Tao Zhong

Dr. Tao Zhong


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 October 2024 in Atmosphere
Verified
Journal Article
Open access
PDF file
Yifan LiYifan Li
Yifan Li
HZHong Zhao
Hong Zhao
TZTao Zhong
Tao Zhong
HWHaibing Wu
Haibing Wu
WPWenhong Peng
Wenhong Peng
YLYu Li
Yu Li
In response to climate change challenges and to ensure stable macadamia nut production, this study analyzed empirical data on macadamia nut yield, climate factors, harvesting time, and post-processing quality from 2020 to 2022. Key findings include: (1) During the flowering to fruit growth stage, 2020 had the highest average temperature, followed by 2021, and then 2022. Conversely, 2022 had the highest precipitation, followed by 2021, and then 2020. (2) Lower temperatures and higher precipitation during the flowering to fruit growth stage contributed to a significant increase in macadamia nut yield, which indirectly extended the harvesting time. In 2022, the average yield of the eight macadamia growers was 8.04 t ha−1, significantly higher than the yields of 6.60 t ha−1 and 6.16 t ha−1 in 2021 and 2020, respectively. Furthermore, the average harvesting time for the eight macadamia growers in 2022 was 8.88 days longer than that in 2021, and 12.50 days longer than that in 2020. (3) Temperature and precipitation had a significant impact on the post-processing quality of macadamia nuts. Lower temperature and higher precipitation during the flowering to fruit growth stage significantly increased the proportion of first-grade fruit, as well as the incidence of mildewed and insect-infested fruits. In conclusion, although a lower temperature and higher precipitation can improve macadamia nut yield, they also lead to delayed harvesting and decreased post-processing quality. Given the observed yield sensitivity to temperature and precipitation, targeted water supplementation strategies during peak heat periods emerge as vital. This approach should be integrated with broader climate resilience planning, including the timing of pest control and disease management, to safeguard macadamia nut production against the multifaceted challenges posed by climate change.

28 October 2026 in Agriculture
Verified
Journal Article
Open access
PDF file
Yifan LiYifan Li
Yifan Li
XWxie weiguo
xie weiguo
HZHong Zhao
Hong Zhao
HWHaibin Wu
Haibin Wu
XGXiaojun Gao
Xiaojun Gao
HMHongjun Mu
Hongjun Mu
Macadamia cultivation has expanded rapidly across diverse agro-ecological zones, but knowledge of cultivar–environment matching remains fragmented across disciplines, hindering the development of evidence-based zoning and management strategies. This review aims to synthesize multidisciplinary evidence into a coherent framework for understanding and managing cultivar–environment (C × E) interactions. We integrate findings from reproductive physiology, ecophysiology, horticulture, and regional agronomy, drawing on evidence from China’s three major production regions (Yunnan, Guangxi, and Guizhou), which represent a broad climatic gradient from dry-season water deficits to warm humid conditions and low-temperature valley stress. Our synthesis yields four principles: (i) Temperature and water regulate reproductive development through stage-specific thresholds. (ii) Cultivars differ markedly in heat requirement, cold tolerance, drought response, and self-compatibility. (iii) Cross-regional comparisons show that yield and kernel quality of identical cultivars vary substantially across provinces. (iv) Adaptive management practices, including high-density planting, sod culture, fertigation, and trunk infusion, can compensate for specific C × E mismatches. These findings are synthesized into a conceptual model linking environmental drivers, phenological windows, physiological thresholds, and management interventions. We identify three research priorities, namely, molecular dissection of adaptive traits, phenological-stage-aware predictive modeling, and standardized multi-location evaluation networks, as essential for supporting climate-resilient cultivar zoning and orchard management.