scholarly journals FEED VALUE OF BLUE PANIC (Panicum antidotale retz.) GRASS AT DIFFERENT GROWTH STAGES AND UNDER VARYING LEVELS OF HUMIC ACID IN SALINE CONDITIONS

2016 ◽  
Vol 21 (2) ◽  
pp. 210
Author(s):  
Ihsanullah DAUR
Keyword(s):  
Humic Acid ◽  
Growth Stages ◽  
Feed Value ◽  
Panicum Antidotale ◽  
Different Growth Stages

scholarly journals Effects of Humic Acid-Irrigation Coupling Techniques on Temperature, Radiation and Rice Growth in Songnen Plain China

2021 ◽  
Author(s):  
Ennan Zheng ◽  
Yinhao Zhu ◽  
Jianyu Hu ◽  
Tianyu Xu ◽  
Zhongxue Zhang
Keyword(s):  
Humic Acid ◽  
Agricultural Soils ◽  
Application Rate ◽  
Growth Stages ◽  
Songnen Plain ◽  
Irrigation Methods ◽  
Fluorescence Characteristics ◽  
Coupling Techniques ◽  
Temperature Radiation ◽  
Different Growth Stages

Abstract In the past decades, the application of organ fertilizer in agricultural soils has attracted wide attention. However, few studies have carefully explored the effects of humic acid on soil and canopy temperature, radiation, the physiological process of plant leaves, especially coupling with the different irrigation methods. To provide a better growing environment for crops and explore the best regulation mode of humic acid and irrigation coupling techniques in the farmland soil environment in the Songnen Plain Heilongjiang Province, through field experiment, we selected rice as the test crop and applied humic acid in the soil with different irrigation methods. The temperature conditions, radiation, agronomic and fluorescence characteristics were monitored by different stages. The effects of different humic acid and irrigation coupling techniques on the temperature and radiation changes during different growth stages were discussed, and the subtle differences of agronomic and fluorescence characteristics in different growth stages of rice plants were compared. The results showed that the humic acid application with different irrigation methods was not beneficial to the maintenance of soil temperature, the differences among the different treatments, were no found significant at 5% probability statistically. However, the differences of radiation interception was obvious, and the best value was CT5 treatment, there were also similarities to plant height. The fluorescence indexes and leaf chlorophyll relative content (SPAD) had the differences with the change of humic acid application rate and irrigation methods. Over all, under the humic acid application rate of 1500 kg·ha-1 with the control irrigation method, could bring the best humic acid and irrigation effects.

scholarly journals The study of humic acid foliar application on physiological and biochemical changes in wheat under irrigation withholding at different growth stages

2016 ◽  
Vol 5 (1) ◽  
pp. 1-7 ◽  
Author(s):  
HR Tohidi
Keyword(s):  
Humic Acid ◽  
Foliar Application ◽  
Stem Elongation ◽  
Research Field ◽  
Growth Stages ◽  
Physiological And Biochemical Characteristics ◽  
Protein Peroxidation ◽  
Physiological And Biochemical ◽  
Different Levels ◽  
Different Growth Stages

In order to study effect of humic acid (HA) foliar application and limited irrigation, on physiological and biochemical characteristics of wheat an experiment was conducted in research field of Varamin, Iran during 2012 growing season. The experimental design was laid out in a randomized complete block with a split plots arrangement of treatments in three replications. Main plots included four different levels of irrigation (complete irrigation, irrigation withholding at stem elongation stage, irrigation withholding at flowering stage and irrigation withholding at seed setting stage) and three different concentration of HA foliar application (0, 150 and 300) was allocated to subplots. The results showed that irrigation withholding conditions in different growth stages significantly decreased seed yield and total chlorophyll content but by contrast increased electrolyte leakage, antioxidant enzymes activity and lipid and protein peroxidation. It appears that HA act in plants via a specific form of stress that is detected by anti-stress defense systems in plants. These HA applied to plants can protect against water stress in degraded soils.International Journal of Natural Sciences (2015), 5(1) 1-7

Cytokinins from terminal buds of Euphoria longana during different growth stages

1997 ◽  
Vol 99 (1) ◽  
pp. 185-189
Author(s):  
Wen-Shaw Chen ◽  
Kuang-Liang Huang ◽  
Hsiao-Ching Yu
Keyword(s):  
Growth Stages ◽  
Terminal Buds ◽  
Different Growth Stages

Effects of Meteorological Factors at Different Growth Stages on Yield Traits of Maize (Zea maysL.) in Heilonggang Basin

2013 ◽  
Vol 39 (5) ◽  
pp. 919 ◽  
Author(s):  
Bo MING ◽  
Jin-Cheng ZHU ◽  
Hong-Bin TAO ◽  
Li-Na XU ◽  
Bu-Qing GUO ◽  
...  
Keyword(s):  
Meteorological Factors ◽  
Growth Stages ◽  
Yield Traits ◽  
Different Growth Stages

scholarly journals Label3DMaize: toolkit for 3D point cloud data annotation of maize shoots

GigaScience ◽  
2021 ◽  
Vol 10 (5) ◽  
Author(s):  
Teng Miao ◽  
Weiliang Wen ◽  
Yinglun Li ◽  
Sheng Wu ◽  
Chao Zhu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Point Cloud ◽  
Training Dataset ◽  
Growth Stages ◽  
3D Point Cloud ◽  
Plant Structure ◽  
Data Annotation ◽  
Cloud Data ◽  
Point Cloud Segmentation ◽  
Different Growth Stages

Abstract Background The 3D point cloud is the most direct and effective data form for studying plant structure and morphology. In point cloud studies, the point cloud segmentation of individual plants to organs directly determines the accuracy of organ-level phenotype estimation and the reliability of the 3D plant reconstruction. However, highly accurate, automatic, and robust point cloud segmentation approaches for plants are unavailable. Thus, the high-throughput segmentation of many shoots is challenging. Although deep learning can feasibly solve this issue, software tools for 3D point cloud annotation to construct the training dataset are lacking. Results We propose a top-to-down point cloud segmentation algorithm using optimal transportation distance for maize shoots. We apply our point cloud annotation toolkit for maize shoots, Label3DMaize, to achieve semi-automatic point cloud segmentation and annotation of maize shoots at different growth stages, through a series of operations, including stem segmentation, coarse segmentation, fine segmentation, and sample-based segmentation. The toolkit takes ∼4–10 minutes to segment a maize shoot and consumes 10–20% of the total time if only coarse segmentation is required. Fine segmentation is more detailed than coarse segmentation, especially at the organ connection regions. The accuracy of coarse segmentation can reach 97.2% that of fine segmentation. Conclusion Label3DMaize integrates point cloud segmentation algorithms and manual interactive operations, realizing semi-automatic point cloud segmentation of maize shoots at different growth stages. The toolkit provides a practical data annotation tool for further online segmentation research based on deep learning and is expected to promote automatic point cloud processing of various plants.

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