Article
Agronomy
Apurba Kanti Choudhury, Md. Samim Hossain Molla, Taslima Zahan, Ranjit Sen, Jatish Chandra Biswas, Sohela Akhter, Sheikh Ishtiaque, Faruque Ahmed, Md. Maniruzaman, Md. Belal Hossain, Parimal Chandra Sarker, Eldessoky S. Dessoky, Mohamed M. Hassan, Akbar Hossain
Summary: The study identified the optimal sowing window for maize in the northern region of Bangladesh (Rangpur) to be from November 5 to December 5, and from November 20 to December 5 in the western region (Jashore). Utilizing the CERES-Maize model, the research was able to accurately forecast maize yields, providing important insights for future sowing strategies and yield predictions.
Article
Agronomy
Simona Bassu, Davide Fumagalli, Andrea Toreti, Andrej Ceglar, Francesco Giunta, Rosella Motzo, Zuzanna Zajac, Stefan Niemeyer
Summary: Understanding and modeling the effects of sowing date and cultivar on maize yield is crucial for developing climate change adaptation strategies. Testing different models against observed data in a Mediterranean environment showed that future climate conditions may lead to lower maize yields, even with changes in phenology and sowing dates.
FIELD CROPS RESEARCH
(2021)
Article
Agriculture, Multidisciplinary
Shengchao Qiao, Sandy P. Harrison, I. Colin Prentice, Han Wang
Summary: This study develops a model that predicts the choice of wheat types and sowing dates based on climate conditions. The model is evaluated and used to predict future changes in sowing dates under different climate scenarios. The findings provide insights into the impacts of climate change on crop calendars.
AGRICULTURAL SYSTEMS
(2023)
Article
Agriculture, Multidisciplinary
Muhammad Kashif Mubarik, Khadim Hussain, Ghulam Abbas, Muhammad Tanveer Altaf, Faheem Shahzad Baloch, Shakeel Ahmad
Summary: Determining the optimal sowing date, irrigation frequency, and cultivar is crucial for achieving maximum sorghum yield in semiarid and arid environments. This study found that the sowing date, irrigation regime, and cultivar significantly affected sorghum growth and yield.
TURKISH JOURNAL OF AGRICULTURE AND FORESTRY
(2022)
Article
Agronomy
Zemin Zhang, Changhe Lu
Summary: In recent years, there has been a decline in China's crop production growth rate, leading to concerns over whether grain yields have reached their potential. A study conducted in the North China Plain (NCP) used the WOFOST model to simulate the potential yield of irrigated maize crops. The study found that the average potential yield in the region decreased by 37.6 kg ha(-1) per year from 1960 to 2017, with an annual maize yield gap of 29.0%-51.3% during 1998-2017 in the NCP.
FOOD AND ENERGY SECURITY
(2023)
Article
Meteorology & Atmospheric Sciences
Zhiqiang Dong, Xiaoping Xue, Zhihua Pan
Summary: This study assesses the vulnerability of winter wheat and summer maize production in Shandong Province to climate change. The results indicate that the vulnerability of these crops will increase in the future, particularly in the Jiaozhou peninsula and northwestern Shandong.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Environmental Sciences
Sha Zhang, Yun Bai, Jiahua Zhang
Summary: This study developed a new method to estimate the yield potential and quantify the contribution of suboptimum field managements to the yield gap of summer maize in North China Plain using a remote sensing vegetation index time series. The results showed that the new method provided reasonable estimates for maize yield on a regional scale and highlighted the importance of accurate field management information for improving crop yield effectively.
Article
Agronomy
Ziang Xie, Jiying Kong, Min Tang, Zhenhai Luo, Duo Li, Rui Liu, Shaoyuan Feng, Chao Zhang
Summary: The sowing date and density are important factors affecting crop yield, but their determination is uncertain due to various factors. This study aimed to evaluate the performance of the AquaCrop model for winter rapeseed development and yield simulation under different sowing dates and densities. The results showed that the model had better capability in interpreting crop development for different sowing dates compared to sowing densities. The study provides insights into optimizing rapeseed sowing patterns for high-efficient production.
Article
Environmental Sciences
Matteo Rolle, Stefania Tamea, Pierluigi Claps, Emna Ayari, Nicolas Baghdadi, Mehrez Zribi
Summary: This study presents an estimation of maize actual sowing periods for the year 2019 by combining optical and radar information from Sentinel-1 and Sentinel-2. The use of NDVI and radar time series enabled a high-resolution assessment of sowing periods and the description of maize emergence through the soil.
Article
Green & Sustainable Science & Technology
Jiandong Liu, Jun Du, De-Li Liu, Hans W. Linderholm, Guangsheng Zhou, Yanling Song, Yanbo Shen, Qiang Yu
Summary: This study explores a suitable strategy for simulating potential yields of highland barley using the WOFOST crop growth model, and analyzes the variations in climate conditions and potential yields in the Three Rivers Region from 1961 to 2020. The results suggest that the decrease in global radiation and the increase in temperature during growth periods are the main factors contributing to the decrease in potential yields. It is recommended to cultivate new varieties with longer growth periods to adapt to climate change.
Article
Agriculture, Multidisciplinary
R. J. Hall, H. -L. Wei, S. Pearson, Y. Ma, S. Fang, E. Hanna
Summary: This research presents a new approach, known as NARMAX, to model wheat yield. The results show that this method outperforms other models in terms of prediction accuracy and model interpretability. In addition, regional wheat yield forecasts are developed based on a new gridded meteorological data product. This method can be extended to other crop types and locations and is important for understanding the environmental drivers of wheat yield.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Agronomy
Jin Zhao, Zhijuan Liu, Shuo Lv, Xiaomao Lin, Tao Li, Xiaoguang Yang
Summary: By integrating various data and models, this study found that adopting newly-bred maize hybrids can increase maize yield in Northeast China, especially under climate change trends. This study provides important insights for adapting crop production to climate change.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Agriculture, Multidisciplinary
Maria Eliza Turek, Quirijn De Jong van Lier, Robson Andre Armindo
Summary: This study aimed to calibrate the field capacity (FC) value in the bucket-type model WOFOST in order to best simulate the water balance predicted by the Richards equation-based model SWAP, considered as a benchmark. The calibrated FC value depended on various factors such as targets, soil type, climate, and crop drought sensitivity.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Green & Sustainable Science & Technology
Xiaoyu Tian, Bernie A. Engel, Haiyang Qian, En Hua, Shikun Sun, Yubao Wang
Summary: Global food demand is projected to maintain a steady growth rate over the next 30 years, while the growth rate of crop production is expected to gradually slow down. The yield of main food crops may stagnate in some countries. To achieve a balance between food supply and demand, adjustments to diet structure and reduction of food waste are needed, as well as clarifying potential for increasing global food production through measures such as increasing irrigated area and improving efficiency of water and fertilizer use.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Meteorology & Atmospheric Sciences
Xiaomeng Yin, Guoyong Leng
Summary: The study compared the impacts of climate variability and trends on global maize yield between 1980 and 2010 using both statistical and process-based models. The results showed large discrepancies between the models, highlighting the importance of considering different modeling approaches in projecting future crop yields under climate change.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2021)
Article
Agronomy
Wenyi Xu, Bo Elberling, Per Lennart Ambus
Summary: The frequency and extent of wildfires in the Arctic have been increasing due to climate change. In this study, researchers conducted experiments in West Greenland to investigate the long-term impacts of climate warming on post-fire carbon dioxide exchange in arctic tundra ecosystems. They found that fire increased soil organic phosphorus concentrations and burned areas remained a net CO2 source five years after the fire. However, with four to five years of summer warming, the burned areas turned into a net CO2 sink.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yuanhang Yang, Jiabo Yin, Shengyu Kang, Louise J. Slater, Xihui Gu, Aliaksandr Volchak
Summary: This study investigates the impacts of water and heat stress on carbon uptake in China and explores the driving mechanisms of droughts using a machine learning model. The results show that droughts are mostly driven by atmospheric dryness, with precipitation, relative humidity, and temperature playing dominant roles. Water and heat stress have negative impacts on carbon assimilation, and drought occurrence is projected to increase significantly in the future. Improving ecosystem resilience to climate warming is crucial in mitigating the negative effects of droughts on carbon uptake.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ningbo Cui, Shunsheng Zheng, Shouzheng Jiang, Mingjun Wang, Lu Zhao, Ziling He, Yu Feng, Yaosheng Wang, Daozhi Gong, Chunwei Liu, Rangjian Qiu
Summary: This study proposes a method to partition evapotranspiration (ET) into its components in agroforestry systems. The method is based on water-carbon coupling theory and flux conservation hypothesis. The results show that the partitioned components agree well with measurements from other sensors. The study also finds that atmospheric evaporation demand and vegetation factors greatly influence the components of ET, and increased tree leaf area limits understory grass transpiration.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xinhao Li, Tianshan Zha, Andrew Black, Xin Jia, Rachhpal S. Jassal, Peng Liu, Yun Tian, Chuan Jin, Ruizhi Yang, Feng Zhang, Haiqun Yu, Jing Xie
Summary: With the rapid increase of urbanization, evapotranspiration (ET) in urban forests has become increasingly important in urban hydrology and climate. However, there is still a large uncertainty regarding the factors that regulate ET in urban areas. This study investigates the temporal variations of ET in an urban forest park in Beijing using the eddy-covariance technique. The results show that daily ET is close to zero during winter but reaches 3-6 mm day-1 in summer. Daily ET increases with vapor pressure deficit (VPD) and soil water content (SWC). Monthly ET increases linearly with normalized difference vegetation index and shows a strong correlation with surface conductance (gs), while exhibiting saturated responses to increasing monthly precipitation (PPT). Annual ET ranges from 326 to 566 mm, and soil water replenishment through PPT from the previous year is responsible for the generally higher monthly ET in spring relative to PPT. Biotic factors and PPT seasonality play essential roles in regulating ET at different scales.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Zhaogang Liu, Zhi Chen, Meng Yang, Tianxiang Hao, Guirui Yu, Xianjin Zhu, Weikang Zhang, Lexin Ma, Xiaojun Dou, Yong Lin, Wenxing Luo, Lang Han, Mingyu Sun, Shiping Chen, Gang Dong, Yanhong Gao, Yanbin Hao, Shicheng Jiang, Yingnian Li, Yuzhe Li, Shaomin Liu, Peili Shi, Junlei Tan, Yakun Tang, Xiaoping Xin, Fawei Zhang, Yangjian Zhang, Liang Zhao, Li Zhou, Zhilin Zhu
Summary: This study investigates the responses of temperate grassland (TG) and alpine grassland (AG) to climate change by studying carbon (C) fluxes across different regions in China. The results reveal that water factors consistently increase C fluxes, while temperature factors have opposite effects on TG and AG. The study enhances our understanding of C sinks and grassland sensitivity to climate change.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Peng Li, Huijie Li, Bingcheng Si, Tao Zhou, Chunhua Zhang, Min Li
Summary: This study mapped the distribution of forest age on the Chinese Loess Plateau using the LandTrendr algorithm. The results show that the LT algorithm is a convenient, efficient, and reliable method for identifying forest age. The findings have important implications for assessing and quantifying biomass and carbon sequestration in afforestation efforts on the Chinese Loess Plateau.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Review
Agronomy
Yean-Uk Kim, Heidi Webber, Samuel G. K. Adiku, Rogerio de S. Noia Junior, Jean-Charles Deswarte, Senthold Asseng, Frank Ewert
Summary: As climate change is expected to increase the intensity and frequency of extreme weather events, it is crucial to assess their impact on cropping systems and explore adaptation options. Process-based crop models (PBCMs) have improved in simulating the impacts of major extreme weather events, but still struggle to reproduce low crop yields under wet conditions. This article provides an overview of the yield-loss mechanisms of excessive rainfall in cereals and the associated modelling approaches, aiming to guide improvements in PBCMs.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Xiaodong Liu, Yingjie Feng, Xinyu Zhao, Zijie Cui, Peiling Liu, Xiuzhi Chen, Qianmei Zhang, Juxiu Liu
Summary: Understanding the impact of climate on litterfall production is crucial for simulating nutrient cycling in forest ecosystems. This study analyzed a 14-year litterfall dataset from two subtropical forests in South China and found that litterfall was mainly influenced by wind speed during the wet season and by temperature during the dry season. These findings have potential significance in improving our understanding of carbon and nutrient cycling in subtropical forest ecosystems under climate change conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Ruonan Chen, Liangyun Liu, Zhunqiao Liu, Xinjie Liu, Jongmin Kim, Hyun Seok Kim, Hojin Lee, Genghong Wu, Chenhui Guo, Lianhong Gu
Summary: Solar-induced chlorophyll fluorescence (SIF) has the potential to estimate gross primary production (GPP), but the quantitative relationship between them is not constant. In this study, a mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) was developed, considering the seasonal variation in a key parameter of the model. The GPP estimates from this model were more accurate compared to other benchmark models, especially in extreme conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jingyi Zhu, Yanzheng Yang, Nan Meng, Ruonan Li, Jinfeng Ma, Hua Zheng
Summary: This study developed a random forest model using climate station and satellite data to generate high-precision precipitation datasets for the Qinghai-Tibet Plateau. By incorporating multisource satellite data, the model achieved a significant enhancement in precipitation accuracy and showed promising results in regions with limited meteorological stations and substantial spatial heterogeneity in precipitation patterns.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Yulin Yan, Youngryel Ryu, Bolun Li, Benjamin Dechant, Sheir Afgen Zaheer, Minseok Kang
Summary: Sustainable rice farming practices are urgently needed to meet increasing food demand, cope with water scarcity, and mitigate climate change. Traditional farming methods that prioritize a single objective have proven to be insufficient, while simultaneously optimizing multiple competing objectives remains less explored. This study optimized farm management to increase rice yield, reduce irrigation water consumption, and tackle the dilemma of reducing GHG emissions. The results suggest that the optimized management can maintain or even increase crop yield, while reducing water demand and GHG emissions by more than 50%.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Sasha D. Hafner, Jesper N. Kamp, Johanna Pedersen
Summary: This study compared micrometeorological and wind tunnel measurements using a semi-empirical model to understand wind tunnel measurement error. The results showed differences in emission estimates between the two methods, but the ALFAM2 model was able to reproduce emission dynamics for both methods when considering differences in mass transfer. The study provides a template for integrating and comparing measurements from different methods, suggesting the use of wind tunnel measurements for model evaluation and parameter estimation.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Wenfang Xu, Wenping Yuan, Donghai Wu, Yao Zhang, Ruoque Shen, Xiaosheng Xia, Philippe Ciais, Juxiu Liu
Summary: In the summer of 2022, China experienced record-breaking heatwaves and droughts, which had a significant impact on plant growth. The study also found that heatwaves were more critical than droughts in limiting vegetation growth.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Jiaqi Guo, Xiaohong Liu, Wensen Ge, Liangju Zhao, Wenjie Fan, Xinyu Zhang, Qiangqiang Lu, Xiaoyu Xing, Zihan Zhou
Summary: Vegetation photosynthetic phenology is an important indicator for understanding the impacts of climate change on terrestrial carbon cycle. This study evaluated and compared the abilities of different spectral indices to model photosynthetic phenology, and found that NIRv and PRI are effective proxies for monitoring photosynthetic phenology.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
Article
Agronomy
Arango Ruda Elizabeth, M. Altaf Arain
Summary: Temperate deciduous forests have significant impacts on regional and global water cycles. This study examined the effects of climate change and extreme weather events on the water use and evapotranspiration of a temperate deciduous forest in eastern North America. The results showed that photosynthetically active radiation and air temperature were the primary drivers of evapotranspiration, while vapor pressure deficit regulated water use efficiency. The study also found a changing trend in water use efficiency over the years, influenced by extreme weather conditions.
AGRICULTURAL AND FOREST METEOROLOGY
(2024)
