Combined application of soluble organic and chemical fertilizers in drip fertigation improves nitrogen use efficiency and enhances tomato yield and quality.

BACKGROUND: Sustainable greenhouse tomato production requires optimal fertilizer management to achieve the double-win strategy of producing high yields and maximizing profits with less environmental pollution. The objective of this study was to seek an optimal fertilization strategy maintaining high productivity of greenhouse tomato, improving nitrogen use efficiency and reducing nitrate leaching risk. RESULTS: The combined application of soluble organic and chemical fertilizers for topdressing (SOSC) not only produced more fruit yield (75.18 Mg ha-1 ) and plant dry matter (10 449.12 kg ha-1 ), but also enhanced plant nutrients uptake, nitrogen recovery efficiency (39.22%), nitrogen agronomic efficiency (176.78 kg kg-1 ), soluble solids, vitamin C and lycopene content in tomato fruits compared with the other treatments, that is chicken manures for basal application and chemical fertilizer for topdressing (CC), soluble organic fertilizer for topdressing (SO) and soluble chemical fertilizer for topdressing (SC). In terms of soil nutrients residue, SOSC had no obvious NO3 - -N accumulation area in the 0-60 cm soil layer, unlike large accumulation in the soil layer below 30 cm in SO and SC. CONCLUSION: The combined application of soluble organic and chemical fertilizers is highly recommended to sustain fruit yield, improve nitrogen use efficiency and reduce soil degradation risks in commercial greenhouse tomato production.

Optimization of Controlled Water and Nitrogen Fertigation on Greenhouse Culture of Capsicum annuum.

This study investigated the effects of different combinations of irrigation and nitrogen levels on the growth of greenhouse sweet peppers, assessing yield, quality, water use efficiency (WUE), and partial factor productivity from applied N (PFPN). By using controlled drip irrigation, the optimal conditions for efficient, large-scale, high-yield, and high quality production of sweet peppers in Northwest China were determined. Using the local conventional irrigation and nitrogen regime as a control (105% ET0, N: 300 kg·hm-2), three alternative irrigation levels were also tested, at 90%, 75%, and 60% ET0. These were combined with nitrogen levels at 100%, as the control, and 75%, 50%, and 25%, resulting in 16 combination treatments. The results show that different supplies of water and nitrogen nutrition had a significant impact on the growth, yield, WUE, PFPN, and quality of fruit. The treatments of W0.90N0.75, W0.90N0.50, W0.75N0.75, and W0.75N0.50 can better maintain the "source-sink" relationship of peppers. They increased the economic yield, WUE, and PFPN. A principal component analysis was performed to evaluate indicators of fruit quality, revealing that the treatment of W0.75N0.50 resulted in the best fruit quality. For greenhouse sweet peppers produced in Northwest China, the combination of W0.90N0.75 resulted in the highest economic yield of 34.85 kg·hm-2. The combination of W0.75N0.75 had the highest WUE of 16.50 kg·m-3. The W0.75N0.50 combination treatment had the highest fruit quality score. For sustainable ecological development and in view of limited water resources in the area, we recommend the W0.75N0.50 combination treatment, since it could obtain the optimal fruit quality, while its economic yield and WUE were 9% and 4% less than the maximum, respectively. This study provides a theoretical basis for the optimal management of water and nitrogen during production of greenhouse sweet peppers in Northwest China.

Research on the food security condition and food supply capacity of Egypt.

Food security is chronically guaranteed in Egypt because of the food subsidy policy of the country. However, the increasing Egyptian population is straining the food supply. To study changes in Egyptian food security and future food supply capacity, we analysed the historical grain production, yield per unit, grain-cultivated area, and per capita grain possession of Egypt. The GM (1,1) model of the grey system was used to predict the future population. Thereafter, the result was combined with scenario analysis to forecast the grain possession and population carrying capacity of Egypt under different scenarios. Results show that the increasing population and limitations in cultivated land will strain Egyptian food security. Only in high cultivated areas and high grain yield scenarios before 2020, or in high cultivated areas and mid grain yield scenarios before 2015, can food supply be basically satisfied (assurance rate ≥ 80%) under a standard of 400 kg per capita. Population carrying capacity in 2030 is between 51.45 and 89.35 million. Thus, we propose the use of advanced technologies in agriculture and the adjustment of plant structure and cropping systems to improve land utilization efficiency. Furthermore, urbanization and other uses of cultivated land should be strictly controlled to ensure the planting of grains.

Monitoring of Chlorophyll Content of Potato in Northern Shaanxi Based on Different Spectral Parameters.

Leaf chlorophyll content (LCC) is an important physiological index to evaluate the photosynthetic capacity and growth health of crops. In this investigation, the focus was placed on the chlorophyll content per unit of leaf area (LCCA) and the chlorophyll content per unit of fresh weight (LCCW) during the tuber formation phase of potatoes in Northern Shaanxi. Ground-based hyperspectral data were acquired for this purpose to formulate the vegetation index. The correlation coefficient method was used to obtain the "trilateral" parameters with the best correlation between potato LCCA and LCCW, empirical vegetation index, any two-band vegetation index constructed after 0-2 fractional differential transformation (step size 0.5), and the parameters with the highest correlation among the three spectral parameters, which were divided into four combinations as model inputs. The prediction models of potato LCCA and LCCW were constructed using the support vector machine (SVM), random forest (RF) and back propagation neural network (BPNN) algorithms. The results showed that, compared with the "trilateral" parameter and the empirical vegetation index, the spectral index constructed by the hyperspectral reflectance after differential transformation had a stronger correlation with potato LCCA and LCCW. Compared with no treatment, the correlation between spectral index and potato LCC and the prediction accuracy of the model showed a trend of decreasing after initial growth with the increase in differential order. The highest correlation index after 0-2 order differential treatment is DI, and the maximum correlation coefficients are 0.787, 0.798, 0.792, 0.788 and 0.756, respectively. The maximum value of the spectral index correlation coefficient after each order differential treatment corresponds to the red edge or near-infrared band. A comprehensive comparison shows that in the LCCA and LCCW estimation models, the RF model has the highest accuracy when combination 3 is used as the input variable. Therefore, it is more recommended to use the LCCA to estimate the chlorophyll content of crop leaves in the agricultural practices of the potato industry. The results of this study can enhance the scientific understanding and accurate simulation of potato canopy spectral information, provide a theoretical basis for the remote sensing inversion of crop growth, and promote the development of modern precision agriculture.

Soybean (Glycine max L.) Leaf Moisture Estimation Based on Multisource Unmanned Aerial Vehicle Image Feature Fusion.

Efficient acquisition of crop leaf moisture information holds significant importance for agricultural production. This information provides farmers with accurate data foundations, enabling them to implement timely and effective irrigation management strategies, thereby maximizing crop growth efficiency and yield. In this study, unmanned aerial vehicle (UAV) multispectral technology was employed. Through two consecutive years of field experiments (2021-2022), soybean (Glycine max L.) leaf moisture data and corresponding UAV multispectral images were collected. Vegetation indices, canopy texture features, and randomly extracted texture indices in combination, which exhibited strong correlations with previous studies and crop parameters, were established. By analyzing the correlation between these parameters and soybean leaf moisture, parameters with significantly correlated coefficients (p < 0.05) were selected as input variables for the model (combination 1: vegetation indices; combination 2: texture features; combination 3: randomly extracted texture indices in combination; combination 4: combination of vegetation indices, texture features, and randomly extracted texture indices). Subsequently, extreme learning machine (ELM), extreme gradient boosting (XGBoost), and back propagation neural network (BPNN) were utilized to model the leaf moisture content. The results indicated that most vegetation indices exhibited higher correlation coefficients with soybean leaf moisture compared with texture features, while randomly extracted texture indices could enhance the correlation with soybean leaf moisture to some extent. RDTI, the random combination texture index, showed the highest correlation coefficient with leaf moisture at 0.683, with the texture combination being Variance1 and Correlation5. When combination 4 (combination of vegetation indices, texture features, and randomly extracted texture indices) was utilized as the input and the XGBoost model was employed for soybean leaf moisture monitoring, the highest level was achieved in this study. The coefficient of determination (R2) of the estimation model validation set reached 0.816, with a root-mean-square error (RMSE) of 1.404 and a mean relative error (MRE) of 1.934%. This study provides a foundation for UAV multispectral monitoring of soybean leaf moisture, offering valuable insights for rapid assessment of crop growth.

Blending urea and slow-release nitrogen fertilizer increases dryland maize yield and nitrogen use efficiency while mitigating ammonia volatilization.

Agricultural non-point source pollution has become the main pollution source in China. Ammonia (NH3) volatilization is one of the main factors of agricultural non-point source pollution. Slow-release nitrogen fertilizer (S) has been widely recognized as an efficient management measure to increase crop yields and mitigate NH3 volatilization. However, few studies have reported the effects of urea (U) blended with slow-release nitrogen fertilizer (UNS) on maize yield and NH3 volatilization under dryland farming conditions. A two-season field experiment with U, S and various blending ratios of U and S (UNS) under two N application rates (N1: 180 kg N ha-1, N2: 240 kg N ha-1) was conducted to determine their effects on maize yield, NH3 volatilization and residual soil NO3--N. The results showed that UNS substantially reduced NH3 volatilization compared with U, primarily because of the relatively low soil pH and electrical conductivity, and the relatively high soil organic matter. UNS significantly increased dry matter, grain yield, N uptake and N use efficiency (NUE), but reduced residual soil NO3--N compared with U and S. Among UNS treatments, the blending ratio of U and S at 3:7 (UNS2) was most effective in improving maize yield and NUE, while mitigating NH3 volatilization and soil NO3--N leaching. N1 not only reduced N losses, but also increased NUE compared with N2. In conclusion, UNS2N1 is recommended as the best N fertilizer application strategy for the sustainable production of dryland maize in northwest China.

[Effects of the frequency and amount of drip irrigation on yield, tuber quality and water use efficiency of potato in sandy soil of Yulin, northern Shaanxi, China]. / 滴灌频率和灌水量对榆林沙土马铃薯产量、品质和水分利用效率的影响.

Reasonable irrigation is still lacking for potato production in the sandy areas of Yulin, northern Shaanxi Province. To solve this problem, field drip fertigation was conducted to examine the growth, yield and quality of potato during the whole growing season. We further analyzed the responses of these indices to different irrigation frequencies and amounts. There were three irrigation frequencies (d), i.e. 4 (D1), 8 (D2) and 10 (D3), and three irrigation amounts, i.e. 60%ETc (W1), 80%ETc(W2) and 100%ETc(W3), where ETc was the crop water requirement, resulting in a total of nine treatments. Under the same irrigation frequency, plant height, leaf area index, dry matter, tuber yield and economic benefits of W3 were higher than those of W1 and W2. W1 had the highest irrigation water use efficiency (IWUE), while water use efficiency was not significantly affected by irrigation amount. The average tuber yield of W3 was 43442 kg·hm-2, which was 23.3% and 11.6% higher than that of W1 and W2, respectively. The net income of W3 was 23492 yuan·hm-2, which was 40.4% and 18.7% higher than that of W1 and W2, respectively. Tubers from W3 had the highest starch and vitamin C contents but the lowest reducing sugar content, which were 14.4%, 18.54 mg·(100 g)-1 FW and 0.7%, respectively. At the same irrigation amount, tuber yield, IWUE, starch and vitamin C contents of D1 were the highest, but the reducing sugar content was the lowest at the low and medium irrigation amounts. At the high irrigation amount, D2 had the highest tuber yield, IWUE, net income, starch and vitamin C contents but the lowest reducing sugar content, which were 46572 kg·hm-2, 23.04 kg·m-3, 26,622 yuan·hm-2,14.6%, 19.53 mg·(100 g)-1 FW and 0.7%, respectively. Based on the interacting effects of drip irrigation frequency and amount, both yield and quality of D2W3 reached the maximum. Results from the principal component analysis showed that D2W3 had the highest score. D2W3(8 d, 100%ETc) had the greatest yield and quality and relatively higher water use efficiency, which was thus considered as the optimal combination of drip irrigation frequency and amount. The results could provide a scientific basis for the drip irrigation scheduling design for high-yield, high-efficiency and high-quality potato production in the sandy areas of Yulin, northern Shaanxi.

[Effects of irrigation amount and various fertigation methods on yield and quality of cucumber in greenhouse].

Taking cucumber as experimental plant, an experiment was conducted to study the effects of irrigation amount and fertigation methods on growth, yield and quality of cucumber in greenhouse. The experiment had designed two irrigation levels, i.e. 100% ET0 (W1) and 75% ET0 (W2), and four fertigation fertilization ratios, i.e. 100%, 66.6%, 33.3% and 0% (Z100, Z66 , Z33, Z0) fertigation of a total amount of (360:180:540 kg · hm(-2)) (N:P2O5:K2O) by 8 times with the corresponding remainders (0%, 33.3%, 66.6% and 100%) were applied to soil as basic fertilization before the planting according to the recommended fertilization rate, and no fertilizer treatment was set up as the control (CK). Results showed that irrigation and fertilization levels had positive correlations with plant height, leaf areas, dry mass, yield and quality of cucumber. Yield at W1Z100 was the highest, reaching 67760 kg · hm(-2). W2 treatment increased the mean water use efficiency (WUE) by 9.4% compared to W1. W2Z100 treatment had the highest WUE, reaching 47.13 kg · m(-3). Yield at W2Z100 was only 3.4% lower than the maximum, but saved 25% of water. Yield and dry matter at Z100 were 15.3% and 16.8% higher than at Z0, respectively, the cucumber fruit vitamin C, soluble protein and soluble sugar contents were increased, and the water use efficiency was increased by 19.1%. W2Z100 treatment was the best treatment which could enable cucumber to obtain both the high-yield and the high-quality.