scholarly journals An approach for the symbolization of colors in rice plant and its adoption for the classification of rice varieties

1962 ◽  
Vol 12 (4) ◽  
pp. 221-225
Author(s):  
Hiroshi Ito ◽  
Tomoya Akihama
Keyword(s):  
Rice Plant ◽  
Rice Varieties

scholarly journals Feature Based Qualitative Classification of Rice Varieties: A Review

2020 ◽  
Vol 64 (02) ◽  
pp. 305-312
Author(s):  
Komal ◽  
Ganesh Kumar Sethi ◽  
Rajesh Kumar Bawa
Keyword(s):  
Rice Varieties ◽  
Qualitative Classification ◽  
Feature Based

scholarly journals SPECTRAL CHARACTERISTIZATION OF RICE FIELD USING MULTITEMPORAL LANDSAT ETM+ DATA

2010 ◽  
Vol 2 (-) ◽  
Author(s):  
I WAYAN NUARSA ◽  
SUSUMU KANNO ◽  
YASUHIRO SUGIMORI ◽  
FUMIHIKO NlSHIO
Keyword(s):  
Spectral Characteristic ◽  
Rice Plant ◽  
Rice Field ◽  
Linear Regression Analysis ◽  
Growth Period ◽  
Blue Band ◽  
Multi Temporal ◽  
Study Characteristics ◽  
Differentiation Period

The preliminary study using Landsat ETM+ to estimate the rice production in Regency of Tabanan, Bali Province was conducted. The objectives of this study were to know spectral characteristic of rice plant in three importance growth periods of rice, and to develop a model to identify the distribution of rice. Landsat ETM+ in two acquisition dates (March 21st, 2003 and May 24*, 2003) were used in this study. Characteristics of rice were analyzed using radiance value of Landsat ETM+ obtained from converting digital number of Landsat data. Multi-variable linear regression analysis was developed to classify the rice in its growth period. The result showed that the rice plant has different reflectance in seedling-development period, ear differentiation period and maturation period. It is expressed by the radiance value of Landsat ETM+. However, spectral characteristic of rice in each band of Landsat ETM+ is similar to the green vegetations in general, except in blue band (Bl). Based on statistical analysis, the classification of rice in each its growth period can be classified. Key words: Rice field, Landsat ETM+, Spectral Characteristic, Multi-temporal.

scholarly journals Pemantauan Fase Pertumbuhan Tanaman Padi Menggunakan Citra Radarsat-2 Quad Polarimetrik

2021 ◽  
Vol 5 (1) ◽  
pp. 1-14
Author(s):  
Rian Nurtyawan ◽  
Gerryn Maulannisaa
Keyword(s):  
Rice Plant ◽  
Alpha Angle ◽  
Surface Scattering ◽  
Growth Phases ◽  
Phase Zone ◽  
Volume Scattering ◽  
Initiation Phase ◽  
Remote Sensing Technology ◽  
Sensing Technology

ABSTRAKIndramayu merupakan salah satu lumbung padi Indonesia yang ada di wilayah Jawa Barat dimana Badan Pusat Statistik mencatat pada tahun 2014, Indramayu menghasilkan padi sebesar 1.361.374 ton. Untuk memantau produksi padi, sangat diperlukan pemantauan fase pertumbuhan tanaman padi, salah satu metodenya dengan teknologi penginderaan jauh sistem RADAR menggunakan citra RADARSAT-2 quad polarimetrik. Penelitian ini bertujuan untuk mengklasifikasi daerah fase pertumbuhan tanaman padi menggunakan metode Cloude Pottier H/A/α (entropi/anisotropi/sudut alfa) dan mengevaluasi metode tersebut dalam klasifikasi fase pertumbuhan tanaman padi. Hasil dari penelitian ini yaitu peta klasifikasi fase pertumbuhan tanaman padi dimana dari keseluruhan akuisisi citra, luas lahan tertinggi adalah fase germination/laut yang berjumlah 2.368.242 m2 (22 September 2014). Hasil klasifikasi ini disesuaikan dengan bidang H-α classification plane untuk mengetahui pada zona mana yang memiliki hamburan paling dominan. Hasil pada 18 Juni 2014 dan 5 Agustus 2014 menunjukkan zona 7 (fase panicle initiation/inisiasi malai), zona 8 (fase milk stage/gabah matang susu), dan zona 9 (fase germination/perkecambahan benih atau fase seeding/pertunasan) menjadi zona yang dominan dimana ketiga mekanisme memiliki arti double-bounce scattering (Z7), volume scattering (Z8), dan surface scattering (Z9) sedangkan pada 22 September 2014 dan 16 Oktober 2014 hamburan yang paling dominan terdapat pada Z8 (fase milk stage/gabah matang susu) dengan mekanisme volume scattering dan Z9 (fase germination/perkecambahan benih atau fase seeding/pertunasan) dengan mekanisme surface scattering.Kata kunci: Pertumbuhan Padi, Klasifikasi, RADARSAT-2, H/A/α ABSTRACTIndramayu is one of Indonesia's granary in West Java where Statistic Data Center noted that in 2014 Indramayu produced 1.361.374 tons of rice. It’s necessary to monitor growth phase of rice plant for monitoring rice production, one of the method is remote sensing technology is the RADAR system with RADARSAT-2 image quad-polarimetric. This study aims to classify the phase of growth of rice plants using the Cloude Pottier H / A / α method (entropy / anisotropy / alpha angle) and evaluate these methods in classification of rice plant growth phases. The results of this study are the classification map of the rice plant phase where from the overall image acquisition, the highest land area is the germination / sea phase, which amounts to 2,368,242 m2 (22 September 2014). The classification results are adjusted with the H-α classification plane to find out which zone has the most dominant scattering. The result on 18 June 2014 and 5 August 2014 showed zone 7 (panicle initiation phase), zone 8 (milk stage phase), and zone 9 (germination/seeding) to be the dominant zone where the three mechanisms mean double-bounce scattering (Z7), volume scattering (Z8), and surface scattering (Z9) while on 22 September 2014 and 16 October 2014 the most dominant scattering is in Z8 (milk stage phase) with volume scattering mechanism and Z9 (germination/seeding phase) with surface scattering mechanismKeywords: Rice Growth , Classification, RADARSAT-2, H/A/α.

scholarly journals Determination of minimum number of random SNP for accurate population classification in rice (Oryza sativa L.)

2020 ◽  
Author(s):  
Shan Wang ◽  
Junhua Ye ◽  
Qun Xu ◽  
Xin Xu ◽  
Yingying Yang ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Structure Analysis ◽  
Sampling Method ◽  
Cross Validation ◽  
Rice Varieties ◽  
Germplasm Collections ◽  
Population Structure Analysis ◽  
Cross Validation Error ◽  
Minimum Number

Abstract Background: Classification of germplasm collections is of great importance for both the conservation and utilization of genetic resources. Thus, it is necessary to estimate and classify rice varieties in order to utilize these germplasms more efficiently for rice breeding. However, molecular classification of large germplasm collections can be costly and labor-intensive. Development of an informative panel of a few markers would allow for rapid and cost-effective assignment of crops to genetic sub-populations.Results: Here, the minimum number of random SNP for rice classification (MNRSRC) was studied using a panel of 51 rice varieties belonging to different sub-groups. Through the genetic structure analysis, the rice panel can be obviously divided into five subgroups. The estimation of the MNRSRC was performed using SNP random sampling method based on genetic diversity and population structure analysis. In the genetic diversity analysis, statistical analysis of the coefficient of variation (CV) was performed for MNRSRC estimation, and we found that CV variation tended to plateau when the number of SNP was around 200, which was verified by the both cross-validation error of K value and correlation analysis of genetic distance. When the number of SNPs was greater than 200, the distribution of cross-validation error value tended to be similar, and correlation coefficients, almost greater than 0.95, exhibited small range of variation. In addition, we found that MNRSRC might not be affected by the number of varieties and the type of varieties.Conclusion: The estimation of the MNRSRC was performed using SNP random sampling method based on genetic diversity and population structure analysis. The results demonstrated that at least about 200 random filtered SNP loci were required for classification in a rice panel. In addition, we also found that MNRSRC might not be affected by the number of varieties and the type of varieties. The study on MNRSRC in this study can provide a reference and theoretical basis for classification of different types of rice panels.

scholarly journals APPLICATION OF TRAP BARRIER SYSTEM COMBINED WITH CAGE TRAP FOR CONTROLLING RATS IN RICE FIELD

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Hastin Wulan Sekarweni ◽  
Yulia Pujiastuti ◽  
Siti Herlinda
Keyword(s):  
Rice Plant ◽  
Rice Field ◽  
Rice Yield ◽  
Research Area ◽  
Yield Reduction ◽  
Rice Varieties ◽  
Rice Plants ◽  
Number Of Males

Rice-field rat is a main pest of rice. Yield reduction caused by rat is quite high, because rats attack rice plant at all stages. One of the efforts applied to control rats is by using Trap Barrier System combined with cage trap. The objective of this research was to identify species of rat attacking rice plants and investigate the presence of  rat by their footprints. The experiment was conducted in Jalur 6  Village Sumber Mulya, Sub-district  Muara Telang,  District Banyuasin, South  Sumatra. One hectare of farmer’s rice field, divided into 3 sub-plot. Each sub-plot was planted with variety paddy of Inpari 22 (sub-plot A), Inpari 33 (sub-plot B), and Inpari 43 (sub-plot C). The number of cage traps was 6 traps per sub-plot. Observations were made 7 times, with an interval of 10 days. Results showed species of trapped rats in the research area was Rattus argentiventer, in which number of males was higher than females. Morphologically, the size of males were bigger than female. Number of footprints did not reperesentative the number of trapped rats. Inpari 43 variety was more preferred by rats because damage intensity was the highest than other two rice varieties.

Sign in / Sign up

Export Citation Format

Share Document