High-Efficiency Utilization of Water-Fertilizer Resources and Green Production of Crops

To provide a theoretical basis for the sustainable application of autumn mulching technology, we examined the effects of straw input on spring maize yield and water-use efficiency in film-mulched farmland. Based on the positioning tests of different mulching methods conducted in 2013, non-mulching (NM), spring mulching (SM), autumn mulching (AM), and autumn mulching combined with the return of straw (AMS) were selected in western Liaoning from 2018 to 2021. Spring maize yield, yield component factors, soil water content, and water-use efficiency under the four treatments were assessed. In each year, the AMS treatment significantly increased the maize yield, which was 48.22%, 9.33%, 30.66%, and 9.92%, and 11.78%, 7.71%, 12.86%, and 4.77% higher than that obtained after the SM and AM treatments, respectively. However, the harvest index was not significantly improved by AMS. AMS treatment significantly improved the precipitation utilization rate in all assessed years. Moreover, the crop water consumption was significantly increased by AMS treatment. Compared with the NM treatment, water-use efficiencies for economic and biological yield were also significantly improved. Thus, autumn mulching combined with straw-returning technology is an effective technical measure for improve spring maize yield and water-use efficiency in semi-arid areas of western Liaoning. Full article

In drylands, where the annual precipitation is low and erratic, improving the water storage capacity and the available water in the soil is crucial for crop production. To explore the effect of long-term agronomic management on water storage capacity and available water in the soil, four agronomic management systems were used (including the farmer’s management model (FM), the high nitrogen input model (HN), the manure amendment model (MM), and the biochar amendment model (BM)) for eight consecutive years, and the variation in wheat yield and soil hydraulic, physical, and chemical properties in the 0–100 cm soil profile were investigated. The management practices varied in terms of seeding rates, nitrogen (N)-application strategies, and the application of manure or biochar. The results showed that, under the manure amendment model (MM), the wheat yield was increased by 17–35%, and the water-use efficiency was increased by 14–29% when compared to the farmer’s management model (FM) and the high nitrogen input model (HN). However, no significant differences in wheat yield and water-use efficiency were found under the biochar amendment model (BM) compared to the HN. The high yield and water-use efficiency under the MM were mainly due to the higher saturated hydraulic conductivity, soil saturated water content, field capacity, and soil available water content, which led to an increase in the available water storage in the 0–100 cm soil profile by 29–48 mm. Furthermore, the MM also improved soil organic matter, porosity, root length density, and root weight density and reduced the soil bulk density, which are beneficial for the improvement of the above soil hydraulic properties. Therefore, it is a practical way to ensure high yield and high efficiency of crops in dryland by improving water storage capacity and the available water in the soil, which can be profoundly regulated by agronomic management. Full article

Tillage practices significantly influence crop yield and soil quality. This study investigated the impact of rotary tillage (RT) and deep tillage (DT) on soil properties, microbial diversity, and melon (Cucumis melo L.) root growth and yield. RT involved breaking up the topsoil to a depth of 15 cm using a rotary tiller, while DT employed a rotary tiller followed by a moldboard plow to turn the soil layer over to a depth of 35 cm. The melon variety “Nasimi” was used as the material. Our findings revealed a remarkable response of soil phosphorus to tillage practices. High-throughput sequencing results revealed a significant impact of tillage practices on the soil fungal composition, richness, and diversity but little impact on the bacterial communities. Compared to RT, DT markedly enhanced melon root length, root surface area, root volume, and mean root diameter by 47.42%, 56.70%, 58.83%, and 27.28%, respectively. Additionally, DT treatments significantly increased melon yield (53.46%) compared to RT. The results indicate that DT improves soil nutrient availability, affects soil fungal community characteristics, and optimizes root distribution in soil, thereby improving melon yield. The findings offer valuable theoretical insights for the implementation of effective tillage practices in open-field melon cultivation. Full article

Returning straw to the field is a crucial practice for enhancing soil quality and increasing efficient use of secondary crop products. However, maize straw has a higher carbon-to-nitrogen ratio compared to other crops. This can result in crop nitrogen loss when the straw is returned to the field. Therefore, it is crucial to explore how different methods of straw return affect maize (Zea mays L.) farmland. In this study, a field experiment was performed with three treatments (I, no straw returned, CK; II, direct straw return, SR; and III, straw returned in deep furrows, ISR) to explore the effects of the different straw return modes on soil carbon and nitrogen content and greenhouse gas emissions. The results indicated that the SR and ISR treatments increased the dissolved organic carbon (DOC) content in the topsoil (0–15 cm). Additionally, the ISR treatment boosted the contents of total nitrogen (TN), nitrate nitrogen (NO₃⁻-N), ammonium nitrogen (NH₄⁺-N), dissolved organic nitrogen (DON), and DOC in the subsurface soil (15–30 cm) compared with CK. When it comes to greenhouse gas emissions, the ISR treatment led to an increase in CO₂ emissions. However, SR and ISR reduced N₂O emissions, with ISR showing a more pronounced reduction. The ISR treatment significantly increased leaf and grain biomass compared to CK and SR. The correlation analyses showed that the yield was positively correlated with soil DOC, and soil greenhouse gas emission was correlated with soil NO₃⁻-N. The ISR technology has great potential in sequestering soil organic matter, improving soil fertility, and realizing sustainable agricultural development. Full article

Apple tree productivity is influenced by the quantity of water and nutrients that are supplied during planting. To enhance resource utilization efficiency and optimize yields, a suitable strategy for supplying water and nitrogen must be established. A field experiment was conducted using a randomized block group design on five-year-old apple trees in Ningxia, with two irrigation lower limit levels (55%FC (W1) and 75%FC (W2)) and four N application levels (0 (N1), 120 (N2), 240 (N3), and 360 (N4) kg·ha⁻¹). Our findings showed that leaf N content increased with a higher irrigation lower limit, but the difference was not statistically significant. However, the leaf N content significantly increased with increasing N application. The growth pattern of new shoots followed logistic curve characteristics, with the maximum new shoot growth rate and time of new shoot growth being delayed under high water and high nitrogen treatments. Apple yield and yield components (weight per fruit and number of fruits per plant) were enhanced under N application compared to no N application. The maximum apple yields were 19,405.3 kg·ha⁻¹ (2022) and 29,607 kg·ha⁻¹ (2023) at the N3 level. A parabolic relationship was observed between apple yield and N application level, with the optimal range of N application being 230–260 kg⸱ha⁻¹. Apple quality indicators were not significantly affected by the irrigation lower limit but were significantly influenced by N application levels. The lower limit of irrigation did not have a significant impact on the quality indicators of the apples. Water and N utilization efficiencies improved with the W2 treatment at the same N application level. A negative relationship was observed between the amount of nitrogen applied and the biased productivity of nitrogen fertilizer. The utilization of nitrogen fertilizer was 127.6 kg·kg⁻¹ (2022) and 200.3 kg·kg⁻¹ (2023) in the W2N2 treatment. The apple yield was sustained, the quality of the fruit improved, and a substantial increase in water productivity was achieved with the W2N3 treatment. The findings of this study can be used as a reference for accurate field irrigation. Full article

The online detection of fertilizer solution information is a crucial link in the implementation of intelligent and precise variable fertilization techniques. However, achieving simultaneous rapid online detection of multiple fertilizer components is still challenging. Therefore, a rapid detection method based on spectrophotometry for qualitative and quantitative identification of four fertilizers (typical N, P, and K fertilizers: KNO₃, (NH₄)₂SO₄, KH₂PO₄, and K₂SO₄) was proposed in this work. Full-scan absorption spectra of fertilizer solutions at varying concentrations were obtained using a UV–visible/near-infrared spectrophotometer. By assessing the linear fit between fertilizer concentration and absorbance at each wavelength within the characteristic band, the characteristic wavelengths for KNO₃, (NH₄)₂SO₄, KH₂PO₄, and K₂SO₄ were identified as 214 nm, 410 nm, 712 nm, and 1708 nm, respectively. The identification method of fertilizer type and the prediction model of concentration were constructed based on characteristic wavelength and the Lambert–Beer law. Based on the above analysis, a four-channel photoelectric sensor was designed with four LEDs emitting wavelengths closely matched to characteristic wavelengths for fertilizer detection. A detection strategy of “qualitative analysis followed by quantitative detection” was proposed to realize the online detection of four fertilizer types and their concentrations. Evaluation of the sensor’s performance showed its high stability, with an accuracy of 81.5% in recognizing fertilizer types. Furthermore, the relative error of the sensor detection was substantially less than ±15% for the fertilizer concentrations not exceeding 80 mg/L. These results confirm the capability of the sensor to meet the practical requirements for online detection of four fertilizer types and concentrations in the field of agricultural engineering. Full article

Foxtail millet (Setaria italica) is an important cereal crop with rich nutritional value. Distinctness, Uniformity, and Stability (DUS) are the prerequisites for the application of new variety rights for foxtail millet. In this study, we investigated 32 DUS test characteristics of 183 foxtail millet resources, studied their artificial selection trends, and identified the varieties that conform to breeding trends. The results indicated significant differences in terms of the means, ranges, and coefficients of variation for each characteristic. A correlation analysis was performed to determine the correlations between various DUS characteristics. A principal component analysis was conducted on 31 test characteristics to determine their primary characteristics. By plotting PC1 and PC2, all the germplasm resources could be clearly distinguished. The trends in foxtail millet breeding were identified through a differential analysis of the DUS test characteristics between the landrace and cultivated varieties. Based on these breeding trends, the optimal solution types for multiple evaluation indicators were determined; the weight allocation was calculated; and a specific TOPSIS algorithm was designed to establish a comprehensive multi-criteria decision-making model. Using this model, the breeding potential of foxtail millet germplasm resources were ranked. These findings provided important reference for foxtail millet breeding in the future. Full article

Water scarcity poses a significant threat to the sustainable production of crops in Northern China. Despite this, the effect of water management practices, such as deficit irrigation, on the yield and WUE of potatoes has been rarely explored. Based on the meta-analysis of field experiment data, this study evaluated the influence of deficit irrigation on potato yield, evapotranspiration (ET), water use efficiency (WUE) and irrigation water use efficiency (IWUE) under variable soil types, water-saving ratio, irrigation methods, soil organic carbon (SOC) content, and fertilizer rate in Northern China. Here, we determined that potato WUE and IWUE were significantly increased by 10.0 and 31.6%, respectively, under deficit irrigation, while ET was significantly decreased by 26.3% compared to full irrigation. Conclusively, deficit irrigation significantly reduced potato yields by 16.4% compared to full irrigation. Furthermore, SOC content played a vital role in improving the WUE and alleviating potato yield losses under deficit irrigation. Our study suggested that maximum WUE with lower potato yield losses under deficit irrigation can be achieved in the Central Plains region of China or in yellow loam soil, brown soil, and meadow soil under alternate root-zone irrigation when the water-saving ratio was less than 45% and fertilizer application rates were 300 kg N ha⁻¹, >240 kg P₂O₅ ha⁻¹, and 181–300 kg K₂O ha⁻¹. Overall, these findings highlight the need for a comprehensive understanding of various agricultural management practices and local environmental conditions to optimize the benefits of deficit irrigation in potato-growing regions across Northern China. Full article

In the southern Xinjiang region of China, developing efficient irrigation and fertilization strategies to enhance resource utilization and prevent desertification is of critical importance. This study focuses on jujubes in Xinjiang, China, and involves a three-year field experiment aimed at exploring the optimal application strategy of magnetically treated water combined with microbial organic fertilizer to provide scientific support for high-quality jujube production. The experiment included a control group (using only fresh water, denoted as CK) and combinations of magnetically treated water drip irrigation with varying amounts of microbial organic fertilizer: in 2021, treatments included M0 (only irrigating with magnetically treated water), M6 (0.6 t/ha), M12 (1.2 t/ha), M18 (1.8 t/ha), and M24 (2.4 t/ha); in 2022 and 2023, treatments included M0, M6 (0.6 t/ha), M12 (1.2 t/ha), M24 (2.4 t/ha), and M48 (4.8 t/ha). This study investigated the effects of magnetically treated water drip irrigation combined with microbial organic fertilizer on soil physical properties, hydraulic parameters, enzyme activity, aggregate stability, and jujube yield and quality. The application of microbial organic fertilizer significantly reduced the soil bulk density by 3.07% to 11.04% and increased soil porosity by 1.97% to 14.75%. Soil saturated hydraulic conductivity gradually decreased with the increasing amount of microbial organic fertilizer, with a reduction range of 5.95% to 13.69%, while the water-holding capacity significantly improved (from 0.217 cm³/cm³ to 0.264 cm³/cm³). Additionally, microbial organic fertilizer significantly enhanced the activities of urease, catalase, and sucrase in the soil and significantly increased the proportion of large soil aggregates. Jujube yield increased by 3.66% to 21.38%, and the quality significantly improved, as evidenced by the increase in soluble sugar and flavonoid content. The Gauss model calculation results recommended 3.09 t·hm² as the optimal amount of microbial organic fertilizer for comprehensively improving jujube yield and quality. These findings indicate that magnetically treated water drip irrigation combined with high amounts of microbial organic fertilizer significantly improved soil physical properties, hydraulic parameters, enzyme activity, aggregate stability, and jujube yield and quality, providing scientific evidence for desert soil improvement and agricultural production. Full article

The application of excessive nitrogen fertiliser has been found to have a detrimental impact on the growth and development of cotton in Xinjiang, China. This has resulted in a reduction in cotton yield and economic benefit. The aim of this study was to investigate the potential for reducing the input of inorganic N fertiliser while maintaining the quality and yield formation of cotton. The objective of this study was to examine the growth, photosynthesis, and yield of cotton crops subjected to varying fertiliser treatments. The experiment was conducted in 2021–2022 with eight treatments in the experiment: no fertiliser (CK); conventional application of inorganic nitrogen fertiliser (T0); T1–T3, with 8%, 16%, and 24% reduction in inorganic nitrogen fertiliser application, respectively; and T4–T6, with organic fertilisers replacing the reduced inorganic nitrogen fertiliser application of T1–T3, respectively. In comparison to T0, T5 demonstrated the most notable agronomical performance and yield components across both years. This is attributable to the spatial distribution of cotton bolls, which was more conducive to the net photosynthetic rate and yield formation. This, in turn, led to an augmented photosynthetic capacity, enhanced biomass accumulation, and an elevated harvesting index. The results of the economic benefit analysis demonstrated that in comparison to the control treatment (T0), the net profit of all treatments except T3 increased. In conclusion, the economic benefit reached its maximum in the range of a 9.90–14.10% reduction in nitrogen and a 16.60–17.60% substitution of organic fertiliser. Full article

Working to simplify mechanistic models on the basis of reliability for estimating crop evapotranspiration (ET) in a greenhouse is still worthwhile for horticulturists. In this study, four ET models (Penman–Monteith, Priestley–Taylor, and Shuttleworth–Wallace models, and the Crop coefficient method) were parameterized after taking the restriction effect of resistance parameters in these models on ET into account, named as PA-PM, PA-PT, PA-CC, and PA-SW, respectively. The performance of these four parameterized models was compared at different growth stages, as well as the entire growing season. Tomatoes that were ET-grown in a solar greenhouse without a heating device were measured using weighting lysimeters during 2016–2017 and 2019–2021, in which data from 2016 were used to adjust the model parameters, and data from the other four study years were used to examine the model performance. The results indicated that the PA-PT and PA-CC models have a better performance in estimating tomato ET at four growth stages, while the PA-PM and PA-SW performed well only at the development and middle stages. Compared to the ET that was measured with the weighting lysimeters, the ET that was predicted using the PA-PM model was 27.0% lower at the initial stage, and 8.7% higher at the late stage; the ET that was computed using the PA-SW model was 19.5% and 13.6% higher at the initial and late stages, respectively. The PA-PT model yielded the lowest root mean square error and the highest index of agreement against the other models over the entire growing season, indicating that the PA-PT model is the best recommended model for estimating tomato ET in a solar greenhouse. Full article