数据驱动模型在巴西全国范围内估计和预测大豆产量的潜在用途

IF 2.1 3区农林科学 Q2 AGRONOMY

International Journal of Plant Production Pub Date : 2022-09-07 DOI:10.1007/s42106-022-00209-0

L. Monteiro, Rafael M. Ramos, R. Battisti, J. Soares, Julianne C. Oliveira, G. Figueiredo, R. A. Lamparelli, C. Nendel, M. Lana

引用次数: 3

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Potential Use of Data-Driven Models to Estimate and Predict Soybean Yields at National Scale in Brazil

查看原文本刊更多论文

Potential Use of Data-Driven Models to Estimate and Predict Soybean Yields at National Scale in Brazil

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Plant Production 农林科学-农艺学

CiteScore

5.30

自引率

4.00%

发文量

审稿时长

6 months

期刊介绍： IJPP publishes original research papers and review papers related to physiology, ecology and production of field crops and forages at field, farm and landscape level. Preferred topics are: (1) yield gap in cropping systems: estimation, causes and closing measures, (2) ecological intensification of plant production, (3) improvement of water and nutrients management in plant production systems, (4) environmental impact of plant production, (5) climate change and plant production, and (6) responses of plant communities to extreme weather conditions. Please note that IJPP does not publish papers with a background in genetics and plant breeding, plant molecular biology, plant biotechnology, as well as soil science, meteorology, product process and post-harvest management unless they are strongly related to plant production under field conditions. Papers based on limited data or of local importance, and results from routine experiments will not normally be considered for publication. Field experiments should include at least two years and/or two environments. Papers on plants other than field crops and forages, and papers based on controlled-environment experiments will not be considered.