Abstract
Hyper-spectral remote sensing is now a frontier of the remote sensing technology, which can monitoring chlorophyll content rapidly and nondestructive. In this study, four nitrogen forms were set up：ammonium sulfate (ammonium nitrogen) B1, potassium nitrate (nitrate nitrogen) B2, urea (amide nitrogen) B3, and formaldehyde urea (slow effect nitrogen fertilizer) B4. The chlorophyll content of B4 treated with different nitrogen forms was significantly different. Spectral parameters also show good correlation. The chlorophyll content estimation model constructed with the spectral parameters DVI(755,690) and DVI(810,690) has a good fitting degree, and the linear model R2 has reached a significant level, respectively. Rice treated with traditional urea had a lower growth rate than the other three types of nitrogen, the slow effect nitrogen fertilizer and ammonium nitrogen were suggested to improve nitrogen utilization efficiency and eventually reach the goal of high yield.
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Claims 7
Claim · model-written summary
Chlorophyll content differed significantly among nitrogen-form treatments.
- Taxon
- rice
Oryza sativat0 - Treatment
- different nitrogen formse0
- Outcome
- chlorophyll contente0
Not reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The chlorophyll content of B4 treated with different nitrogen forms was significantly different.”
t0“rice”
Claim · model-written summary
Spectral parameters correlated with chlorophyll content.
- Taxon
- riceOryza sativat0
- Outcome
- chlorophyll contente1
- Qualifier
- good correlatione0
- Comparator
- Spectral parameterse0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Spectral parameters also show good correlation.”
e1“The chlorophyll content of B4 treated with different nitrogen forms”
t0“rice”
Claim · model-written summary
The DVI(755,690) and DVI(810,690) model had good fit for rice chlorophyll content estimation.
- Taxon
- riceOryza sativat0
- Outcome
- good fitting degreee0
- Comparator
- DVI(755,690) and DVI(810,690)e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The chlorophyll content estimation model constructed with the spectral parameters DVI(755,690) and DVI(810,690) has a good fitting degree”
t0“rice”
Claim · model-written summary
The linear model R2 reached significance.
- Taxon
- riceOryza sativat0
- Outcome
- significant levele0
- Comparator
- linear model R2e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the linear model R2 has reached a significant level”
t0“rice”
Claim · model-written summary
Rice treated with traditional urea grew more slowly than rice receiving the other three nitrogen types.
- Taxon
- RiceOryza sativae0
- Treatment
- traditional ureae0
- Outcome
- growth ratee0
- Direction
- lowere0
- Comparator
- the other three types of nitrogene0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Rice treated with traditional urea had a lower growth rate than the other three types of nitrogen”
Claim · model-written summary
Authors suggested slow effect nitrogen fertilizer to improve nitrogen use and yield.
- Taxon
- riceOryza sativat0
- Outcome
- slow effect nitrogen fertilizere0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the slow effect nitrogen fertilizer and ammonium nitrogen were suggested to improve nitrogen utilization efficiency and eventually reach the goal of high yield”
t0“rice”
Claim · model-written summary
Authors suggested ammonium nitrogen to improve nitrogen use and yield.
- Taxon
- riceOryza sativat0
- Outcome
- ammonium nitrogene0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the slow effect nitrogen fertilizer and ammonium nitrogen were suggested to improve nitrogen utilization efficiency and eventually reach the goal of high yield”
t0“rice”
The same questions in other papers
nitrogen · growth · Oryza sativa (rice)Positive and negative results
108 papers in the same direction as this paper · 402 in the opposite direction
- positive
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