Evaluation of Three Portable Optical Sensors for Non-Destructive Diagnosis of Nitrogen Status in Winter Wheat.

The accurate estimation and timely diagnosis of crop nitrogen (N) status can facilitate in-season fertilizer management. In order to evaluate the performance of three leaf and canopy optical sensors in non-destructively diagnosing winter wheat N status, three experiments using seven wheat cultivars and multi-N-treatments (0-360 kg N ha-1) were conducted in the Jiangsu province of China from 2015 to 2018. Two leaf sensors (SPAD 502, Dualex 4 Scientific+) and one canopy sensor (RapidSCAN CS-45) were used to obtain leaf and canopy spectral data, respectively, during the main growth period. Five N indicators (leaf N concentration (LNC), leaf N accumulation (LNA), plant N concentration (PNC), plant N accumulation (PNA), and N nutrition index (NNI)) were measured synchronously. The relationships between the six sensor-based indices (leaf level: SPAD, Chl, Flav, NBI, canopy level: NDRE, NDVI) and five N parameters were established at each growth stages. The results showed that the Dualex-based NBI performed relatively well among four leaf-sensor indices, while NDRE of RS sensor achieved a best performance due to larger sampling area of canopy sensor for five N indicators estimation across different growth stages. The areal agreement of the NNI diagnosis models ranged from 0.54 to 0.71 for SPAD, 0.66 to 0.84 for NBI, and 0.72 to 0.86 for NDRE, and the kappa coefficient ranged from 0.30 to 0.52 for SPAD, 0.42 to 0.72 for NBI, and 0.53 to 0.75 for NDRE across all growth stages. Overall, these results reveal the potential of sensor-based diagnosis models for the rapid and non-destructive diagnosis of N status.

Improving the spatial and temporal estimation of ecosystem respiration using multi-source data and machine learning methods in a rainfed winter wheat cropland.

The investigation of ecosystem respiration (RE) and its vital influential factors along with the timely and accurate detection of spatiotemporal variations in RE are essential for guiding agricultural production planning. RE observation in the plot region is primarily based on the laborious chamber method. However, upscaling the spatial-temporal estimates of RE at the canopy scale is still challenging. The present study conducted a field experiment to determine RE using the chamber method. A multi-rotor unmanned aerial vehicle (UAV) equipped with a multispectral camera was employed to acquire the canopy spectral data of wheat during each RE test experiment. Moreover, the agronomic indicators of aboveground plant biomass, leaf area index, leaf dry mass as well as agrometeorological and soil data were measured simultaneously. The study analyzed the potential of multi-information for estimating RE at the field scale and proposed two strategies for RE estimation. In addition, a semiempirical, yet Lloyd and Taylor-based, remote sensing model (LT1-NIRV) was developed for estimating RE observed across different growth stages with a small margin of error (coefficient of determination [R2] = 0.60-0.64, root-mean-square error [RMSE] = 285.98-316.19 mg m-2 h-1). Further, five machine learning (ML) algorithms were utilized to independently estimate RE using two different datasets. The rigorous analyses, which included statistical comparison and cross-validation for estimating RE, confirmed that the XGBoost model, with the highest R2 and lowest RMSE (R2 = 0.88 and RMSE = 172.70 mg m-2 h-1), performed the best among the evaluated ML models. The LT1-NIRV model was less effective in estimating RE compared with the other ML models. Based on this comprehensive comparison analysis, the ML model can successfully estimate variations in wheat field RE using high-resolution UAV multispectral images and environmental factors from the wheat cropland system, thereby providing a valuable reference for monitoring and upscaling RE observations.

Potential of Establishing the Universal Critical Nitrogen Dilution Curve for Japonica Rice.

Establishing the universal critical nitrogen (NC) dilution curve can assist in crop N diagnosis at the regional scale. This study conducted 10-year N fertilizer experiments in Yangtze River Reaches to establish universal NC dilution curves for Japonica rice based on simple data-mixing (SDM), random forest algorithm (RFA), and Bayesian hierarchical model (BHM), respectively. Results showed that parameters a and b were affected by the genetic and environmental conditions. Based on RFA, highly related factors of a (plant height, specific leaf area at tillering end, and maximum dry matter weight during vegetative growth period) and b (accumulated growing degree days at tillering end, stem-leaf ratio at tillering end, and maximum leaf area index during vegetative growth period) were successfully applied to establish the universal curve. In addition, representative values (most probable number [MPN]) were selected from posterior distributions obtained by the BHM approach to explore universal parameters a and b. The universal curves established by SDM, RFA, and BHM-MPN were verified to have a strong N diagnostic capacity (N nutrition index validation R 2 ≥ 0.81). In summary, compared with the SDM approach, RFA and BHM-MPN can greatly simplify the modeling process (e.g., defining N-limiting or non-N-limiting groups) while maintaining a good accuracy, which are more conducive to the application and promotion at the regional scale.

[Clinical application of sural neurocutaneous island flaps].

OBJECTIVE: To explore the clinical application characteristics of sural neurocutaneous island flaps. METHODS: Sural neurocutaneous island flaps were used to repair the skin defect accompanied bone and tendon exposure in the lower leg, around the ankle and foot in 21 cases, including 4 cases to repair the foreside of the foot back . Direct flap was used in 5 cases and reverse flap in 16 cases. Meanwhile the coverage and formation of sural nerve were surveyed together with the starting point of peroneal perforator. RESULTS: All the 21 sural flaps were survived, including sural nerve (18 cases) anastomose 12 cases, single trunk 4 cases, double trunk 2 cases. The anastomose site of medial sural cutaneous nerve and the communicating branch of lateral sural cutaneous nerve was at the point of 11 - 14 cm above the ankle in 12 cases. The lower was the anastomose site, the shorter was the sural nerve. The site is 4 - 7 cm above the ankle in 15 out of 18 sural nerve perforator branch cases, and the other 3 cases is 10, 11, 11.5 cm above the ankle respectively. CONCLUSIONS: Sural neurocutaneous island flaps are easy to separate. Major arteries are not injured. It is the ideal flap to repair the skin defect accompanied by bone and tendon exposure in lower leg, around ankle and foot. The nerve must be anastomosed when repairing the heel.

[The expanded cross-leg flap for repairing the soft tissue defects of the instep].

OBJECTIVE: To explore the clinical application of the expanded cross-leg flap for repairing instep soft tissue defects with bone exposure. METHODS: The expanded cross-leg flap was used to repair instep defects in 10 patients. After flap transferring the donor site was closed directly without skin grafting. RESULTS: Satisfactory results were achieved in all the cases. The flaps survived well. The donor site had less scar and kept good appearance. CONCLUSIONS: The expanded cross-leg flap is a better choice for repairing the soft tissue defects of the instep. It is simple and easy with less trauma to the donor site. After the operation, both the recipient and the donor areas had good appearance.