Crop plant height is a critical parameter for assessing crop physiological properties, such as above-ground biomass and grain yield and crop health. Current dominant plant height estimation methods are based on digital surface model (DSM) and vegetation indexes (VIs). However, DSM-based methods usually estimate plant height by growth stages, which would result in some discontinuity between growth stages due to different fitting curves. Additionally, there has been limited research on the application of VI-based plant height estimation for multiple crop species. Thus, this study investigated the validity and challenges associated with these methods for estimating canopy heights of multi-variety rice throughout the entire growing season. A total of 474 rice varieties were cultivated in a single season, and RGB images including red, green, and blue bands, DSMs, multispectral images including near infrared and red edge bands, and manually measured plant heights were collected in 2022. DSMs and 26 commonly used VIs were employed to estimate rice canopy heights during the growing season. The plant height estimation using DSMs was performed using different quantiles (50th, 75th, and 95th), while two-stage linear regression (TLR) models based on each VI were developed. The DSM-based method at the 95th quantile showed high accuracy, with an R² value of 0.94 and an RMSE value of 0.06 m. However, the plant height estimation at the early growth stage showed lower effectiveness, with an R² < 0. For the VIs, height estimation with MTCI yielded the best results, with an R² of 0.704. The first stage of the TLR model (maximum R² = 0.664) was significantly better than the second stage (maximum R² = 0.133), which indicated that the VIs were more suitable for estimating canopy height at the early growth stage. By grouping the 474 varieties into 15 clusters, the R² values of the VI-based TLR models exhibited inconsistencies across clusters (maximum R² = 0.984; minimum R² = 0.042), which meant that the VIs were suitable for estimating canopy height in the cultivation of similar or specific rice varieties. However, the DSM-based method showed little difference in performance among the varieties, which meant that the DSM-based method was suitable for multi-variety rice breeding. But for specific clusters, the VI-based methods were better than the DSM-based methods for plant height estimation. In conclusion, the DSM-based method at the 95th quantile was suitable for plant height estimation in the multi-variety rice breeding process, and we recommend using DSMs for plant height estimation after 26 DAT. Furthermore, the MTCI-based TLR model was suitable for plant height estimation in monoculture planting or as a correction for DSM-based plant height estimation in the pre-growth period of rice.

Observations of the effects of long-term paddy-upland rotations on soil carbon (C) and nitrogen (N) stocks are scarce. This experiment aimed to examine soil C and N stock characteristics and their relationships with rice yield using four long-term rotation systems. The results showed that in the topsoil at 50 cm, compared to rice-fallow (RF), rice-potato with rice straw mulch and return (RP) and rice-Chinese milk vetch (RC) increased soil organic carbon (SOC) stock by 19.67% and 15.29%, total nitrogen (TN) stock by 20.40% and 18.54%, and available nitrogen (AN) density by 61.54% and 34.44%, respectively; while rice-wheat (RW) increased AN density by 30.24%. Furthermore, the increases in densities of soil C and N at 20–30 cm were likely to increase rice above biomass and yield. The highest soil C and N densities were observed in RP, which was the best choice for increasing soil nutrients and rice yield. In addition, SOC, TN, and AN had obvious stratification and surface aggregation characteristics, and more than 70% of the total stocks were concentrated at the top 30 cm. These results provide a theoretical basis for the high-yield cultivation of rice in the middle and lower reaches of the Yangtze River.

Mid−season drainage (MSD) is a widely used water management practice in rice (Oryza sativa L.) cultivation. However, the timing of the initiation and termination of MSD is highly arbitrary and subjective, and a quantitative indicator is lacking in precision agronomic practice. In this study, datasets (91 cases) from previous field experiments were obtained and used to fit adjusted exponential growth models, incorporating rice canopy light interception (CLI) and tillering development dynamics. Different criteria for initiating and terminating MSD were developed based on CLI indicators. The results showed that the CLI indicator at 80% of the projected panicle could be used to predict the initiation of MSD; however, it was highly variable, depending on the growing season and rice cultivated variety. The values for Indica rice were 0.26 to 0.31 and 0.31 to 0.42 in the late and single seasons, respectively, while the values for Japonica rice were 0.15 to 0.29 and 0.23 to 0.33, respectively. In addition, the CLI values at 7 to 10 days prior to panicle initiation (PI) ranged from 0.77 to 0.87 and from 0.56 to 0.83 for the Indica and Japonica varieties, respectively, and were calculated to determine MSD termination. The CLI indicators for MSD were greatly dependent on the cultivated variety, growing season, and planting method. The results of the correlation study and principal component analysis (PCA) indicated that the differences in CLI values attributed to rice type and growing season were driven by the tillering and canopy characteristic traits, respectively. Therefore, the current parameters could provide a reference for subsequent field applications in specific areas, but further optimization is needed to increase their robustness. To evaluate the usefulness of the CLI indicator for determining MSD initiation and termination, a set of devices for monitoring canopy light interception and water level was developed, and an on-farm trial was carried out in the middle and lower reaches of the Yangtze River in China in 2022. The field application demonstrated that MSD could be scheduled automatically based on the current system, and that the effect was consistent in practice.