Paper · 2025 · Agronomy

Rice Yield and Nitrogen Use Efficiency Under Climate Change: Unraveling Key Drivers with Least Absolute Shrinkage and Selection Operator Regression

Yingjun Ma; Menglong Sun; Xianglong Liang; et al.

7
claims
14
verbatim quotes
6
citations
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research areas
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Open access · cc-by

Abstract

Rice (Oryza sativa L.), a staple crop vital to global food security, faces escalating threats from climate change and inefficient nitrogen management. This study employed least absolute shrinkage and selection operator (LASSO) regression to analyze the stage-specific impacts of nitrogen application, temperature, and rainfall on rice yield and nitrogen use efficiency (NUE) across three growing seasons (2020–2022) in Jiangsu Province, China. The key findings revealed the following: (1) the reproductive stages (flowering and filling stages) exhibited extreme thermal sensitivity, with high temperatures (>35 °C) causing substantial yield losses (33.1% average) and reducing nitrogen recovery efficiency (NRE: 22.4–60.5% loss) and the nitrogen translocation ratio (NTR: 26.3–61.6% loss); (2) the vegetative stages (tillering and jointing and booting stages) were highly rainfall-sensitive, with rainfall during tillering (2.1–9.7 mm/day) influencing 50% of the traits, including four NUE types; (3) appropriate nitrogen management (250–350 kgN·ha−1) mitigated the heat-induced losses, increasing physiological nitrogen use efficiency (PNUE) by 30.0–41.8% under extreme heat and alleviating the losses of yield. This study further verified the generalizability of LASSO. Compared with the traditional models, LASSO overcomes the issue of multicollinearity and can more effectively identify the key factors driving climate change across different spatial gradients. These findings provide actionable insights for optimizing nitrogen application timing, improving climate-resilient breeding, and developing stage-specific adaptation strategies to safeguard rice productivity under global warming.

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 7

Associationobservedoriginal resultnegativemeasured

Claim · model-written summary

High reproductive-stage temperatures caused average rice yield losses of 33.1%.

Organ / stage
flowering and filling stagese0
Treatment
high temperatures (>35 °C)e0
Outcome
yield lossese0
Direction
lossese0
Value
33.1%e0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Oryza sativa
Oryza sativa · Taxon · picture from its Wikimedia Commons categoryDesmanthus4food · CC BY-SA 3.0 us · Wikimedia Commons ↗

Verbatim

e0

“the reproductive stages (flowering and filling stages) exhibited extreme thermal sensitivity, with high temperatures (>35 °C) causing substantial yield losses (33.1% average)”

✓ located verbatim in the source · abstract, characters 489–663 · show in text ↑
t0

“Rice Yield and Nitrogen Use Efficiency”

✓ located verbatim in the source · title, characters 0–38 · show in text ↑
Associationobservedoriginal resultnegativemeasured

Claim · model-written summary

High temperatures reduced nitrogen recovery efficiency by 22.4–60.5%.

Treatment
high temperatures (>35 °C)e0
Outcome
nitrogen recovery efficiencye0
Direction
reducinge0
Value
22.4–60.5%e0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Oryza sativa
Oryza sativa · Taxon · picture from its Wikimedia Commons categoryDesmanthus4food · CC BY-SA 3.0 us · Wikimedia Commons ↗

Verbatim

e0

“high temperatures (>35 °C) causing substantial yield losses (33.1% average) and reducing nitrogen recovery efficiency (NRE: 22.4–60.5% loss)”

✓ located verbatim in the source · abstract, characters 588–728 · show in text ↑
t0

“Rice Yield and Nitrogen Use Efficiency”

✓ located verbatim in the source · title, characters 0–38 · show in text ↑
Associationobservedoriginal resultnegativemeasured

Claim · model-written summary

High temperatures reduced nitrogen translocation ratio by 26.3–61.6%.

Outcome
nitrogen translocation ratioe0
Direction
losse0
Value
26.3–61.6%e0

Not reportedTreatment

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Oryza sativa
Oryza sativa · Taxon · picture from its Wikimedia Commons categoryDesmanthus4food · CC BY-SA 3.0 us · Wikimedia Commons ↗

Verbatim

e0

“reducing nitrogen recovery efficiency (NRE: 22.4–60.5% loss) and the nitrogen translocation ratio (NTR: 26.3–61.6% loss)”

✓ located verbatim in the source · abstract, characters 668–788 · show in text ↑
t0

“Rice Yield and Nitrogen Use Efficiency”

✓ located verbatim in the source · title, characters 0–38 · show in text ↑
Associationobservedoriginal resultmeasured

Claim · model-written summary

Tillering rainfall influenced half the measured traits, including four NUE types.

Treatment
rainfall during tillering (2.1–9.7 mm/day)e0
Outcome
traitse0
Value
50%e0
Qualifier
including four NUE typese0

Not reportedDirection

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Oryza sativa
Oryza sativa · Taxon · picture from its Wikimedia Commons categoryDesmanthus4food · CC BY-SA 3.0 us · Wikimedia Commons ↗

Verbatim

e0

“rainfall during tillering (2.1–9.7 mm/day) influencing 50% of the traits, including four NUE types”

✓ located verbatim in the source · abstract, characters 897–995 · show in text ↑
t0

“Rice Yield and Nitrogen Use Efficiency”

✓ located verbatim in the source · title, characters 0–38 · show in text ↑
Intervention effectobservedoriginal resultpositivemeasured

Claim · model-written summary

Nitrogen at 250–350 kgN·ha−1 increased PNUE by 30.0–41.8% under extreme heat.

Treatment
nitrogen management (250–350 kgN·ha−1)e0
Outcome
physiological nitrogen use efficiencye0
Direction
increasinge0
Value
30.0–41.8%e0
Qualifier
under extreme heate0

Not reportedComparator

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Oryza sativa
Oryza sativa · Taxon · picture from its Wikimedia Commons categoryDesmanthus4food · CC BY-SA 3.0 us · Wikimedia Commons ↗

Verbatim

e0

“appropriate nitrogen management (250–350 kgN·ha−1) mitigated the heat-induced losses, increasing physiological nitrogen use efficiency (PNUE) by 30.0–41.8% under extreme heat”

✓ located verbatim in the source · abstract, characters 1001–1175 · show in text ↑
t0

“Rice Yield and Nitrogen Use Efficiency”

✓ located verbatim in the source · title, characters 0–38 · show in text ↑
Intervention effectobservedoriginal resultpositivemeasured

Claim · model-written summary

Nitrogen management alleviated heat-induced yield losses.

Treatment
nitrogen management (250–350 kgN·ha−1)e0
Outcome
losses of yielde0
Direction
alleviatinge0

Not reportedComparator

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Oryza sativa
Oryza sativa · Taxon · picture from its Wikimedia Commons categoryDesmanthus4food · CC BY-SA 3.0 us · Wikimedia Commons ↗

Verbatim

e0

“appropriate nitrogen management (250–350 kgN·ha−1) mitigated the heat-induced losses, increasing physiological nitrogen use efficiency (PNUE) by 30.0–41.8% under extreme heat and alleviating the losses of yield”

✓ located verbatim in the source · abstract, characters 1001–1211 · show in text ↑
t0

“Rice Yield and Nitrogen Use Efficiency”

✓ located verbatim in the source · title, characters 0–38 · show in text ↑
Method / resourceauthor interpretationoriginal resultpositivemeasured

Claim · model-written summary

LASSO overcame multicollinearity and identified climate drivers more effectively than traditional models.

Outcome
identify the key factors driving climate changee0
Direction
more effectivelye0
Comparator
traditional modelse0

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Oryza sativa
Oryza sativa · Taxon · picture from its Wikimedia Commons categoryDesmanthus4food · CC BY-SA 3.0 us · Wikimedia Commons ↗

Verbatim

e0

“Compared with the traditional models, LASSO overcomes the issue of multicollinearity and can more effectively identify the key factors driving climate change across different spatial gradients”

✓ located verbatim in the source · abstract, characters 1272–1464 · show in text ↑
t0

“Rice Yield and Nitrogen Use Efficiency”

✓ located verbatim in the source · title, characters 0–38 · show in text ↑

nitrogen · nutrient: efficiency · Oryza sativa (rice)Positive and negative results

262 papers: 217 positive, 45 negative or no effect

216 papers in the same direction as this paper · 41 in the opposite direction · 4 reporting no difference from an alternative

  1. negative
  2. negative
  3. no effect

258 papers more in this group

See all 262 papers →

nitrogen · yield · Oryza sativa (rice)Positive and negative results

2,045 papers: 1,803 positive, 242 negative or no effect

1,802 papers in the same direction as this paper · 193 in the opposite direction · 49 reporting no difference from an alternative

  1. positive
  2. negative
  3. negative

2,041 papers more in this group

See all 2,045 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.