scholarly journals Regularity in Variation of Leaf Color and Nitrogen Distribution in Half-Leaf Blades by Leaf Position on the Stems of Rice Plants. II. Uneven translocation of nitrogen between outside and inside half-leaves.

1996 ◽  
Vol 65 (2) ◽  
pp. 229-237
Author(s):  
Hironori MIMOTO ◽  
Kiyoyuki IMAI ◽  
Kyoko HARADA ◽  
Hiroyuki DAIMON ◽  
Masamichi OHE
PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0124071 ◽  
Author(s):  
Chang-Kug Kim ◽  
Young-Joo Seol ◽  
Younhee Shin ◽  
Hye-Min Lim ◽  
Gang-Seob Lee ◽  
...  

2017 ◽  
Vol 7 ◽  
Author(s):  
Xia Zhao ◽  
Tingting Chen ◽  
Baohua Feng ◽  
Caixia Zhang ◽  
Shaobing Peng ◽  
...  

2020 ◽  
Vol 173 ◽  
pp. 105431 ◽  
Author(s):  
Ming Tao ◽  
Xu Ma ◽  
Xunan Huang ◽  
Chuang Liu ◽  
Ruoling Deng ◽  
...  
Keyword(s):  

Driven by the opportunity that digital devices and robust information are readily available, the development and application of new techniques and tools in agriculture are challenging and rewarding processes. This includes techniques learned that is based on traditional methods, practices, experiences, environmental patterns and human capability. The most sought technique comes from human intelligence that is dynamic, adaptive and robust. Nitrogen deficiency in rice plants can be determined via the color of the leaves. It is dependent on the depth of the green pigment in the color spectrum present in the leaves. Based on these characteristics, the application of computational artificial intelligence and machine vision can be adopted to create assistive technologies for agriculture. In this paper, a mobile application is developed and implemented that can be used to assist rice farmers determine nitrogen deficiency, through the leaf color in rice plants. The application can be used alternatively or together with the traditional protocol of nitrogen fertilizer management. It is mobile, simple and it also addresses some drawbacks of the human eye to distinguish color depths brought about by other factors, like sunlight, shading, humidity, temperature, etc. It utilizes image processing techniques to digitally captured images represented in numerically transformed Red, Green, and Blue color formats. The digital images are then normalized to remove the effects of illumination and then compared using the image/pixel subtraction technique with the base color images converted and extracted from the leaf color chart standard. Eventually, the application determines nitrogen deficiency and suggests the concentration and volume of fertilizer to be applied to the rice plants. Accuracy of the technique is determined by computing the Z statistic score.


1997 ◽  
Vol 101 (4) ◽  
pp. 764-769 ◽  
Author(s):  
Heike Stoermer ◽  
Bettina Seith ◽  
Ulrike Hanemann ◽  
Eckhard George ◽  
Heinz Rennenberg

1995 ◽  
Vol 93 (4) ◽  
pp. 617-623 ◽  
Author(s):  
Shu-Chen Grace Chen ◽  
Sang-Pin Wu ◽  
Pang-Kuo Lo ◽  
Dir-Pu Mon ◽  
Long-Fang Oliver Chen
Keyword(s):  

1981 ◽  
Vol 6 (3) ◽  
pp. 347-349 ◽  
Author(s):  
Takashi YUMITA ◽  
Akinori SHOJI ◽  
Izuru YAMAMOTO
Keyword(s):  

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