Abstract
Real-time nitrogen (N) management tools like GreenSeeker™ (GS™), SPAD meters, and leaf colour chart (LCC) predict crop N requirements using leaf reflectance and greenness. However, the high cost of GS™ and SPAD meters restricts their adoption by farmers, while LCC provides only qualitative guidance and depends on subjective colour perception. Digital imaging-based measurement of leaf greenness using RGB values converted to Hue-Saturation-Brightness (HSB) for calculating the Dark Green Colour Index (DGCI) offers a cost-effective alternative for assessing crop N status. In this study, we developed and validated a DGCI-based Android application, Pusa N Doctor, for precision N prescription. Data on DGCI, NDVI, SPAD, LCC, and leaf nitrogen concentration (N%) were collected at 10-day intervals from 25 to 65 days after sowing during 2020-2022. DGCI at 35 and 45 DAS exhibited the strongest correlation with N%, followed by NDVI. While N% served as the absolute indicator of leaf N status, DGCI, NDVI, SPAD, and LCC acted as relative indicators. Calibration of N% against relative measures and DGCI against NDVI, SPAD, and LCC showed DGCI to be the most accurate predictor of N% (R² = 0.69; MAPE = 16.96 %) and NDVI (R² = 0.85; MAPE = 8.76 %). Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splits reduced N use by 18.6 % and improved nitrogen use efficiency indicators by 20-23 % compared to the recommended dose, with comparable yields and 15 % lower N losses. The app provides a scalable, farmer-friendly, and environmentally sustainable solution aligned with SDG 12 and SDG 13.
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Claims 7
Claim · model-written summary
DGCI was the most accurate predictor of leaf N% among the tested indicators (R² = 0.69).
- Outcome
- most accurate predictor of N%e1
- Value
- R² = 0.69e1
- Qualifier
- MAPE = 16.96 %e1
- Comparator
- NDVI, SPAD, and LCCe1
Zea maysOrganisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“maize production”
e1“Calibration of N% against relative measures and DGCI against NDVI, SPAD, and LCC showed DGCI to be the most accurate predictor of N% (R² = 0.69; MAPE = 16.96 %) and NDVI (R² = 0.85; MAPE = 8.76 %)”
Claim · model-written summary
DGCI was the most accurate predictor of NDVI (R² = 0.85).
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“maize production”
e1“Calibration of N% against relative measures and DGCI against NDVI, SPAD, and LCC showed DGCI to be the most accurate predictor of N% (R² = 0.69; MAPE = 16.96 %) and NDVI (R² = 0.85; MAPE = 8.76 %)”
Claim · model-written summary
DGCI at 35 and 45 DAS showed the strongest correlation with N%, followed by NDVI.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“maize production”
e2“DGCI at 35 and 45 DAS exhibited the strongest correlation with N%, followed by NDVI”
Claim · model-written summary
Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splits reduced N use by 18.6 % relative to the recommended dose.
- Treatment
- Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splitse3
- Outcome
- N usee3
- Direction
- reducede3
- Value
- 18.6 %e3
- Comparator
- the recommended dosee3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“maize production”
e3“Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splits reduced N use by 18.6 % and improved nitrogen use efficiency indicators by 20-23 % compared to the recommended dose, with comparable yields and 15 % lower N losses”
Claim · model-written summary
The same DGCI-guided N regime improved nitrogen use efficiency indicators by 20-23 % relative to the recommended dose.
- Treatment
- Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splitse3
- Outcome
- nitrogen use efficiency indicatorse3
- Direction
- improvede3
- Value
- 20-23 %e3
- Comparator
- the recommended dosee3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“maize production”
e3“Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splits reduced N use by 18.6 % and improved nitrogen use efficiency indicators by 20-23 % compared to the recommended dose, with comparable yields and 15 % lower N losses”
Claim · model-written summary
The DGCI-guided N regime gave comparable yields to the recommended dose.
- Treatment
- Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splitse3
- Outcome
- yieldse3
- Direction
- comparablee3
- Comparator
- the recommended dosee3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“maize production”
e3“Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splits reduced N use by 18.6 % and improved nitrogen use efficiency indicators by 20-23 % compared to the recommended dose, with comparable yields and 15 % lower N losses”
Claim · model-written summary
The DGCI-guided N regime lowered N losses by 15 % relative to the recommended dose.
- Treatment
- Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splitse3
- Outcome
- N lossese3
- Direction
- lowere3
- Value
- 15 %e3
- Comparator
- the recommended dosee3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“maize production”
e3“Applying 50 kg N ha⁻¹ as basal plus two DGCI-guided splits reduced N use by 18.6 % and improved nitrogen use efficiency indicators by 20-23 % compared to the recommended dose, with comparable yields and 15 % lower N losses”
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See all 2,185 papers →Claims are grouped by organism, treatment and what was measured or targeted. A paper counts as positive when any of its claims in the group is positive.