## 1 Introduction  
The dynamics of periodic events in plants, known as plant phenology, reflect the responses of the terrestrial biosphere to climate change [1; 2; 3; 4]. As the specific part of plant phenology, the agricultural crop growth stages function as more sensitive and integrated indicators of the agricultural ecosystem to environmental conditions [5; 6]. In addition, as the physiological signals responding to the growing conditions, crop growth stages could determine the biophysical structure of the crop and its photosynthesis intensity, evapotranspiration rate and light use efficiency [7; 8]. For example, drought stress during the silking stage of maize could cause a 3-8% loss to its yield, while, for soybeans during the setting pods stage, the reduced number of pods may be 20% [9; 10]. That explains the reason why the yield loss of maize and soybean are particularly sensitive to the water condition during the silking stage and the setting pods stage, respectively [11; 12]. For the same reason, these two growing stages have been also seen as the critical irrigation window of these two crops [12; 13]. Hence, the agricultural crop growth stages could build a critical link between environmental conditions and the physiological growth of crops, and contribute to crop yield estimation, precise crop management and decision making. The solar-induced chlorophyll fluorescence (SIF) is the signal emitted by the chlorophyll-a molecules in vegetation when they absorb photosynthetically active radiation during photosynthesis. This signal, which falls within the spectrum of 650 nm to 800 nm, is a valuable indicator of various plant phenophases [14]. As a by-product of photosynthesis, SIF has been proven to be strongly related with the gross primary production (GPP) of vegetation for different ecosystems [15; 16; 17; 18]. In addition to its role in monitoring photosynthesis, SIF also provides valuable insights into the biophysical structure of plants [19; 20; 21]. Due to its advantages over traditional vegetation indices (VIs), SIF data has become increasingly popular for monitoring plant growth conditions [15; 22; 23]. Over the past decade, SIF data has been retrieved globally from various satellite missions, including GOSAT (Greenhouse gases Observing SATellite) [15; 16; 22], GOME-2 (The Global Ozone Monitoring Experiment-2) [24; 25], SCIAMACHY [25; 26], OCO-2 (Orbiting Carbon Observatory-2) [27], TROPOMI (TRPOPSheric Monitoring Instrument) [28] and Tansat [29; 30]. These missions have paved the way for regional-scale crop growth condition monitoring using SIF data. Advancements in remote sensing technology have opened new avenues for understanding plant phenology, offering valuable insights into crop growth and its response to environmental factors [31; 32; 33; 34; 35]. Phenological estimation utilizing remote sensing time series data typically involves several key steps. Initially, the data undergo compositing and filtering to mitigate cloud contamination, viewing geometry issues, and atmospheric interference [36; 37]. Subsequently, phenological models such as smoothing spline functions, double logistic functions, and asymmetric Gaussian functions are employed to fit the signal curve throughout the growing season [31; 38; 39]. Finally, phenological transition dates are extracted from the fitted phenological curve with various methods [40; 41; 42]. Despite the progress made in utilizing remote sensing data for the crop phenology estimation, several challenges persist. Firstly, there is a discrepancy between phenological transition dates, such as the start of the season, and crop growth stages like the silking stage of maize and heading stage of winter wheat, creating a temporal gap [5; 42]. Secondly, many studies on crop phenology estimation are constrained within the broader framework of plant phenology, focusing primarily on the start, peak, and end of the growing season [43; 44; 45]. This limitation hinders the alignment of phenological estimations with actual crop growth stage observations in agronomy.