Abstract
Efficient nitrogen management is critical to improving maize (Zea mays L.) productivity and sustainability under rainfed conditions, where excessive or untimely N use can result in environmental degradation and low nitrogen use efficiency (NUE). Two years of field studies were conducted during consecutive Rabi seasons (2017-18 and 2018-19) at the wetland Farm of S.V. Agricultural College, Tirupati, to calibrate the lead colour chart (LCC) for increasing grain yield, NUE and nutrient uptake under varied planting densities. The study intended to establish threshold leaf greenness values as practical guides for in-season, need based nitrogen top dressing in maize. A split-split plot design was used with three planting densities (66666, 83333 and 111111 plants ha-1), three nitrogen levels (30, 35 and 40 kg N ha-1) and three LCC thresholds (4, 4.5 and 5). Results showed that highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5 significantly improved plant growth parameters, chlorophyll content, dry matter accumulation and kernel yield (5.36 t ha-1), along with enhanced nitrogen uptake (114.1 kg ha-1) and NUE (31.4 kg grain per kg N). Regression analysis revealed that dry weight (R² = 0.96), LAI (R² = 0.84) and NUE (R² = 0.70) were the strongest predictors of yield. LCC based nitrogen scheduling synchronized N supply with crop demand, minimized losses and improved soil N balance. These findings validate that LCC is an effective, ow cost tool for enhancing maize productivity and nutrient efficient under rainfed conditions.
Abstract from the paper’s OpenAlex record; open copy licensed cc-by. Read at the source ↗
The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.
Claims 9
Claim · model-written summary
Highest planting density with 40 kg N ha-1 applied on LCC 5 significantly increased maize kernel yield to 5.36 t ha-1.
- Treatment
- highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5e1
- Outcome
- kernel yielde1
- Direction
- improvede1
- Value
- 5.36 t ha-1e1
- Setting
- wetland Farm of S.V. Agricultural College, Tirupatie0
Zea maysNot reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e0“at the wetland Farm of S.V. Agricultural College, Tirupati”
e1“highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5 significantly improved plant growth parameters, chlorophyll content, dry matter accumulation and kernel yield (5.36 t ha-1), along with enhanced nitrogen uptake (114.1 kg ha-1) and NUE (31.4 kg grain per kg N)”
Claim · model-written summary
Highest planting density with 40 kg N ha-1 on LCC 5 significantly improved plant growth parameters, chlorophyll content and dry matter accumulation in maize.
- Treatment
- highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5e1
- Outcome
- plant growth parameters, chlorophyll content, dry matter accumulatione1
- Direction
- improvede1
- Setting
- wetland Farm of S.V. Agricultural College, Tirupatie0
Not reportedComparatorValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e0“at the wetland Farm of S.V. Agricultural College, Tirupati”
e1“highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5 significantly improved plant growth parameters, chlorophyll content, dry matter accumulation and kernel yield (5.36 t ha-1), along with enhanced nitrogen uptake (114.1 kg ha-1) and NUE (31.4 kg grain per kg N)”
Claim · model-written summary
Highest planting density with 40 kg N ha-1 on LCC 5 enhanced maize nitrogen uptake to 114.1 kg ha-1.
- Treatment
- highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5e1
- Outcome
- nitrogen uptakee1
- Direction
- enhancede1
- Value
- 114.1 kg ha-1e1
- Setting
- wetland Farm of S.V. Agricultural College, Tirupatie0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e0“at the wetland Farm of S.V. Agricultural College, Tirupati”
e1“highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5 significantly improved plant growth parameters, chlorophyll content, dry matter accumulation and kernel yield (5.36 t ha-1), along with enhanced nitrogen uptake (114.1 kg ha-1) and NUE (31.4 kg grain per kg N)”
Claim · model-written summary
Highest planting density with 40 kg N ha-1 on LCC 5 enhanced maize nitrogen use efficiency to 31.4 kg grain per kg N.
- Treatment
- highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5e1
- Outcome
- NUEe1
- Direction
- enhancede1
- Value
- 31.4 kg grain per kg Ne1
- Setting
- wetland Farm of S.V. Agricultural College, Tirupatie0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e0“at the wetland Farm of S.V. Agricultural College, Tirupati”
e1“highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5 significantly improved plant growth parameters, chlorophyll content, dry matter accumulation and kernel yield (5.36 t ha-1), along with enhanced nitrogen uptake (114.1 kg ha-1) and NUE (31.4 kg grain per kg N)”
Claim · model-written summary
Dry weight was the strongest predictor of maize yield, with R² = 0.96.
- Treatment
- dry weighte5
- Outcome
- yielde5
- Value
- R² = 0.96e5
- Setting
- wetland Farm of S.V. Agricultural College, Tirupatie0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e0“at the wetland Farm of S.V. Agricultural College, Tirupati”
e5“Regression analysis revealed that dry weight (R² = 0.96), LAI (R² = 0.84) and NUE (R² = 0.70) were the strongest predictors of yield”
Claim · model-written summary
LAI was a strong predictor of maize yield, with R² = 0.84.
- Treatment
- LAIe5
- Outcome
- yielde5
- Value
- R² = 0.84e5
- Setting
- wetland Farm of S.V. Agricultural College, Tirupatie0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e0“at the wetland Farm of S.V. Agricultural College, Tirupati”
e5“Regression analysis revealed that dry weight (R² = 0.96), LAI (R² = 0.84) and NUE (R² = 0.70) were the strongest predictors of yield”
Claim · model-written summary
NUE was a strong predictor of maize yield, with R² = 0.70.
- Treatment
- NUEe5
- Outcome
- yielde5
- Value
- R² = 0.70e5
- Setting
- wetland Farm of S.V. Agricultural College, Tirupatie0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e0“at the wetland Farm of S.V. Agricultural College, Tirupati”
e5“Regression analysis revealed that dry weight (R² = 0.96), LAI (R² = 0.84) and NUE (R² = 0.70) were the strongest predictors of yield”
Claim · model-written summary
LCC is an effective, low-cost tool for enhancing maize productivity under rainfed conditions.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e1“These findings validate that LCC is an effective, ow cost tool for enhancing maize productivity and nutrient efficient under rainfed conditions”
Claim · model-written summary
LCC based nitrogen scheduling improved soil N balance in maize.
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Rabi maize”
e1“LCC based nitrogen scheduling synchronized N supply with crop demand, minimized losses and improved soil N balance”
The same questions in other papers
lead atom · nutrient: content · Zea mays (maize)Results differ
14 in the opposite direction
- negative
- no effect
- negative
11 papers more in this group
See all 15 papers →lead atom · yield · Zea mays (maize)Positive and negative results
1 paper in the same direction as this paper · 2 in the opposite direction
- negative
- no effect
- positive
lead atom · physiology: pigments · Zea mays (maize)Positive and negative results
1 paper in the same direction as this paper · 3 in the opposite direction
- negative
- negative
- negative
1 paper more in this group
See all 5 papers →density · nutrient: efficiency · Zea mays (maize)Positive and negative results
8 papers in the same direction as this paper · 1 in the opposite direction
- no effect
- positive
- positive
6 papers more in this group
See all 10 papers →density · physiology: pigments · Zea mays (maize)Positive and negative results
9 papers in the same direction as this paper · 5 in the opposite direction
- negative
- negative
- negative
11 papers more in this group
See all 15 papers →density · nutrient: content · Zea mays (maize)Positive and negative results
33 papers in the same direction as this paper · 10 in the opposite direction
- no effect
- negative
- no effect
40 papers more in this group
See all 44 papers →nitrogen · physiology: pigments · Zea mays (maize)Positive and negative results
111 papers in the same direction as this paper · 13 in the opposite direction · 1 reporting no difference from an alternative
- negative
- negative
- no effect
122 papers more in this group
See all 126 papers →nitrogen · nutrient: efficiency · Zea mays (maize)Positive and negative results
141 papers in the same direction as this paper · 42 in the opposite direction · 10 reporting no difference from an alternative
- negative
- negative
- no effect
190 papers more in this group
See all 194 papers →8 of 11 groups shown: named compounds and organisms first, then groups whose results differ (checked claim by claim), then those with positive and negative results, then the smaller groups.
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.