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“yield decrease”

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2020

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paper W4409452756 ✕

Intervention effectobservedoriginal resultnegativeprojected

Claim · model-written summary

Yield trait optimization projected a 13–21 % decrease in nitrogen-use efficiency.

Taxon: wheatTriticum aestivume1
Treatment: trait-optimisation for yielde0
Outcome: nitrogen-use efficiencye0
Direction: decreasee0
Value: 13–21 %e0

Not reportedComparator

Verbatim

e0
“trait-optimisation for yield revealed clear trade-offs for nitrogen demand (16–36 % increase), N 2 O emissions (30–50 % increase), greenhouse gas emission intensity (24–35 % increase) and nitrogen-use efficiency (13–21 % decrease)”
✓ located verbatim in the source · abstract, characters 1835–2065

t0
“Dire need for quantification of environmental impacts associated with breeding climate-resilient crops”
✓ located verbatim in the source · title, characters 0–102

e1
“climate and wheat yield variability”
✓ located verbatim in the source · abstract, characters 1130–1165

Title

Dire need for quantification of environmental impacts associated with breeding climate-resilient crops

Chunhu Wang; Matthew Tom Harrison; De Li Liu; et al. Agricultural Systems 2025. doi:10.1016/j.agsy.2025.104352

Other claims from this paper (12)

Association Climate and wheat yield variability were significantly correlated in many arable areas.
Association precipitation explained wheat yield variance (R 2 = 0.38).
Association temperature explained wheat yield variance (R 2 = 0.31).
Association solar radiation explained wheat yield variance (R 2 = 0.29).
Association Photothermal quotients explained regional wheat yield gaps and ranged from 0.55 to 1.14.
Observation Rainfed wheat yield was projected to decrease by 12 % in the 2050s under SSP245.
Observation Rainfed wheat yield was projected to decrease by 24 % in the 2050s under SSP585.
Intervention effect Cultivars with higher RUE and larger grain size could increase grain yield by 61–80% under current and future climates.
Intervention effect Yield trait optimization projected a 16–36 % increase in nitrogen demand.
Intervention effect Yield trait optimization projected a 30–50 % increase in N 2 O emissions.
Intervention effect Yield trait optimization projected a 24–35 % increase in greenhouse gas emission intensity.
Recommendation The authors recommend that crop breeding include sustainability indicators for nitrogen demand, use and efficiency.

Observationobservedoriginal resultprojected

Claim · model-written summary

Rainfed wheat yield was projected to decrease by 12 % in the 2050s under SSP245.

Taxon: wheatTriticum aestivume0
Outcome: rainfed wheat yieldse0
Direction: decreasede0
Value: 12 %e0
Qualifier: SSP245e0

Verbatim

e0
“simulated rainfed wheat yields decreased by 12 % and 24 % in 2050s under emissions scenarios SSP245 and SSP585, respectively”
✓ located verbatim in the source · abstract, characters 1549–1673

Title

Dire need for quantification of environmental impacts associated with breeding climate-resilient crops

Chunhu Wang; Matthew Tom Harrison; De Li Liu; et al. Agricultural Systems 2025. doi:10.1016/j.agsy.2025.104352

Other claims from this paper (12)

Association Climate and wheat yield variability were significantly correlated in many arable areas.
Association precipitation explained wheat yield variance (R 2 = 0.38).
Association temperature explained wheat yield variance (R 2 = 0.31).
Association solar radiation explained wheat yield variance (R 2 = 0.29).
Association Photothermal quotients explained regional wheat yield gaps and ranged from 0.55 to 1.14.
Observation Rainfed wheat yield was projected to decrease by 24 % in the 2050s under SSP585.
Intervention effect Cultivars with higher RUE and larger grain size could increase grain yield by 61–80% under current and future climates.
Intervention effect Yield trait optimization projected a 16–36 % increase in nitrogen demand.
Intervention effect Yield trait optimization projected a 30–50 % increase in N 2 O emissions.
Intervention effect Yield trait optimization projected a 24–35 % increase in greenhouse gas emission intensity.
Intervention effect Yield trait optimization projected a 13–21 % decrease in nitrogen-use efficiency.
Recommendation The authors recommend that crop breeding include sustainability indicators for nitrogen demand, use and efficiency.

Observationobservedoriginal resultprojected

Claim · model-written summary

Rainfed wheat yield was projected to decrease by 24 % in the 2050s under SSP585.

Taxon: wheatTriticum aestivume0
Outcome: rainfed wheat yieldse0
Direction: decreasede0
Value: 24 %e0
Qualifier: SSP585e0

Verbatim

e0
“simulated rainfed wheat yields decreased by 12 % and 24 % in 2050s under emissions scenarios SSP245 and SSP585, respectively”
✓ located verbatim in the source · abstract, characters 1549–1673

Title

Dire need for quantification of environmental impacts associated with breeding climate-resilient crops

Chunhu Wang; Matthew Tom Harrison; De Li Liu; et al. Agricultural Systems 2025. doi:10.1016/j.agsy.2025.104352

Other claims from this paper (12)

Association Climate and wheat yield variability were significantly correlated in many arable areas.
Association precipitation explained wheat yield variance (R 2 = 0.38).
Association temperature explained wheat yield variance (R 2 = 0.31).
Association solar radiation explained wheat yield variance (R 2 = 0.29).
Association Photothermal quotients explained regional wheat yield gaps and ranged from 0.55 to 1.14.
Observation Rainfed wheat yield was projected to decrease by 12 % in the 2050s under SSP245.
Intervention effect Cultivars with higher RUE and larger grain size could increase grain yield by 61–80% under current and future climates.
Intervention effect Yield trait optimization projected a 16–36 % increase in nitrogen demand.
Intervention effect Yield trait optimization projected a 30–50 % increase in N 2 O emissions.
Intervention effect Yield trait optimization projected a 24–35 % increase in greenhouse gas emission intensity.
Intervention effect Yield trait optimization projected a 13–21 % decrease in nitrogen-use efficiency.
Recommendation The authors recommend that crop breeding include sustainability indicators for nitrogen demand, use and efficiency.

Intervention effectobservedoriginal resultnegativeprojected

Claim · model-written summary

Yield trait optimization projected a 16–36 % increase in nitrogen demand.

Taxon: wheatTriticum aestivume1
Treatment: trait-optimisation for yielde0
Outcome: nitrogen demande0
Direction: increasee0
Value: 16–36 %e0

Not reportedComparator

Verbatim

e0
“trait-optimisation for yield revealed clear trade-offs for nitrogen demand (16–36 % increase), N 2 O emissions (30–50 % increase), greenhouse gas emission intensity (24–35 % increase) and nitrogen-use efficiency (13–21 % decrease)”
✓ located verbatim in the source · abstract, characters 1835–2065

t0
“Dire need for quantification of environmental impacts associated with breeding climate-resilient crops”
✓ located verbatim in the source · title, characters 0–102

e1
“climate and wheat yield variability”
✓ located verbatim in the source · abstract, characters 1130–1165

Title

Dire need for quantification of environmental impacts associated with breeding climate-resilient crops

Chunhu Wang; Matthew Tom Harrison; De Li Liu; et al. Agricultural Systems 2025. doi:10.1016/j.agsy.2025.104352

Other claims from this paper (12)

Association Climate and wheat yield variability were significantly correlated in many arable areas.
Association precipitation explained wheat yield variance (R 2 = 0.38).
Association temperature explained wheat yield variance (R 2 = 0.31).
Association solar radiation explained wheat yield variance (R 2 = 0.29).
Association Photothermal quotients explained regional wheat yield gaps and ranged from 0.55 to 1.14.
Observation Rainfed wheat yield was projected to decrease by 12 % in the 2050s under SSP245.
Observation Rainfed wheat yield was projected to decrease by 24 % in the 2050s under SSP585.
Intervention effect Cultivars with higher RUE and larger grain size could increase grain yield by 61–80% under current and future climates.
Intervention effect Yield trait optimization projected a 30–50 % increase in N 2 O emissions.
Intervention effect Yield trait optimization projected a 24–35 % increase in greenhouse gas emission intensity.
Intervention effect Yield trait optimization projected a 13–21 % decrease in nitrogen-use efficiency.
Recommendation The authors recommend that crop breeding include sustainability indicators for nitrogen demand, use and efficiency.

Intervention effectobservedoriginal resultnegativeprojected

Claim · model-written summary

Yield trait optimization projected a 30–50 % increase in N 2 O emissions.

Taxon: wheatTriticum aestivume1
Treatment: trait-optimisation for yielde0
Outcome: N 2 O emissionse0
Direction: increasee0
Value: 30–50 %e0

Not reportedComparator

Verbatim

e0
“trait-optimisation for yield revealed clear trade-offs for nitrogen demand (16–36 % increase), N 2 O emissions (30–50 % increase), greenhouse gas emission intensity (24–35 % increase) and nitrogen-use efficiency (13–21 % decrease)”
✓ located verbatim in the source · abstract, characters 1835–2065

t0
“Dire need for quantification of environmental impacts associated with breeding climate-resilient crops”
✓ located verbatim in the source · title, characters 0–102

e1
“climate and wheat yield variability”
✓ located verbatim in the source · abstract, characters 1130–1165

Title

Dire need for quantification of environmental impacts associated with breeding climate-resilient crops

Chunhu Wang; Matthew Tom Harrison; De Li Liu; et al. Agricultural Systems 2025. doi:10.1016/j.agsy.2025.104352

Other claims from this paper (12)

Association Climate and wheat yield variability were significantly correlated in many arable areas.
Association precipitation explained wheat yield variance (R 2 = 0.38).
Association temperature explained wheat yield variance (R 2 = 0.31).
Association solar radiation explained wheat yield variance (R 2 = 0.29).
Association Photothermal quotients explained regional wheat yield gaps and ranged from 0.55 to 1.14.
Observation Rainfed wheat yield was projected to decrease by 12 % in the 2050s under SSP245.
Observation Rainfed wheat yield was projected to decrease by 24 % in the 2050s under SSP585.
Intervention effect Cultivars with higher RUE and larger grain size could increase grain yield by 61–80% under current and future climates.
Intervention effect Yield trait optimization projected a 16–36 % increase in nitrogen demand.
Intervention effect Yield trait optimization projected a 24–35 % increase in greenhouse gas emission intensity.
Intervention effect Yield trait optimization projected a 13–21 % decrease in nitrogen-use efficiency.
Recommendation The authors recommend that crop breeding include sustainability indicators for nitrogen demand, use and efficiency.

Intervention effectobservedoriginal resultnegativeprojected

Claim · model-written summary

Yield trait optimization projected a 24–35 % increase in greenhouse gas emission intensity.

Taxon: wheatTriticum aestivume1
Treatment: trait-optimisation for yielde0
Outcome: greenhouse gas emission intensitye0
Direction: increasee0
Value: 24–35 %e0

Not reportedComparator

Verbatim

e0
“trait-optimisation for yield revealed clear trade-offs for nitrogen demand (16–36 % increase), N 2 O emissions (30–50 % increase), greenhouse gas emission intensity (24–35 % increase) and nitrogen-use efficiency (13–21 % decrease)”
✓ located verbatim in the source · abstract, characters 1835–2065

t0
“Dire need for quantification of environmental impacts associated with breeding climate-resilient crops”
✓ located verbatim in the source · title, characters 0–102

e1
“climate and wheat yield variability”
✓ located verbatim in the source · abstract, characters 1130–1165

Title

Dire need for quantification of environmental impacts associated with breeding climate-resilient crops

Chunhu Wang; Matthew Tom Harrison; De Li Liu; et al. Agricultural Systems 2025. doi:10.1016/j.agsy.2025.104352

Other claims from this paper (12)

Association Climate and wheat yield variability were significantly correlated in many arable areas.
Association precipitation explained wheat yield variance (R 2 = 0.38).
Association temperature explained wheat yield variance (R 2 = 0.31).
Association solar radiation explained wheat yield variance (R 2 = 0.29).
Association Photothermal quotients explained regional wheat yield gaps and ranged from 0.55 to 1.14.
Observation Rainfed wheat yield was projected to decrease by 12 % in the 2050s under SSP245.
Observation Rainfed wheat yield was projected to decrease by 24 % in the 2050s under SSP585.
Intervention effect Cultivars with higher RUE and larger grain size could increase grain yield by 61–80% under current and future climates.
Intervention effect Yield trait optimization projected a 16–36 % increase in nitrogen demand.
Intervention effect Yield trait optimization projected a 30–50 % increase in N 2 O emissions.
Intervention effect Yield trait optimization projected a 13–21 % decrease in nitrogen-use efficiency.
Recommendation The authors recommend that crop breeding include sustainability indicators for nitrogen demand, use and efficiency.

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