Fucang Zhang

To address the insufficient characterization of vertical heterogeneity in potato canopy leaf nitrogen content (LNC), this study developed a layer-specific LNC estimation framework based on canopy hyperspectral reflectance, fractional-order derivative (FOD) transformation, and two-band and three-band optimized spectral indices. Partial least squares regression (PLSR) was then used to evaluate the predictive ability of the selected spectral indices for Top, Middle, and Bottom LNC. Field experiments were conducted from 2022 to 2023 in the semi-arid region of Yulin, Shaanxi Province, China. Canopy hyperspectral reflectance from 350 to 1830 nm and LNC measurements of upper (Top), middle (Middle), and lower (Bottom) leaves were synchronously acquired during the tuber formation stage. The results showed that potato canopy LNC exhibited a clear vertical gradient, following the order Top LNC > Middle LNC > Bottom LNC. Traditional vegetation indices were significantly correlated with LNC, but their correlations decreased with increasing canopy depth, with the highest correlation for Bottom LNC being only 0.524. Compared with traditional vegetation indices, FOD-based two-band indices showed stronger Pearson correlations with layer-specific LNC. Under FOD1.5, the maximum absolute Pearson correlation coefficients (|r|) between the selected two-band indices and LNC reached 0.855, 0.849, and 0.814 for Top, Middle, and Bottom LNC, respectively. The three-band optimized spectral indices further enhanced spectral information extraction, with maximum |r| values of 0.893, 0.885, and 0.852, respectively. However, cross-year validation produced substantially lower R² values, indicating limited temporal transferability of the selected indices and the need for further validation before broader application. Compared with the traditional vegetation index model, it increased the testing-set R² for Bottom LNC by 0.279 and reduced RMSE from 0.159 to 0.113. These results suggest that FOD1.5-integrated three-band optimized spectral indices can improve the indirect estimation of layer-specific LNC from canopy reflectance, particularly for Bottom LNC, where the reflectance–LNC association is affected by canopy signal attenuation and mixing. The findings provide a methodological reference for describing canopy vertical nitrogen status and functional heterogeneity in potato, while their broader applicability requires further validation across growth stages, cultivars, sites, and nitrogen management conditions.

Winter wheat production in the extremely arid oasis region of Xinjiang relies heavily on irrigation and fertilization, but conventional high-input management can induce luxury transpiration and non-productive water consumption, limiting the coordinated improvement of grain yield, water use efficiency (WUE), and economic benefits. To identify the threshold at which water–fertilizer inputs shift from efficient use to inefficient water consumption and to define a robust management range, a two-year field experiment was conducted in southern Xinjiang during the 2022–2023 and 2023–2024 growing seasons. Four irrigation levels, corresponding to 60%, 80%, 100%, and 120% of crop evapotranspiration (ET_c), and four fertilization levels were established to evaluate the effects of water–fertilizer interactions on canopy development, leaf gas exchange, evapotranspiration, yield, WUE, and economic benefits. Appropriate water and nutrient supply promoted canopy establishment and maintained higher photosynthetic capacity, thereby increasing grain yield, WUE, and net return. However, excessive inputs weakened yield gains and failed to synchronously improve WUE and economic benefits. Linear plateau models revealed clear thresholds in both the crop-stand scale evapotranspiration (ET)–dry matter accumulation (DM) relationship and the leaf-scale transpiration rate (Tr)–net photosynthetic rate (Pn) relationship. The seasonal ET thresholds were 504.59 and 553.87 mm in the two growing seasons, respectively, and the Tr threshold was 4.83 mmol m⁻² s⁻¹. Beyond these thresholds, additional water consumption was not effectively converted into photosynthetic assimilation or biomass accumulation, indicating luxury transpiration. Year-specific response surface analysis and TOPSIS evaluation showed that I3F3, namely 100% ET_c combined with 210–195–75 kg ha⁻¹ N–P₂O₅–K₂O, together with its adjacent range, sustained high grain yield, WUE, and economic benefits, with I3F3 achieving the best overall performance in both years. The intersection of the two-year high-performance regions further defined a robust interannual feasible range with an irrigation amount of 506.21–545.09 mm and a total fertilizer input of 369.54–628.33 kg ha⁻¹. Overall, maintaining water and fertilizer inputs within the I3F3-adjacent range can reduce non-productive water consumption and luxury transpiration risk while synergistically improving grain yield, WUE, and economic benefits in winter wheat.

Synergistic water–nitrogen (N) management is vital for high maize (Zea mays L.) yields, but the integrated physiological mechanisms driving yield formation remain unclear. A 2-year field study with 3 irrigation levels and 4 N rates revealed that high maize yields were maintained under mild drought combined with medium-to-high N via distinct pathways. Water–N synergy enhanced leaf antioxidant capacity, with N increasing peroxidase (POD) activity and reducing malondialdehyde, thereby mitigating oxidative stress, delaying chlorophyll and photosynthesis (An) decline, and sustaining assimilates such as soluble sugars (SS) and free amino acids (FAA). In grains, mild drought raised SS by 3.0% but reduced sucrose synthase (SuSy) and ADP-glucose pyrophosphorylase (AGPase) activities by 13.3% and 20.7%, respectively, lowering starch (ST) by 9.7%. Severe drought drastically reduced assimilate input, enzyme activities, and ST (−37.3%). N metabolism was also impaired, with lower FAA and protein (PRO) linked to lower glutamine synthetase and glutamate synthase activities. Hormonal balance was critical: zeatin + zeatin riboside (Z + ZR) and indole-3-acetic acid (IAA) promoted grain weight and correlated positively with carbon-metabolizing enzymes, while severe drought increased gibberellin A3 (GA3). In a multivariate analysis, SuSy, AGPase, IAA, Z + ZR, and GA3 explained 82.32% of ST variation, and the interaction between N metabolism enzymes and hormonal ratios explained 92.0% of PRO variation. Carbohydrate metabolism, N metabolism, and hormone balance accounted for 44%, 19%, and 7% of the variation in 100-grain weight, respectively, while their interactions explained an additional 19%. This study establishes a physiological network of water–N synergy, highlighting antioxidant enhancement and hormone–metabolism interactions, that provides a theoretical basis for precision water–N management in maize production.