To optimize the growth management of spring maize, it is essential to understand the dynamics of plant height and leaf area index (LAI) under controlled water and nitrogen supply. This study conducted two-year field experiments (2022–2023) in Karamay, Xinjiang. Three irrigation levels (75%, 100%, and 125% of Crop Evapotranspiration (ET_c)) and four nitrogen application rates (0, 93, 186, and 279 kg N/ha) were set. A logistic growth model was fitted using accumulated effective temperature as the independent variable to analyze the growth and development characteristics of spring maize under various water and nitrogen conditions. The results demonstrated that the logistic models, based on relative effective accumulated temperature, had a determination coefficient (R²) of over 0.99 and a Normalized Root Mean Square Error (NRMSE) of less than 10%. Irrigation extended the rapid growth phase of plant height, whereas nitrogen application shortened the time to enter this rapid growth phase and prolonged its duration. Irrigation increased the maximum LAI growth rate and shortened and prolonged the rapid growth phase, while nitrogen extended the duration of the rapid growth phase for LAI. The W2N2 treatment, consisting of 100% ET_c irrigation and 186 kg N/ha, was identified as the optimal drip irrigation water–nitrogen combination for spring maize in the study area. Under optimal water and nitrogen supply, both the maximum growth rate and the average growth rate during the rapid growth phase were higher, requiring accumulated effective temperatures of 825.16–845.74 °C·d and 856.68–890.00 °C·d, respectively, to reach these rates. The appropriate water and nitrogen supply significantly enhanced the synergistic promotion of growth and development in spring maize. This study provides a theoretical basis for the quantitative analysis of growth dynamics in summer maize using effective accumulated temperature.

Globally, water scarcity demands immediate attention, particularly in arid regions like Northwest China, necessitating efficient water use strategies in crop cultivation. Quinoa (Chenopodium quinoa Willd.), celebrated for both its drought tolerance and nutritional value, has consequently emerged as a central focus in contemporary agricultural research seeking solutions to this challenge. To explore the effects of different irrigation amounts on quinoa yield and water productivity, a mulched drip irrigation technique was applied in community trials of quinoa in Mulei County in 2020 and in Bole City in 2021. The “JL-1” quinoa variety was used as the experimental material, and four irrigation levels were set (255 mm, 292 mm, 330 mm, and 367 mm). This study examined the impact of varying irrigation amounts on quinoa growth indicators, like plant height, stem diameter, leaf area index, aboveground biomass, and yield, and analyzed water productivity. The results from two years of trials indicated that different irrigation gradients had significant or extremely significant effects on quinoa growth indicators. The maximum values of growth indicators were achieved under the highest irrigation level of the control treatment. Water production rates in the 2020 trial in Mulei were highest at an irrigation amount of 330 mm, while in the 2021 trial in Bole, the highest water production rate was observed at 292 mm. Across the two years of trials, when the irrigation amounts were the same prior to the heading stage, the differences among all treatments were not significant, whereas varying irrigation gradients had a significant impact on growth after the heading stage. Furthermore, the growing environment significantly affected the quinoa yield; in the Bole trial, strong winds in the mid-growth period led to severe lodging of quinoa. The findings suggest that managing irrigation amounts, specifically by appropriately increasing irrigation during the water-sensitive stage of quinoa (from heading to grain filling) and reducing water during the early growth stage, can control the growth in quinoa height, thereby improving yield while conserving water resources.

Given the current global water scarcity issues, which particularly affect arid regions such as northwestern China, it is crucial to find crop planting patterns that result in efficient water resource utilization. Quinoa, as a drought-resistant and highly nutritious crop, has garnered significant attention from agricultural researchers in recent years. From 2019 to 2020, a series of experimental studies were conducted under non-mulching drip irrigation conditions to investigate the growth adaptability and the response to different irrigation levels of quinoa in an arid region in northwestern China. A comparative analysis of quinoa’s dry matter accumulation, yield, thousand-grain weight, harvest index, and water use efficiency under varying irrigation levels revealed that increasing irrigation significantly enhanced quinoa’s dry matter accumulation and yield. By optimizing the irrigation strategies, we found that the water-saving practice of initiating moderate irrigation in the sensitive water-demanding stages (flowering and fruiting) of quinoa increased the yield. The experiment results showed that, in 2020, the optimal irrigation amount was 3675 m³·ha⁻¹ during a 14-day irrigation cycle, meeting quinoa’s growth requirements while improving water resource utilization efficiency. This study not only provides a scientific basis for the efficient cultivation of quinoa in the arid regions of northwestern China, but also offers new insights into and technical support for agricultural water resource management in the region, contributing to the sustainable development of agriculture in arid areas.

A field experiment was conducted on 16-year-old ‘Wen 185’ walnut trees in Aksu, Southern Xinjiang, to identify optimal water and fertilizer management under subsurface drip irrigation. Four irrigation levels were established: 75% ET_c (W1), 100% ET_c (W2), 125% ET_c (W3), and 150% ET_c (W4). These were combined with three fertilizer levels: N 270, P 240, K 300 kg ha⁻¹ (F1), N 360, P 320, K 400 kg ha⁻¹ (F2), and N 450, P 400, K 500 kg ha⁻¹ (F3). This resulted in a total of 12 treatments. This study assessed the impact of different water and fertilizer treatments on walnut growth dynamics, yield, fruit quality, water and fertilizer use efficiency, and soil nitrate residue. Principal component analysis (PCA) was used to construct comprehensive growth and photosynthesis indices (CGI and CPI). Parameters significantly correlated with yield and quality were then screened via Pearson analysis, and a game theory-based combination weighting method was adopted to determine weights for integrating six categories of indicators: growth, photosynthesis, yield, quality, resource use efficiency, and environmental impact. A coupled TOPSIS-GRA model was developed for comprehensive evaluation. Furthermore, binary quadratic regression was employed to optimize the application ranges of water and fertilizer. The results showed that the W2F2 treatment achieved the highest rank by synergistically enhancing growth, photosynthetic performance, yield, and quality. This treatment also maintained high water use efficiency (WUE) and partial factor productivity of fertilizer (PFP) and effectively reduced nitrate accumulation in deep soil layers. The CGI and CPI, derived from PCA, effectively quantified phenological growth and photosynthetic characteristics. Correlation analysis identified seven core parameters, among which IV-CPI correlated most strongly with yield. In contrast, II-CPI was more closely associated with increased single-fruit weight and reduced tannin content. Within the comprehensive evaluation system that used game theory-based combination weighting, yield received the highest weight (0.215), while IV-CPI was assigned the lowest (0.011). The TOPSIS-GRA coupled model identified the W2F2 treatment as the highest-ranked. Furthermore, regression optimization determined the optimal total seasonal application ranges to be 5869.94–6519.81 m³ ha⁻¹ for irrigation and 975.54–1107.49 kg ha⁻¹ for fertilization. The coupled TOPSIS-GRA model enabled a balanced assessment of the objectives: high yield, superior quality, resource use efficiency, and environmental sustainability. Thus, it provides a theoretical foundation and practical guidance for enhancing the productivity and sustainability of subsurface drip-irrigated walnut orchards in Southern Xinjiang.

To identify optimal water and fertilizer management for walnut trees under subsurface drip irrigation in Southern Xinjiang, a field experiment was conducted on 16-year-old ‘Wen 185’ walnuts in Aksu. Four irrigation levels—75% ETc (W1), 100% ETc (W2), 125% ETc (W3), and 150% ETc (W4)—and three fertilizer levels—N 270, P 240, K 300 kg·hm-2 (F1), N 360, P 320, K 400 kg·hm-2 (F2), and N 450, P 400, K 500 kg·hm-2 (F3)—were applied, resulting in 12 treatments. This study assessed the impact of different water and fertilizer treatments on walnut growth dynamics, yield, fruit quality, water and fertilizer use efficiency, and soil nitrate residue. Principal component analysis (PCA) was employed to develop comprehensive growth and photosynthesis indices (CGI and CPI). Pearson correlation analysis was used to identify parameters significantly correlated with yield and quality. A game theory-based combination weighting method was then applied to integrate six categories of indicators: growth, photosynthesis, yield, quality, resource use efficiency, and environmental impact. A coupled TOPSIS-GRA model was established for comprehensive evaluation, and binary quadratic regression was used to optimize the water and fertilizer application ranges. The results demonstrated that the W2F2 treatment provided the most effective synergistic enhancement in terms of growth, photosynthetic performance, yield, and quality. It also maintained high water use efficiency (WUE) and partial factor productivity of fertilizer (PFP), while effectively mitigating nitrate accumulation in deep soil layers. The CGI and CPI indices, developed through PCA, successfully quantified phenological growth and photosynthetic characteristics. Correlation analysis identified seven core parameters. Among these, IV-CPI showed the strongest correlation with yield, whereas II-CPI contributed notably to increasing single-fruit weight and reducing tannin content. Within the comprehensive evaluation system employing game theory-based combination weighting, yield was assigned the highest weight (0.215), and IV-CPI received the lowest (0.011). The TOPSIS-GRA model ranked W2F2 highest, with an optimal irrigation range of 5869.94–6519.81 m3·hm-2 and fertilizer application rate of 975.54–1107.49 kg·hm-2. The coupled TOPSIS-GRA model effectively balanced the objectives of high yield, superior quality, resource use efficiency, and environmental sustainability. It offers a solid theoretical basis and practical technical guidance for enhancing both the productivity and sustainability of walnut orchards under subsurface drip irrigation in the Southern Xinjiang region.