Potato, sweet potato, and yam models for climate change: A review

Raymundo, Rubí; Asseng, Senthold; Cammarano, Davide; Quiroz, Roberto

doi:10.1016/j.fcr.2014.06.017

Cited by 97 publications

(60 citation statements)

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“…Fewer studies have been conducted on the potential effects of climate change on root and tuber crops such as potato (Chen & Setter, 2012;Craigon et al, 2002;Katny et al, 2005) and cassava (Fernandez et al, 2002;Gleadow et al, 2009). In the case of yam, a small number of statistical analyses on the relationship between climatic data and yam yield in Africa (Ike, 2012;Zakari et al, 2014) as well as simulation studies based on models such as CROPSYSTVB-Yam and EPIC-Yam (Marcos et al, 2011;Srivastava & Gaiser, 2010;Srivastava et al, 2012) have been conducted but no experiments related to the effects of elevated [CO 2 ] have been performed in yam (Raymundo et al, 2014), including Chinese yam. Therefore, understanding the responses of Chinese yam to climate change factors such as increasing [CO 2 ] and air temperature is important to determine effective strategies for cultivation in the future.…”

Section: Temperature-gradient Chamber and Treatmentsmentioning

confidence: 99%

Effects of elevated CO₂ concentration on growth and photosynthesis of Chinese yam under different temperature regimes

Thinh

Shimono

Kumagai

et al. 2017

Plant Production Science

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Section: Temperature-gradient Chamber and Treatmentsmentioning

confidence: 99%

Effects of elevated CO₂ concentration on growth and photosynthesis of Chinese yam under different temperature regimes

Thinh

Shimono

Kumagai

et al. 2017

Plant Production Science

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“…These classical potato models are mainly based on the response to nitrogen fertilizer [30], temperature, and daylight [31] or the incidence of solar radiation [32] and are often used to estimate yields during the growing season. There is a wide range of potato crop growth models in the literature such as SUBSTOR-Potato, LINTUL-Potato, SOLANUM, APSIMPotato, SPUDSIM, POMOD, SIMPOTATO or Potato Calculator [33][34][35]. However, most of these models have not been comprehensively tested to real field data and some have never even been used in a real application [36].…”

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Potato Yield Prediction Using Machine Learning Techniques and Sentinel 2 Data

et al. 2019

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Traditional potato growth models evidence certain limitations, such as the cost of obtaining the input data required to run the models, the lack of spatial information in some instances, or the actual quality of input data. In order to address these issues, we develop a model to predict potato yield using satellite remote sensing. In an effort to offer a good predictive model that improves the state of the art on potato precision agriculture, we use images from the twin Sentinel 2 satellites (European Space Agency-Copernicus Programme) over three growing seasons, applying different machine learning models. First, we fitted nine machine learning algorithms with various pre-processing scenarios using variables from July, August and September based on the red, red-edge and infra-red bands of the spectrum. Second, we selected the best performing models and evaluated them against independent test data. Finally, we repeated the previous two steps using only variables corresponding to July and August. Our results showed that the feature selection step proved vital during data pre-processing in order to reduce multicollinearity among predictors. The Regression Quantile Lasso model (11.67% Root Mean Square Error, RMSE; R 2 = 0.88 and 9.18% Mean Absolute Error, MAE) and Leap Backwards model (10.94% RMSE, R 2 = 0.89 and 8.95% MAE) performed better when predictors with a correlation coefficient > 0.5 were removed from the dataset. In contrast, the Support Vector Machine Radial (svmRadial) performed better with no feature selection method (11.7% RMSE, R 2 = 0.93 and 8.64% MAE). In addition, we used a random forest model to predict potato yields in Castilla y León (Spain) 1-2 months prior to harvest, and obtained satisfactory results (11.16% RMSE, R 2 = 0.89 and 8.71% MAE). These results demonstrate the suitability of our models to predict potato yields in the region studied.The use of new technologies, such as satellite data, Geographic Information Systems (GIS) or Global Positioning Systems (GPS), can improve crop yield production and its quality [1], helping to secure food supply for the future as well as reducing the negative impacts resulting from agricultural practices [11]. More specifically, satellite remote sensing data has many applications in agriculture: soil property detection [12], crop type classification [13], crop yield forecast [14], crop health monitoring [15], soil moisture retrieval [16] or weather data assessment [17]. Remote sensing offers vast amounts of information which can be considered big data [18], and can help to improve crop modelling and decision-making. Big data has been described by Wolfert et al. [19] as "massive volumes of data with a wide variety that can be captured, analysed and used for decision-making", with said authors expecting big data to have a major impact on the agricultural sector. In order to improve the use of this data, given its size and variety, machine learning has emerged as an appropriate tool to identify rules and patterns in datasets [20], in addition to autonomously...

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“…However, current studies focus on the production quantity of yams and its change, being unable to identify the medical quality variation associated with climate change, soil, and geographical conditions. Moreover, Raymundo et al (2014) argued that the ability of both the CropSystVB-Yam and EPIC-Yam models in climate change impact assessment is limited mainly owing to the lack of calibrations with modern cultivars across agro-climatic zones.…”

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Agro-ecological suitability assessment of Chinese Medicinal Yam under future climate change

Fan

Zhong

et al. 2019

Environ Geochem Health

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Chinese Medicinal Yam (CMY) has been prescribed as medicinal food for thousand years in China by Traditional Chinese Medicine (TCM) practitioners. Its medical benefits include nourishing the stomach and spleen to improve digestion, replenishing lung and kidney, etc., according to the TCM literature. As living standard rises and public health awareness improves in recent years, the potential medicinal benefits of CMY have attracted increasing attention in China. It has been found that the observed climate change in last several decades, together with the change in economic structure, has driven significant shift in the pattern of the traditional CMY planting areas. To identify suitable planting area for CMY in the near future is critical for ensuring the quality and Dongli Fan and Honglin Zhong have contributed equally to this work.Environ Geochem Health (2020) 42:987-1000 https://doi.org/10.1007/s10653-019-00437-w( 0123456789().,-volV) (0123456789().,-volV) Hebei, and western Shandong. The climate suitability of these areas will be improved due to global warming in the next 50 years, and therefore, they will continue to be the most suitable CMY planting regions.

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Potato, sweet potato, and yam models for climate change: A review

Cited by 97 publications

References 100 publications

Effects of elevated CO₂ concentration on growth and photosynthesis of Chinese yam under different temperature regimes

Effects of elevated CO₂ concentration on growth and photosynthesis of Chinese yam under different temperature regimes

Potato Yield Prediction Using Machine Learning Techniques and Sentinel 2 Data

Agro-ecological suitability assessment of Chinese Medicinal Yam under future climate change

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Potato, sweet potato, and yam models for climate change: A review

Cited by 97 publications

References 100 publications

Effects of elevated CO2 concentration on growth and photosynthesis of Chinese yam under different temperature regimes

Effects of elevated CO2 concentration on growth and photosynthesis of Chinese yam under different temperature regimes

Potato Yield Prediction Using Machine Learning Techniques and Sentinel 2 Data

Agro-ecological suitability assessment of Chinese Medicinal Yam under future climate change

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Product

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Effects of elevated CO₂ concentration on growth and photosynthesis of Chinese yam under different temperature regimes

Effects of elevated CO₂ concentration on growth and photosynthesis of Chinese yam under different temperature regimes