingredient may not only reduce waste and environmental pollution but also provide inexpensive feed components for ruminants. An experiment was conducted to prepare wastelage in the field laboratory of Animal Science Department, Bangladesh Agricultural University, Mymensingh. Rice straw (Oryza sativa L.) was mixed with 0%, 10%, 20% and 30% caged layer excreta (CLE) and 5% molasses in each treatment on dry matter (DM) basis and ensiled in air tight container under room temperature. After 60 days, ensiled mixture was opened. All the wastelage had desirable smell, light brownish color, soft texture and no fungal growth was found. Results revealed that PH, DM, crude protein (CP), crude fiber (CF), ash, in vitro organic matter digestibility and metabolizable energy were significantly (p<0.05) influenced by different levels of CLE. The highest CP (5.97g/100g DM) was observed in wastelage with 30% CLE (p<0.05) followed by 20% and 10% CLE. The PH level, DM, Ash and CF contents were decreased linearly (p<0.05) from 4.8 to 4.11, 78.00 to 55.63, 25.08 to 17.70 and 22.57 to 14.95%, respectively as the level of CLE increased from 0 to 30%. In all treatments, EE content was not significantly influenced by the different level of CLE. The in vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) also increased significantly (p<0.05) with the increased level of CLE and maximum value (57.51%, and 8.12 MJ/Kg DM, respectively) was obtained in wastelage with 10% CLE, which is statistically identical with 20% CLE. Therefore, it could be speculated that ensiling rice straw with up to 20% CLE improved the feeding value of wastelage.Asian J. Med. Biol. Res. September 2018, 4(3): 251-258

Multiple alleles at Early flowering 1 locus making variation in the basic vegetative growth period in rice (Oryza sativa L.)

2009 ◽  
Vol 119 (2) ◽  
pp. 315-323 ◽  
Author(s):  
Hiroki Saito ◽  
Qingbo Yuan ◽  
Yutaka Okumoto ◽  
Kazuyuki Doi ◽  
Atsushi Yoshimura ◽  
...  
Keyword(s):  
Oryza Sativa ◽  
Vegetative Growth ◽  
Oryza Sativa L ◽  
Growth Period ◽  
Early Flowering ◽  
Multiple Alleles ◽  
Basic Vegetative Growth

QTL Analysis for Traits Associated with Feeding Value of Straw in Rice (Oryza sativa L.)

Rice Science ◽  
2008 ◽  
Vol 15 (3) ◽  
pp. 195-200 ◽  
Author(s):  
Chen-fei DONG ◽  
Qing-sheng CAI ◽  
Cai-lin WANG ◽  
Jiro HARADA ◽  
Keisuke NEMOTO ◽  
...  
Keyword(s):  
Oryza Sativa ◽  
Qtl Analysis ◽  
Oryza Sativa L ◽  
Feeding Value

Effects of gibberellic acid application after anthesis on the feeding value of double-purpose rice (Oryza sativa L.) straw at harvest

2012 ◽  
Vol 131 ◽  
pp. 75-80 ◽  
Author(s):  
Chen Fei Dong ◽  
Hong Ru Gu ◽  
Cheng Long Ding ◽  
Neng Xiang Xu ◽  
NanQing Liu ◽  
...  
Keyword(s):  
Oryza Sativa ◽  
Gibberellic Acid ◽  
Oryza Sativa L ◽  
Feeding Value

scholarly journals Structural Characteristics of the Guaiacyl-Rich Lignins From Rice (Oryza sativa L.) Husks and Straw

2021 ◽  
Vol 12 ◽  
Author(s):  
Mario J. Rosado ◽  
Jorge Rencoret ◽  
Gisela Marques ◽  
Ana Gutiérrez ◽  
José C. del Río
Keyword(s):  
Oryza Sativa ◽  
Rice Straw ◽  
Oryza Sativa L ◽  
Structural Characteristics ◽  
Analytical Techniques ◽  
Gas Chromatography Mass Spectrometry ◽  
Aryl Ether ◽  
Rice Husks ◽  
Alkyl Aryl ◽  
G Ratio

Rice (Oryza sativa L.) is a major cereal crop used for human nutrition worldwide. Harvesting and processing of rice generates huge amounts of lignocellulosic by-products such as rice husks and straw, which present important lignin contents that can be used to produce chemicals and materials. In this work, the structural characteristics of the lignins from rice husks and straw have been studied in detail. For this, whole cell walls of rice husks and straw and their isolated lignin preparations were thoroughly analyzed by an array of analytical techniques, including pyrolysis coupled to gas chromatography-mass spectrometry (Py-GC/MS), nuclear magnetic resonance (NMR), and derivatization followed by reductive cleavage (DFRC). The analyses revealed that both lignins, particularly the lignin from rice husks, were highly enriched in guaiacyl (G) units, and depleted in p-hydroxyphenyl (H) and syringyl (S) units, with H:G:S compositions of 7:81:12 (for rice husks) and 5:71:24 (for rice straw). These compositions were reflected in the relative abundances of the different interunit linkages. Hence, the lignin from rice husks were depleted in β–O–4′ alkyl-aryl ether units (representing 65% of all inter-unit linkages), but presented important amounts of β–5′ (phenylcoumarans, 23%) and other condensed units. On the other hand, the lignin from rice straw presented higher levels of β–O–4′ alkyl-aryl ethers (78%) but lower levels of phenylcoumarans (β–5′, 12%) and other condensed linkages, consistent with a lignin with a slightly higher S/G ratio. In addition, both lignins were partially acylated at the γ-OH of the side-chain (ca. 10–12% acylation degree) with p-coumarates, which overwhelmingly occurred over S-units. Finally, important amounts of the flavone tricin were also found incorporated into these lignins, being particularly abundant in the lignin of rice straw.

scholarly journals Rice (Oryza sativa L.) Growth Modeling Based on Growth Degree Day (GDD) and Artificial Intelligence Algorithms

Agriculture ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 59
Author(s):  
Li-Wei Liu ◽  
Chun-Tang Lu ◽  
Yu-Min Wang ◽  
Kuan-Hui Lin ◽  
Xing-Mao Ma ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Oryza Sativa ◽  
Oryza Sativa L ◽  
Gene Expression Programming ◽  
Model Performance ◽  
Growth Period ◽  
Rice Production ◽  
Growth Prediction ◽  
Rice Growth ◽  
Degree Day

Rice (Oryza sativa L.) growth prediction is key for precise rice production. However, the traditional linear rice growth forecasting model is ineffective under rapidly changing climate conditions. Here we show that growth rate (Gr) can be well-predicted by artificial intelligence (AI)-based artificial neural networks (ANN) and gene-expression programming (GEP), with accumulated air temperatures based on growth degree day (GDD). In total, 10,246 Gr from 95 cultivations were obtained with three cultivars, TK9, TNG71, and KH147, in Central and Southern Taiwan. The model performance was evaluated by the Pearson correlation coefficient (r), root mean square error (RMSE), and relative RMSE (r-RMSE) in the whole growth period (lifecycle), as well as the average and specific key stages (transplanting, 50% initial tillering, panicle initiation, 50% heading, and physiological maturity). The results in lifecycle Gr modeling showed that ANN and GEP models had comparable r (0.9893), but the GEP model had the lowest RMSE (3.83 days) and r-RMSE (7.24%). In stage average and specific key stages, each model has its own best-fit growth period. Overall, GEP model is recommended for rice growth prediction considering the model performance, applicability, and routine farming work. This study may lead to smart rice production due to the enhanced capacity to predict rice growth in the field.

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