Physicochemical Changes and Diastatic Activity Associated with Germination of ‘Boromo’, a Paddy Rice Variety from Western Nigeria

2014 ◽  
Vol 39 (2) ◽  
pp. 116-122 ◽  
Author(s):  
A.O. Olugbile ◽  
A.O. Obadina ◽  
A.O. Atanda ◽  
O.B. Omemu ◽  
S.O.A. Olatope
Keyword(s):  
Rice Variety ◽  
Paddy Rice ◽  
Physicochemical Changes ◽  
Diastatic Activity

scholarly journals Analysing the effect of paddy rice variety on fluorescence characteristics for nitrogen application monitoring

2018 ◽  
Vol 5 (6) ◽  
pp. 180485 ◽  
Author(s):  
Chaoyong Shen ◽  
Zhongke Feng ◽  
Daoqin Zhou
Keyword(s):  
Rice Variety ◽  
Paddy Rice ◽  
N Fertilizer ◽  
Experimental Results ◽  
Rice Varieties ◽  
Growth Status ◽  
Fluorescence Characteristics ◽  
Key Factor ◽  
Leaf N Content ◽  
The Relationship

Paddy rice is one of the most important cereal crops worldwide, so it is very important to accurately monitor its growth status and photosynthetic efficiency. The nitrogen (N) level is a key factor closely related to crop growth. In this study, laser-induced fluorescence (LIF) technology combined with multi-variate analysis was applied to investigate the effect of paddy rice variety on N fertilizer level monitoring. Principal components analysis was conducted to extract the variables of the main fluorescence characteristics to identify N levels. Experimental results demonstrated that no nitrogen fertilizer can be completely identified for each paddy rice variety. In addition, other N levels can also be well classified based on the fluorescence characteristics. The relationship between the fluorescence ratio (F735/F685 : F735, and F685 denote the fluorescence intensity at 735 nm, and 685 nm, respectively) and leaf N content of different paddy rice varieties is also discussed. Experimental results revealed that LIF technology is an effective method of monitoring the N fertilizer and leaf biochemical components of paddy rice.

scholarly journals A New Paddy Rice Variety "Aya" with Good Eating Quality Due to Low Amylose Content Developed by Anther Culture Breeding.

1993 ◽  
Vol 43 (1) ◽  
pp. 155-163 ◽  
Author(s):  
Yasufumi KUNIHIRO ◽  
Yasunari EBE ◽  
Nobo SHINBASHI ◽  
Harumi KIKUCHI ◽  
Hisashi TANNO ◽  
...  
Keyword(s):  
Anther Culture ◽  
Amylose Content ◽  
Rice Variety ◽  
Paddy Rice ◽  
Eating Quality

Effects of Water Circulation and Quantity on GABA Content and some Properties of Germinated Brown Rice

2014 ◽  
Vol 931-932 ◽  
pp. 1529-1533
Author(s):  
Sirorat Pilawut ◽  
Winit Chinsuwan
Keyword(s):  
Nutritional Quality ◽  
Rice Variety ◽  
Brown Rice ◽  
Value Added ◽  
Paddy Rice ◽  
Rice Grain ◽  
Rice Seed ◽  
Stagnant Water ◽  
Germinated Brown Rice ◽  
Gaba Content

At germination stage, paddy rice seed produces phytochemicals that are essential for human health. One way of value added concept for rice production is to germinate paddy rice grain to increase nutritional quality before selling. Typical method of soaking paddy grain in stagnant water for 1 to 2 days has been employed for germination. Water flowing through rice grains instead of stagnant may increase its nutritional quality. The objective of this study was to compare 2 methods of grain watering, i.e. soaking in stagnant water and circulating water through grains, on gamma aminobutyric acid (GABA) content and some other properties. The appropriate proportion of water used was also to be evaluated. The Khoa Dok Mali 105 rice variety was chosen for germination tests. The soaking and circulation methods were compared at 8 levels of water quantity i.e. 3, 4, 5, 6, 7, 8, 9 and 10 times of paddy rice by weight. The results showed GABA content of paddy rice under circulation method was higher for all water quantities. The higher the amount of water, the higher the GABA content in both watering methods.

scholarly journals Development of Paddy Rice Seed Classification Process using Machine Learning Techniques for Automatic Grading Machine

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Kantip Kiratiratanapruk ◽  
Pitchayagan Temniranrat ◽  
Wasin Sinthupinyo ◽  
Panintorn Prempree ◽  
Kosom Chaitavon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Machine Vision ◽  
Rice Variety ◽  
Screening Method ◽  
Paddy Rice ◽  
Machine Learning Techniques ◽  
Rice Seed ◽  
Rice Varieties ◽  
Learning Techniques

To increase productivity in agricultural production, speed, and accuracy is the key requirement for long-term economic growth, competitiveness, and sustainability. Traditional manual paddy rice seed classification operations are costly and unreliable because human decisions in identifying objects and issues are inconsistent, subjective, and slow. Machine vision technology provides an alternative for automated processes, which are nondestructive, cost-effective, fast, and accurate techniques. In this work, we presented a study that utilized machine vision technology to classify 14 Oryza sativa rice varieties. Each cultivar used over 3,500 seed samples, a total of close to 50,000 seeds. There were three main processes, including preprocessing, feature extraction, and rice variety classification. We started the first process using a seed orientation method that aligned the seed bodies in the same direction. Next, a quality screening method was applied to detect unusual physical seed samples. Their physical information including shape, color, and texture properties was extracted to be data representations for the classification. Four methods (LR, LDA, k-NN, and SVM) of statistical machine learning techniques and five pretrained models (VGG16, VGG19, Xception, InceptionV3, and InceptionResNetV2) on deep learning techniques were applied for the classification performance comparison. In our study, the rice dataset were classified in both subgroups and collective groups for studying ambiguous relationships among them. The best accuracy was obtained from the SVM method at 90.61%, 82.71%, and 83.9% in subgroups 1 and 2 and the collective group, respectively, while the best accuracy on the deep learning techniques was at 95.15% from InceptionResNetV2 models. In addition, we showed an improvement in the overall performance of the system in terms of data qualities involving seed orientation and quality screening. Our study demonstrated a practical design of rice classification using machine vision technology.

A Study On Agricultural Marketing Practices And Constraints With Special Reference To Paddy / Rice

2011 ◽  
Vol 1 (5) ◽  
pp. 153-156
Author(s):  
CM Maran CM Maran ◽  
◽  
Dr Raja Pranmalai
Keyword(s):  
Special Reference ◽  
Paddy Rice ◽  
Agricultural Marketing

Varietal differences of juvenile phase duration and photoperiodic sensitivity in paddy rice.

1989 ◽  
Vol 58 (4) ◽  
pp. 628-634 ◽  
Author(s):  
Hironori MIMOTO ◽  
Masanori YANASE ◽  
Hiroyoshi CHUJO
Keyword(s):  
Paddy Rice ◽  
Phase Duration ◽  
Varietal Differences ◽  
Photoperiodic Sensitivity ◽  
Juvenile Phase

Lowland Rice Yield as Affected by Straw Incorporation and Inorganic Fertilizer Over Cropping Seasons in Fluvisol

2014 ◽  
Vol 3 (1) ◽  
pp. 129-141
Author(s):  
Brahima Koné ◽  
Zadi Florent ◽  
Gala bi Trazié Jeremie ◽  
Akassimadou Edja Fulgence ◽  
Konan Kouamé Firmin ◽  
...  
Keyword(s):  
Grain Yield ◽  
Rice Variety ◽  
Mineral Fertilizer ◽  
Lowland Rice ◽  
Inorganic Fertilizer ◽  
Cropping Season ◽  
Significant Difference ◽  
Straw Incorporation ◽  
Cropping Seasons ◽  
Fertilizer Effect

Grain yield stabilization of lowland rice over cropping seasons was explored using different compositions of inorganic fertilizers (NPK, NPKCa, NPKMg, NPKZn, NPKCaMg, NPKCaZn and NPKCaMgZn) and straw incorporation (3, 6, 9, 12 and 15 tha-1 ). No fertilizer and no straw amended plot was the control in a split-plot design with three replications laid in a Fluvisol of Guinea savanna in Centre Cote d’Ivoire. Three weeks old nursery rice variety NERICA L19 was transplanted. No significant difference of grain yield was observed between the different treatments excluding the highest yields recorded for treatments NPKMg (5.09 tha-1 ), NPKZn (5.15 tha-1 ) and NPKCaéMg (5.31 tha-1 ) compared with 12 (3.95 tha1 ) and 15 tha-1 (4.14 tha-1 ) as straw rates respectively. Grain yield declining trend was more pronounced for mineral fertilizer treatments showing twice greater depressive effect of cropping cycle compared with the straw especially, for treatments characterized by highest grain yield in the first cropping season and similar grain yields were recorded for both sources of nutrient in the third cropping cycle. Of slowness of nutrients releasing by straw, highest grain yield was expected for this soil amender within a longer period of cultivation whereas, unbalance soil micronutrients should be relevant to studious declining yield under inorganic fertilizer effect. Nevertheless, the straw rate of 12 tha-1 supplying 0.58% of NPK as mineral fertilizer equivalent can be recommended for sustaining lowland rice production in the studied agro-ecosystems unless for three cropping seasons.

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