Climate variability and change impacts on crop productivity
DOI:
https://doi.org/10.4081/ija.2022.2177Abstract
Not available
Downloads
References
Acibuca V, Kaya A, Kaya T, 2022. Interregional comparative analysis of ‘farmers’ perceptions and expectations of climate change. Ital. J. Agron. 17:2121. https://doi.org/10.4081/ija.2022.2121
Adusei G, Aidoo MK, Srivastava AK, Asibuo JY, Gaiser T, 2022. The impact of climate change on the productivity of cowpea (Vigna unguiculata) under three different socio-economic pathways. Ital. J. Agron. 17:2118. https://doi.org/10.4081/ija.2022.2118
Asseng S, Ewert F, Martre P, Rötter RP, Lobell DB, Cammarano D, et al. 2015. Rising temperatures reduce global wheat production. Nat. Clim. Change 5:5.
Asseng S, Ewert F, Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, et al. 2013. Uncertainty in simulating wheat yields under climate change. Nat. Clim. Change 3:827.
Basso B, 2022. Techno-diversity for carbon farming and climate resilience. Ital. J. Agron. 17:2178. https://doi.org/10.4081/ija.2022.2178
Cammarano D, Becherini F, Leolini L, Camuffo D, Moriondo M, della Valle A, Ferrise R, 2022. Impact of long-term (1764-2017) air temperature on phenology of cereals and vines in two locations of northern Italy. Ital. J. Agron. 17:2164. https://doi.org/10.4081/ija.2022.2164
Ehsan N, Hoogenboom G, Qamar MK, Wilkerson CJ, Wajid SA, Aziz F, 2022. Climate change risk perception and adaptation to climate smart agriculture are required to increase wheat production for food security. Ital. J. Agron. 17:2129. https://doi.org/10.4081/ija.2022.2129
Intergovernmental Panel on Climate Change I, 2021 Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B. (Eds.). Cambridge: Cambridge University Press.
Li X, Chen C, Yang X, Xiong J, Ma N, 2022. The optimisation of rapeseed yield and growth duration through adaptive crop management in climate change: evidence from China. Ital. J. Agron. 17:2104. https://doi.org/10.4081/ija.2022.2104
Lobell DB, Asseng S, 2017. Comparing estimates of climate change impacts from process-based and statistical crop models. Environ. Res. Lett. 12:13.
Pulina P, Ferrise R, Mula L, Brilli L, Giglio L, Iocola I, Ventrella D, Zavattaro L, Grignani C, Roggero PP, 2022. The ability of crop models to predict soil organic carbon changes in a maize cropping system under contrasting fertilization and residues management: evidence from a long-term experiment. Ital. J. Agron. 17:2179. https://doi.org/10.4081/ija.2022.2179
Schillaci C, Inverardi F, Battaglia ML, Perego A, Thomason W, Acutis M, 2022. Assessment of hail damages in maize using remote sensing and comparison with an insurance assessment: a case study in Lombardy. Ital. J. Agron. 17:2126. https://doi.org/10.4081/ija.2022.2126
Wang E, Martre P, Zhao Z, Ewert F, Maiorano A, Rötter RP, Kimball BA, Ottman MJ, Wall GW, White JW, Reynolds MP, Alderman PD, Aggarwal PK, Anothai J, Basso B, Biernath C, Cammarano D, Challinor AJ, et al. 2017. The uncertainty of crop yield projections is reduced by improved temperature response functions. Nat. Plants 3:17102.
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
