4.7 Article

Impact of crop management and environment on the spatio-temporal variance of potato yield at regional scale

期刊

FIELD CROPS RESEARCH
卷 270, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.fcr.2021.108213

关键词

Spatial variance; Planting date; Irrigation; APSIM; Regional modelling; Solanum tuberosum L

类别

资金

  1. Universities Australia (Australia)
  2. German Academic Exchange Service (DAAD, Germany) through the Australia-Germany Joint Research Co-operation Scheme

向作者/读者索取更多资源

This study used a crop model to simulate potato yields, finding that irrigation had a significant impact on simulated yields, especially under different planting dates. There was a correlation between soil type and yield variance, with high PAWC soils being mainly affected by global solar radiation, while irrigation strategy became more important as PAWC values decreased.
The uncertainties associated with crop model inputs can affect the spatio-temporal variance of simulated yields, particularly under suboptimal irrigation. The aim of this study was to determine and quantify the main drivers of irrigated potato yield variance; as influenced by crop management practices as well as climate and soil factors. Using a locally calibrated crop model (APSIM), three planting dates x three irrigation strategies (plus a nonwater limited treatment) were simulated using 30 years of historical weather data across potato production areas in Tasmania, Australia. We used (i) correlation analysis, (ii) variance decomposition and (iii) maps to visualise the spatial decomposition of variance of potato yield. Our results showed that the implementation of potential irrigation compensated for the impact of planting date on climate drivers of simulated yield and changed the most important yield driving factors from irrigation and planting date to global solar radiation (r = 0.69-0.81). Under early-planting, we found positive correlations of simulated yield vs. global solar radiation (r up to 0.75 under high and medium irrigation) and between the simulated yield and rainfall (r up to 0.55 under low irrigation). In general, a mix of negative and positive correlations were found for minimum and maximum temperature depending on soil type. Using variance decomposition analysis, we found that crop management factors explained the greatest yield variance depending on soil type related to plant available water capacity (PAWC). For soils with high PAWC (>200 mm), most variance was explained by global solar radiation (56-62 %) followed by planting date (43-47 %). However, when PAWC values decreased from 242 mm to 94 mm, the contribution of global solar radiation and planting date were reduced from 62 % to 5.8 % and from 47 % to 4.4 %, respectively, and the contribution of irrigation strategy increased from 0.4%-32.5%. We identified a need to

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据