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Sawatraksa N, Banterng P, Jogloy S, Vorasoot N, Hoogenboom G. Crop model determined mega-environments for cassava yield trials on paddy fields following rice. Heliyon 2023; 9:e14201. [PMID: 36923856 PMCID: PMC10009544 DOI: 10.1016/j.heliyon.2023.e14201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 02/19/2023] [Accepted: 02/23/2023] [Indexed: 03/06/2023] Open
Abstract
The Cropping System Model (CSM)-MANIHOT-Cassava provides the opportunity to determine target environments for cassava (Manihot esculenta Crantz) yield trials by simulating growth and yield data for various environments. The aim of this research was to investigate whether cassava production on paddy fields in Northeast, Thailand could be grouped into mega-environments using the model. Simulations for four different cassava genotypes grown on paddy field following rice harvest was conducted for various soil types and the weather data from 1988 to 2017. The genotype main effect plus genotype by environment interaction (GGE biplot) technique was used to group the mega-environments. The analyses of yearly data showed inconsistent results across years for environment grouping and for the winning genotypes of the individual environment group. An analysis using GGE biplot with the average value of the simulated storage root dry weight (SDW) for 30 years indicated that all 41 environments were grouped into two different mega-environments. This study demonstrated the ability of the CSM-MANIHOT-Cassava to help identify the mega-environments for cassava yield trials on paddy field during off-season of rice that could help reduce both time and resources.
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Affiliation(s)
- Nateetip Sawatraksa
- Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand.,Faculty of Science and Agricultural Technology, Rajamangala University of Technology Lanna Lampang, Lampang, 52000, Thailand
| | - Poramate Banterng
- Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand.,Plant Breeding Research Center for Sustainable Agriculture, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Sanun Jogloy
- Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand.,Plant Breeding Research Center for Sustainable Agriculture, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Nimitr Vorasoot
- Department of Agronomy, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Gerrit Hoogenboom
- Institute for Sustainable Food Systems, University of Florida, 32611, USA.,Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, 32611, USA
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Gupta D, Gujre N, Singha S, Mitra S. Role of existing and emerging technologies in advancing climate-smart agriculture through modeling: A review. ECOL INFORM 2022. [DOI: 10.1016/j.ecoinf.2022.101805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Koimbori JK, Wang S, Pan J, Guo L, Li K. Yield Response of Spring Maize under Future Climate and the Effects of Adaptation Measures in Northeast China. PLANTS (BASEL, SWITZERLAND) 2022; 11:1634. [PMID: 35807590 PMCID: PMC9269085 DOI: 10.3390/plants11131634] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 06/11/2022] [Accepted: 06/13/2022] [Indexed: 06/15/2023]
Abstract
Agriculture production has been found to be the most sensitive sector to climate change. Northeast China (NEC) is one of the world's major regions for spring maize production and it has been affected by climate change due to increases in temperature and decreases in sunshine hours and precipitation levels over the past few decades. In this study, the CERES-Maize model-v4.7 was adopted to assess the impact of future climatic change on the yield of spring maize in NEC and the effect of adaptation measures in two future periods, the 2030s (2021 to 2040) and the 2050s (2041 to 2060) relative to the baseline (1986 to 2005) under RCP4.5 and RCP8.5 scenarios. The results showed that increased temperatures and the decreases in both the precipitation level and sunshine hours in the NEC at six representative sites in the 2030s and 2050s periods based on RCP4.5 and RCP8.5 climate scenarios would shorten the maize growth durations by (1-38 days) and this would result in a reduction in maize yield by (2.5-26.4%). Adaptation measures, including altered planting date, supplemental irrigation and use of cultivars with longer growth periods could offset some negative impacts of yield decrease in maize. For high-temperature-sensitive cultivars, the adoption of early planting, cultivar change and adding irrigation practices could lead to an increase in maize yield by 23.7-43.6% and these measures were shown to be effective adaptation options towards reducing yield loss from climate change. The simulation results exhibited the effective contribution of appropriate adaptation measures in eliminating the negative impact of future climate change on maize yield.
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Affiliation(s)
- Jackson K. Koimbori
- Key Lab for Agro-Environment, Ministry of Agriculture and Rural Affairs, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (J.K.K.); (J.P.); (L.G.)
| | - Shuai Wang
- College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China;
| | - Jie Pan
- Key Lab for Agro-Environment, Ministry of Agriculture and Rural Affairs, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (J.K.K.); (J.P.); (L.G.)
| | - Liping Guo
- Key Lab for Agro-Environment, Ministry of Agriculture and Rural Affairs, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (J.K.K.); (J.P.); (L.G.)
| | - Kuo Li
- Key Lab for Agro-Environment, Ministry of Agriculture and Rural Affairs, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (J.K.K.); (J.P.); (L.G.)
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Moreno-Cadena P, Hoogenboom G, Cock JH, Ramirez-Villegas J, Pypers P, Kreye C, Tariku M, Ezui KS, Becerra Lopez-Lavalle LA, Asseng S. Modeling growth, development and yield of cassava: A review. FIELD CROPS RESEARCH 2021; 267:108140. [PMID: 34140751 PMCID: PMC8146721 DOI: 10.1016/j.fcr.2021.108140] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Cassava is an important crop in the developing world. The goal of this study was to review published cassava models (18) for their capability to simulate storage root biomass and to categorize them into static and dynamic models. The majority (14) are dynamic and capture within season growth dynamics. Most (13) of the dynamic models consider environmental factors such as temperature, solar radiation, soil water and nutrient restrictions. More than half (10) have been calibrated for a distinct genotype. Only one of the four static models includes environmental variables. While the static regression models are useful to estimate final yield, their application is limited to the locations or varieties used for their development unless recalibrated for distinct conditions. Dynamic models simulate growth process and provide estimates of yield over time with, in most cases, no fixed maturity date. The dynamic models that simulate the detailed development of nodal units tend to be less accurate in determining final yield compared to the simpler dynamic and statistic models. However, they can be more safely applied to novel environmental conditions that can be explored in silico. Deficiencies in the current models are highlighted including suggestions on how they can be improved. None of the current dynamic cassava models adequately simulates the starch content of fresh cassava roots with almost all models based on dry biomass simulations. Further studies are necessary to develop a new module for existing cassava models to simulate cassava quality.
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Affiliation(s)
- Patricia Moreno-Cadena
- Agricultural and Biological Engineering Department, University of Florida, 101 Frazier Rogers Hall, PO Box 110570, Gainesville, FL, 32611-0570, USA
- Alliance of Bioversity International and International Center for Tropical Agriculture (CIAT), km 17 recta Cali–Palmira, 763537, Cali, Colombia
- International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
- Corresponding author at: Agricultural and Biological Engineering Department, University of Florida, 101 Frazier Rogers Hall, PO Box 110570, Gainesville, FL, 32611-0570, USA.
| | - Gerrit Hoogenboom
- Agricultural and Biological Engineering Department, University of Florida, 101 Frazier Rogers Hall, PO Box 110570, Gainesville, FL, 32611-0570, USA
- Institute for Sustainable Food Systems, University of Florida, 101 Frazier Rogers Hall, PO Box 110570, Gainesville, FL, 32611-0570, USA
| | - James H. Cock
- Alliance of Bioversity International and International Center for Tropical Agriculture (CIAT), km 17 recta Cali–Palmira, 763537, Cali, Colombia
| | - Julian Ramirez-Villegas
- Alliance of Bioversity International and International Center for Tropical Agriculture (CIAT), km 17 recta Cali–Palmira, 763537, Cali, Colombia
- CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Cali, Colombia
| | - Pieter Pypers
- International Institute of Tropical Agriculture (IITA), ICIPE Campus, P.O. Box 30772-00100, Nairobi, Kenya
| | - Christine Kreye
- International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Meklit Tariku
- International Institute of Tropical Agriculture (IITA), ICIPE Campus, P.O. Box 30772-00100, Nairobi, Kenya
| | - Kodjovi Senam Ezui
- African Plant Nutrition Institute (APNI), ICIPE Campus, Duduville – Kasarani, Thika Road, Nairobi, Kenya
| | - Luis Augusto Becerra Lopez-Lavalle
- Alliance of Bioversity International and International Center for Tropical Agriculture (CIAT), km 17 recta Cali–Palmira, 763537, Cali, Colombia
| | - Senthold Asseng
- Agricultural and Biological Engineering Department, University of Florida, 101 Frazier Rogers Hall, PO Box 110570, Gainesville, FL, 32611-0570, USA
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