Article
Ecology
Oleg Askeyev, Arthur Askeyev, Igor Askeyev, Tim Sparks
Summary: The study aimed to investigate temperature drivers of spring phenology in boreal habitat in Russia over the period 1989-2020. The results showed that extreme temperatures in March 2020 led to record-breaking warm temperatures, leading to significant advances in some phenological events and identifying temperature thresholds for a majority of the events. Segmented regression models outperformed linear models in explaining the relationship between temperature and phenology, indicating the importance of temperature thresholds in boreal ecosystems.
GLOBAL ECOLOGY AND BIOGEOGRAPHY
(2022)
Article
Environmental Sciences
Wenxin Cai, Jinyan Tian, Xiaojuan Li, Lin Zhu, Beibei Chen
Summary: This study developed a new method for rapid and accurate mapping of winter wheat using a combination of multiple phenological spectral features (Mpsf) and a one-class support vector machine (OCSVM). The method has low cost and high accuracy, and produced one of the highest accuracy winter wheat-mapping products in Beijing.
Article
Agronomy
Zongpeng Li, Zhen Chen, Qian Cheng, Fuyi Duan, Ruixiu Sui, Xiuqiao Huang, Honggang Xu
Summary: This study used UAV hyperspectral remote sensing data and machine learning methods to predict winter wheat yields. By extracting spectral indices and performing feature selection, both basic learner models and an ensemble learner model were constructed. The results showed that the SVM yield prediction model performed the best among the base learner models, and the ensemble learner model had higher accuracy, especially at the grain-filling stage.
Article
Agronomy
Yu Zhao, Yang Meng, Shaoyu Han, Haikuan Feng, Guijun Yang, Zhenhai Li
Summary: In this study, a hierarchical linear model (HLM) was constructed to adapt the relationship between vegetation indices (VIs) and agronomic traits across multiple growing seasons. The model's performance was evaluated through sensitivity analysis. Results showed that optical VIs performed poorly in predicting above-ground biomass (AGB) and unit area nitrogen content (PNC), but performed well for leaf area index (LAI), species above-ground biomass (LGB), unit area nitrogen content (LNC), and chlorophyll index (SPAD). Sensitivity indices varied for different phenological information in the prediction models. The AGB and PNC prediction models considering phenological information were more accurate than the models based on VI.
Article
Agronomy
David J. Cann, James R. Hunt, Kenton D. Porker, Felicity A. J. Harris, Allan Rattey, Jessica Hyles
Summary: This study assessed the importance of diverse phenology for yield adaptation of winter wheat to environments with varied optimal flowering periods (OFPs). The results showed that quick and very quick developing winter wheat had broad adaptation to diverse OFPs, and phenology may be less important for adaptation to different OFP environments than previously thought.
EUROPEAN JOURNAL OF AGRONOMY
(2023)
Article
Multidisciplinary Sciences
Sarah C. Elmendorf, Robert D. Hollister
Summary: A modified growing degree day model with a maximum temperature threshold is the best predictor for the timing of flowering of many tundra plants. This finding explains why moderate temperature changes accompanied by larger changes in daily maximum temperatures result in less shifting of plant phenology than ambient warming.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Katharina Harfenmeister, Sibylle Itzerott, Cornelia Weltzien, Daniel Spengler
Summary: Monitoring the phenological development of winter wheat and winter barley using remote sensing features such as backscatter, polarimetric parameters, and NDVI shows sensitivity to specific stages. The approach demonstrates transferability across test sites and years, with differences mainly attributed to meteorological variations.
Article
Multidisciplinary Sciences
Amit Kumar Srivastava, Nima Safaei, Saeed Khaki, Gina Lopez, Wenzhi Zeng, Frank Ewert, Thomas Gaiser, Jaber Rahimi
Summary: This study analyzes the performance of machine learning and deep learning methods for winter wheat yield prediction, proposes a convolutional neural network model, and compares it with eight baseline models. The results show that nonlinear models are more effective in understanding the relationship between crop yield and input data, and the proposed CNN model outperforms all other baseline models in winter wheat yield prediction.
SCIENTIFIC REPORTS
(2022)
Article
Environmental Sciences
Petra Dizkova, Lenka Bartosova, Monika Blahova, Jan Balek, Lenka Hajkova, Daniela Semeradova, Jakub Bohuslav, Eva Pohankova, Zdenek Zalud, Miroslav Trnka
Summary: The phenological phases of field crops in recent decades in the Czech Republic have shifted earlier and shown correlations with temperatures from previous spring months. By using the PhenoClim thermal time model and satellite data, including the determination of start of the growing season (SOS), it is possible to refine the modeling of the onset of phenophases with greater accuracy.
Article
Plant Sciences
Fengyun Ma, Gina Brown-Guedira, Moonseok Kang, Byung-Kee Baik
Summary: This study characterized the genetic variation in phenology genes of eastern U.S. soft winter wheat and Korean winter wheat using molecular markers, finding that Ppd-D1 and Rht-D1 genes exhibited the highest genetic diversity and different genotypes influence heading date. Korean winter wheat headed earlier than eastern U.S. soft winter wheat largely due to its specific genotype combination.
Article
Agriculture, Multidisciplinary
Jiujiang Wu, Yue Wang, Hongzheng Shen, Yongqiang Wang, Xiaoyi Ma
Summary: This study utilized an autoregressive moving-average model to predict winter wheat maturity date, showing higher accuracy compared to traditional local empirical methods. The two-step filtering method based on future meteorological data performed the best on May 1st.
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2022)
Article
Plant Sciences
Gurjinder S. Baath, Vijaya Gopal Kakani, Brian K. Northup, Prasanna H. Gowda, Alexandre C. Rocateli, Hardeep Singh
Summary: Ambient temperatures play a crucial role in regulating the growth and yield of sesame, with the plant being more sensitive to low temperatures but tolerant of high temperatures. Sesame shows optimal biomass accumulation between 15.7-27.3 degrees Celsius, with reproductive yields declining above 25 degrees Celsius and no seed yields obtained beyond 33 degrees Celsius. The estimated temperature limits can be utilized to develop crop models for management and adaptation strategies of sesame under current and future climate scenarios.
JOURNAL OF PLANT GROWTH REGULATION
(2022)
Article
Geography, Physical
Lingling Fan, Jing Yang, Xiao Sun, Fen Zhao, Shefang Liang, Dingding Duan, Hao Chen, Lang Xia, Jing Sun, Peng Yang
Summary: Accurate winter wheat distribution is crucial for yield estimation and agricultural resources monitoring. This study evaluated the effects of a single acquisition date on winter wheat classification using multi-temporal Landsat 8 imagery. The results showed that the initial and late growth images were the most discriminating dates for time series classification of winter wheat.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Agronomy
Milan Mirosavljevic, Sanja Mikic, Vesna Zupunski, Ankica Kondic Spika, Dragana Trkulja, Carl-Otto Ottosen, Rong Zhou, Lamis Abdelhakim
Summary: The study found that heat stress affects wheat photosynthesis and yield, with different cultivars showing varying levels of tolerance to this stress. Heat stress has a greater impact on photosynthetic parameters and yield during grain filling.
JOURNAL OF AGRONOMY AND CROP SCIENCE
(2021)
Article
Meteorology & Atmospheric Sciences
Mayank Shekhar, Muskan Singh, Shaktiman Singh, Anshuman Bhardwaj, Rupesh Dhyani, Parminder S. Ranhotra, Lydia Sam, Amalava Bhattacharyya
Summary: The changing climate poses a significant threat to wheat yield and food security in the Gangetic Plain. Excessive precipitation and rising winter temperatures may delay wheat growth, while higher temperatures can potentially increase yield. Additionally, air temperature and sea surface temperature show a significant positive correlation with wheat yield in this region.
THEORETICAL AND APPLIED CLIMATOLOGY
(2022)
Article
Agriculture, Multidisciplinary
Siyi Li, Bin Wang, Puyu Feng, De Li Liu, Linchao Li, Lijie Shi, Qiang Yu
Summary: This study aims to develop an indicator-based method to assess the vulnerability of wheat yield and evaluate the climate vulnerability of the wheat belt in south-eastern Australia using long-term crop yield and climate data. The results show a decrease in climate vulnerability over the past few decades, mainly due to improvements in agronomic management practices, technology, and socio-economic progress.
AGRICULTURAL SYSTEMS
(2022)
Article
Agronomy
Yunfei Wang, Yufeng Zou, Huanjie Cai, Yijian Zeng, Jianqiang He, Lianyu Yu, Chao Zhang, Qaisar Saddique, Xiongbiao Peng, Kadambot H. M. Siddique, Qiang Yu, Zhongbo Su
Summary: The study found that evapotranspiration in the winter wheat and summer maize growing seasons in the Guanzhong Plain is influenced by multiple factors, with net radiation and surface conductance being the primary controlling factors. Surface conductance has a stronger impact on evapotranspiration in the summer maize growing season.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
Mingxi Zhang, Xihua Yang, Jamie Cleverly, Alfredo Huete, Hong Zhang, Qiang Yu
Summary: Under ongoing global warming, heat waves in Australia are predicted to increase in frequency and severity, causing devastating impacts on ecosystems. A toolkit called heat wave tracker (HWT) has been developed to analyze historical and projected heat waves in Australia, contributing to global research on heat waves under accelerated global warming.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Geosciences, Multidisciplinary
Kefan Chen, Liang Ning, Zhengyu Liu, Jian Liu, Mi Yan, Weiyi Sun, Linwang Yuan, Guonian Lv, Longhui Li, Chunhan Jin, Zhengguo Shi
Summary: Previous studies have shown that volcanic eruptions can have a nonlinear effect on drought events in Eastern China. Late-phase volcanic eruptions have a greater impact on drought persistence and intensity, while early-phase eruptions have weaker impacts. This is hypothesized to be related to the positive feedback between soil moisture and precipitation, as well as its interaction with the East Asia Summer Monsoon.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Geosciences, Multidisciplinary
Cong Wang, Jing Li, Qinhuo Liu, Alfredo Huete, Longhui Li, Yadong Dong, Jing Zhao
Summary: The study reveals that the El Nino-Southern Oscillation (ENSO) has diverse effects on vegetation in the west Pacific region, and different types of ENSO events lead to different vegetation anomalies, which are closely related to variations in precipitation and temperature.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Engineering, Civil
Qingyin Zhang, Xiaoxu Jia, Tongchuan Li, Mingan Shao, Qiang Yu, Xiaorong Wei
Summary: After excluding precipitation for two years, soil water storage deficit mainly occurred in the 0-1 m soil layer rather than in the 1-4 m layer. Excluding precipitation for two years resulted in an 18% decrease in soil water storage in the 0-1 m soil layer, as well as significant decreases in soil Ks, total porosity, and BD, along with a decrease in total soil OC concentration.
JOURNAL OF HYDROLOGY
(2022)
Article
Agronomy
Shang Chen, Liang He, Wenbiao Dong, Ruotong Li, Tengcong Jiang, Linchao Li, Hao Feng, Kuifeng Zhao, Qiang Yu, Jianqiang He
Summary: Within-season crop yield prediction using a dynamic crop model can provide valuable references for field management practices and regional food security. In this study, two strategies were established based on a five-year maize experiment in the Loess Plateau of China, and satisfactory predictions were obtained.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Agronomy
Shang Chen, Chuan He, Zhuo Huang, Xijuan Xu, Tengcong Jiang, Zhihao He, Jiandong Liu, Baofeng Su, Hao Feng, Qiang Yu, Jianqiang He
Summary: Accurate estimation of reference evapotranspiration is crucial for regional water resources planning and irrigation scheduling. This study provides two solutions for dealing with missing global solar radiation data in China mainland's ET0 estimation.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Agronomy
Zhihao He, Kaiyuan Gong, Zhiliang Zhang, Wenbiao Dong, Hao Feng, Qiang Yu, Jianqiang He
Summary: Research in China's Yellow River Basin has seen increasing interest and publications, with a focus on farming, water, soil, and environment. Key research topics have centered around the impacts of climate change and human activities on sediment, soil erosion and vegetation restoration, and the relationship between crops and environment in the Loess Plateau. Climate change and the Loess Plateau have gained significant attention in recent years.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Ecology
G. Cheng, R. D. Harmel, L. Ma, J. D. Derner, D. J. Augustine, P. N. S. Bartling, Q. X. Fang, J. R. Williams, C. J. Zilverberg, R. B. Boone, Q. Yu
Summary: This study improved the APEX model to better simulate cattle weight gain in real-world rangeland conditions. The research found that dry matter intake, total digestible nutrients, and temporal distribution of dry matter intake were the primary influencers of cattle performance. With the evaluation of various management alternatives, the APEX model can provide science-based rangeland decision support.
RANGELAND ECOLOGY & MANAGEMENT
(2022)
Article
Environmental Sciences
Zhunqiao Liu, Feng Zhao, Xinjie Liu, Qiang Yu, Yunfei Wang, Xiongbiao Peng, Huanjie Cai, Xiaoliang Lu
Summary: Progress has been made in predicting terrestrial gross primary productivity (GPP) from solar-induced chlorophyll fluorescence (SIF) using a process-based model that mechanistically links SIFTOC with vegetation photosynthetic activity. The model demonstrates good accuracy in quantifying canopy photosynthesis at both half-hourly and daily scales, enhancing our ability to estimate GPP with SIF at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Jiaqi Dong, Longhui Li, Yuzhen Li, Qiang Yu
Summary: This study compared the performance of eight satellite-based LUE-type GPP models in capturing the mean, temporal trend, and interannual variability of global GPP. The results showed differences in the estimated global mean GPP, variability, and trends among the models. Additionally, no consistent features were identified among the models based on plant functional types and climate classifications. Future studies should incorporate the latest mechanisms and environmental factors into models to better understand the evolutions of terrestrial ecosystem functioning.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Hongyan Cheng, Minshu Yuan, Liang Tang, Yufang Shen, Qiang Yu, Shiqing Li
Summary: Localized fertilization of phosphorus has potential benefits in achieving higher crop productivity and nutrient use efficiency. However, the underlying biological mechanisms of interactions between soil microorganisms and related metabolic cycle remain largely unknown. This study combined microbiology with non-target metabolomics to investigate the effects of P fertilizer levels and fertilization patterns on wheat soil microbial communities and metabolic functions. The results showed that P fertilizer decreased bacterial and fungal diversity, and significantly changed overall community structures and compositions. P levels and patterns also interfered with complexity of symbiosis networks.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Song Leng, Alfredo Huete, Jamie Cleverly, Qiang Yu, Rongrong Zhang, Qianfeng Wang
Summary: Accurate characterization of spatial patterns and temporal variations in dryland vegetation is crucial for understanding terrestrial ecosystem functioning in changing climates. Satellite observations of solar-induced chlorophyll fluorescence and enhanced vegetation index reveal the significant impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation. The greenness-based vegetation index can better capture the seasonal and interannual variation in vegetation production.
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.