Determining the optimum climate preseason for plant phenology analysis using rubber (Hevea brasiliensis) as a model

巴西橡胶树 物候学 天然橡胶 环境科学 气候变化 生物 植物 生态学 材料科学 复合材料
作者
Fathin Ayuni Azizan,Anthony Young,Ammar Abdul Aziz
出处
期刊:Remote Sensing Letters [Informa]
卷期号:13 (11): 1121-1130 被引量:2
标识
DOI:10.1080/2150704x.2022.2131477
摘要

Identifying the optimum preseason that best explains subsequent plant phenology is essential to understanding how climatic factors influence plant growth. This study evaluated the preseason (30, 60, 90, 120, and 180-day) influence of average temperature and rainfall accumulation on the two primary phenological events for rubber (Hevea brasiliensis): refoliation, or start of season (SOS), and defoliation, or end of the season (EOS). These phenological events were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Different Vegetation Index (NDVI) time-series data over a ten-year period (2010 to 2019). Pearson correlation and multiple linear regression analyses were performed using these datasets to determine the optimal climate preseason for rubber phenology, based on the highest coefficient results. The results showed that the 90-day preseason conditions prior to the SOS and EOS were critical in advancing or delaying the start and end of the rubber season compared to other preseasons, indicated by the best combination of moderate to high correlation values. The 90-day preseason had the highest coefficient of determination (R2) and lowest root mean standard error (RMSE), confirming its utility for identifying preseason conditions for studying rubber phenology.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
keanu发布了新的文献求助10
刚刚
刚刚
桐桐应助liyh采纳,获得10
刚刚
大宝剑2号完成签到,获得积分10
刚刚
1秒前
1秒前
1秒前
1秒前
LL完成签到,获得积分10
2秒前
2秒前
2秒前
2秒前
king发布了新的文献求助10
2秒前
3秒前
3秒前
3秒前
何噜噜噜关注了科研通微信公众号
4秒前
4秒前
最佳worker发布了新的文献求助10
4秒前
素心完成签到 ,获得积分10
5秒前
共享精神应助香香采纳,获得10
5秒前
6秒前
1234完成签到,获得积分20
6秒前
yangjiali发布了新的文献求助10
6秒前
6秒前
我爱学习发布了新的文献求助10
6秒前
7秒前
7秒前
Lkc发布了新的文献求助10
7秒前
7秒前
wang发布了新的文献求助10
7秒前
武广敏完成签到,获得积分10
7秒前
Lee发布了新的文献求助10
7秒前
科研通AI6.3应助现代早晨采纳,获得10
8秒前
seedcui完成签到,获得积分10
8秒前
sunday2024完成签到,获得积分10
8秒前
混世魔王完成签到,获得积分20
9秒前
cloud完成签到,获得积分10
9秒前
9秒前
1234发布了新的文献求助10
9秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Les Mantodea de guyane 2500
Feldspar inclusion dating of ceramics and burnt stones 1000
What is the Future of Psychotherapy in a Digital Age? 801
The Psychological Quest for Meaning 800
Digital and Social Media Marketing 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5969690
求助须知:如何正确求助?哪些是违规求助? 7274172
关于积分的说明 15984424
捐赠科研通 5107051
什么是DOI,文献DOI怎么找? 2742837
邀请新用户注册赠送积分活动 1707974
关于科研通互助平台的介绍 1621112