Jujube Yield Research Articles

Microbial Organic Fertilizer Combined with Magnetically Treated Water Drip Irrigation Promoted the Stability of Desert Soil Aggregates and Improved the Yield and Quality of Jujubes.

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.

Effects of Actinomycete Act12 on Soil Microbial Community Structure and Plant Traits of Ziziphus jujuba Mill.

Biocontrol agents play a crucial role in agricultural production by reducing the use of pesticides and chemical fertilizers, controlling pests and diseases, and enhancing crop yield and quality. While extensive research has focused on the growth-promoting and yield-increasing effects of biocontrol agents on herbaceous plants, their impact on woody crops such as trees and shrubs has not been reported. This study investigates the effects of the actinomycete strain Act12, applied via root drenching and foliar spraying, on the flowering and fruit set rates, leaf physiology and enzyme activity, and fruit characteristics and yield of the jujube tree (Ziziphus jujuba Mill.). Additionally, this study analyzes the physicochemical properties of the soil and the diversity and community structure of its microorganisms. The results indicate that treatment with Act12 significantly altered the α and β diversity of soil microorganisms and enhanced the interaction networks among them. This led to increased levels of available nitrogen, phosphorus, and potassium in the soil, significantly improving nutrient availability. Consequently, there was an improvement in the number of flower buds and fruits, as well as an increase in the longitudinal diameter and individual fruit weight of the jujube. These effects significantly enhanced the yield and total sugar content of the winter jujube. Given these findings, Act12 can be considered an effective microbial agent for enhancing the yield and quality of winter jujube when applied to the soil.

Optimized sand tube irrigation combined with nitrogen application improves jujube yield as well as water and nitrogen use efficiencies in an arid desert region of Northwest China

Efficient water-saving irrigation techniques and appropriate nitrogen (N) application are keys to solving the problems of water scarcity and irrational fertilization in jujube cultivation. In this study, first, the effects of sand tube irrigation (STI) on surface and subsurface wetted characteristics were investigated using in-situ infiltration tests in a jujube garden. Compared with surface drip irrigation (SD), STI reduced surface wetted area by 57.4% and wetted perimeter of the surface wetted circle by 37.1% and increased subsurface maximum infiltration distance of wetting front by 64.9%. At the optimal sand tube depth of 20 cm, surface wetted area of the surface wetted circle decreased by 65.4% and maximum infiltration distance of the wetting front increased by 70.9%, compared with SD. Two-year field experiments then investigated the effects of STI and SD on soil water storage, jujube leaf chlorophyll, net photosynthetic rate, actual water consumption, fruit yield, and water (WUE) and N (NUE) use efficiencies at four levels of N (pure nitrogen: N1, 0; N2, 286 kg ha–1; N3, 381 kg ha–1; N4, 476 kg ha–1) at the same irrigation amount (45 mm irrigation–1, total of 8). Compared with SD, STI increased soil water storage 18.0% (2021) and 15.6% (2022) during the entire growth period and also chlorophyll content, nitrogen balance index, and net photosynthetic rate, with both increasing and then decreasing with increasing N. Compared with SD, STI increased yields by 39.1% and 36.5% and WUE by 44.3% and 39.7% in 2021 and 2022, respectively. Nitrogen use efficiency was 2.5 (2021) and 1.6 (2022) times higher with STI than with SD. STI combined with N3 had the highest yield, WUE, NUE, and net income and is thus recommended as the optimal water–N combination. In conclusion, STI combined with appropriate N application can be an effective water-saving irrigation technology alternative to SD in jujube cultivation in arid areas.

Inverting Chlorophyll Content in Jujube Leaves Using a Back-Propagation Neural Network–Random Forest–Ridge Regression Algorithm with Combined Hyperspectral Data and Image Color Channels

Chlorophyll content is highly susceptible to environmental changes, and monitoring these changes can be a crucial tool for optimizing crop management and providing a foundation for research in plant physiology and ecology. This is expected to deepen our scientific understanding of plant ecological adaptation mechanisms, offer a basis for improving agricultural production, and contribute to ecosystem management. This study involved the collection of hyperspectral data, image data, and SPAD data from jujube leaves. These data were then processed using SG smoothing and the isolated forest algorithm, following which eigenvalues were extracted using a combination of Pearson’s phase relationship method and the Partial Least Squares Regression–continuous projection method. Subsequently, seven methods were employed to analyze the results, with hyperspectral data and color channel data used as independent variables in separate experiments. The findings indicated that the integrated BPNN-RF-Ridge Regression algorithm provided the best results, with an R2 of 0.8249, MAE of 2.437, and RMSE of 2.9724. The inclusion of color channel data as an independent variable led to a 3.2% improvement in R2, with MAE and RMSE increasing by 1.6% and 3.9%, respectively. These results demonstrate the effectiveness of integrated methods for the determination of chlorophyll content in jujube leaves and underscore the potential of using multi-source data to improve the model fit with a minimal impact on errors. Further research is warranted to explore the application of these findings in precision agriculture for jujube yield optimization and income-related endeavors, as well as to provide insights for similar studies in other plant species.

The Influences of Soil and Meteorological Factors on the Growth and Fruit Quality of Chinese Jujube (Ziziphus jujuba Mill.).

Chinese jujube (Ziziphus jujuba Mill.) is attracting more and more attention worldwide due to their tasty and nutritious fruit with extremely high contents of vitamin C (Vc) and soluble sugar. In order to find out the main factors that influence jujube growth and reproductive adaptability, the phenological periods, vegetative growths, fruiting abilities, and fruit qualities of eight newly released cultivars were compared and comprehensively analyzed in three representative ecological sites of the three main jujube-producing regions including Fuping (Hebei), Taigu (Shanxi), and Alar (Xinjiang) in China. Our results showed that the characteristics of jujube cultivars were significantly affected by soil and meteorological factors. The fruit number per bearing shoot was much more affected by temperature, light, and rainfall. The fruit number per bearing shoot, contents of soluble solids, and soluble sugar and Vc contents in fruits were influenced more by meteorological factors. The content of flavonoids was affected by both soil and meteorological factors. A principal component analysis (PCA) indicated that cultivars suitable for planting in Fuping (Hebei) were Yuhong and Lengbaiyu. Zaocuimi, Fucuimi, and Zaoqiuhong were suitable to be cultivated in Taigu (Shanxi), while Zaocuimi, Yuhong, Yulu, Luzao 2, and Yueguang behaved better in Alar (Xinjiang). This study provides insights of the environmental factors on jujube yield and quality and therefore provides references for highly efficient jujube cultivation.

Magnetically treated water drip irrigation combined with carboxymethyl cellulose (CMC) application: A regulating strategy for enhancing the jujube yield and quality in southern Xinjiang of China

Developing effective regulation strategies for improving the efficiency of irrigation water and fertilizers, and preventing further expansion of desertification in southern Xinjiang, China, is crucial. Magnetically treated water (MTW) has been shown to have a positive effect on plant growth. The carboxymethyl cellulose (CMC) has been widely used as an efficient soil amendment to improve soil aggregation and hydraulic properties. This study aimed to explore the optimal mode of combining MTW drip irrigation and CMC application for high-quality jujube production. Conventional freshwater irrigation was set up in both 2021 and 2022 (control group, CK). CMC treatments under MTW drip irrigation included C0 (0), C150 (150 kg/ha), C250 (250 kg/ha), C350 (350 kg/ha), and C450 (450 kg/ha) in 2021, and C0 (0), C150 (150 kg/ha), C300 (300 kg/ha), C450 (450 kg/ha), and C600 (600 kg/ha) in 2022. The results showed that CMC significantly increased soil porosity, water-holding capacity, and decreased soil bulk density and soil saturated hydraulic conductivity. CMC contributed 2.88 % to 27.96 % of large aggregates (>0.25 mm), significantly improving soil aggregate stability. Water and fertilizer (N, P, K) productivity increased by 4.5 % to 11.0 % and 1.9 % to 11.3 %, respectively. Jujube yield increased by 2.75 % to 15.98 %, and MTW increased jujube yield by 3.10 % compared to the CK. The recommended optimal CMC application rate was approximately 430 kg/ha. This mode provides a reliable theoretical reference for jujube industry development and soil desertification improvement in southern Xinjiang, China.

Drip irrigation shapes the soil bacterial communities and enhances jujube yield by regulating the soil moisture content and nutrient levels

In the agricultural zones of the arid Xinjiang region of China, reducing irrigation is mandatory. However, irrigation affects the composition and diversity of the soil bacterial community which is vital to crop yield. To the best of our knowledge, very little research has been conducted on the relationships among the soil bacterial community, irrigation method, and yield as well as their underlying in jujube agroecosystems. Here, we investigated the soil physicochemistry and bacterial communities in jujube fields subjected to drip irrigation (DI) and traditional flood irrigation (FI), and their associations with yield at the flowering and fruit set (FFS) and end-of-growth (EG) stages. Under DI, the jujube yield was 8712.00 ± 24.54 kg/hm2, which was 7.64% higher than that obtained under FI (8094.33 ± 43.67 kg/hm2). DI increased the relative soil bacteria community diversity by decreasing the moisture content and increasing the nutrient levels in the soil. DI also transformed the soil bacterial community so that Bacteroidota predominated at the FFS stage and the probiotics Chloroflexi and Firmicutes predominated at the EG stage. A co-occurrence network analysis showed that DI created stable complex Soil bacteria communities in jujube fields, Though Dependentiae and Deferriberota had low relative abundance, they were nonetheless key nodes in the soil bacterial community network. A neutral community model (NCM) revealed that stochastic processes drove the soil bacterial community assembly whereas DI promoted deterministic processes by regulating the soil moisture content and nutrient levels. Partial least squares path modeling (PLS-PM) disclosed that DI affected the soil bacterial community structure by decreasing the moisture content (−0.342 **) and increasing the nutrient levels (0.557 **) in the soil. The PLS-PM also demonstrated that the observed change in the soil bacterial community structure was the main reason for the increase in jujube yield (1.098 **). The present work provides insights into the mechanisms underlying the correlations between the soil bacterial community and crop yield in response to changes in the irrigation method.

Effects of Microbial Organic Fertilizer (MOF) Application on Desert Soil Enzyme Activity and Jujube Yield and Quality

Developing effective regulatory strategies to enhance irrigation water and fertilizer efficiency in the southern Xinjiang region of China, while simultaneously combatting desertification, is of paramount significance. This study focuses on Chinese jujube in Xinjiang and presents findings from a two-year field experiment aimed at investigating the optimal application strategy of microbial organic fertilizer (MOF). The research aims to provide a scientific foundation for achieving high-quality jujube production. The experiment involved a control group (utilizing only freshwater, referred to as CK) and various combinations of MOF treatments. In 2021, these treatments included M1 (0.6 t/ha), M2 (1.2 t/ha), M3 (1.8 t/ha), and M4 (2.4 t/ha), while in 2022, they encompassed M1 (0.6 t/ha), M2 (1.2 t/ha), M4 (2.4 t/ha), and M5 (4.8 t/ha). Over the two-year trial period, we assessed various indices, including the soil’s physical properties, hydraulic characteristics, soil enzyme activities, and relative chlorophyll content. Additionally, we evaluated jujube yield, quality, and economic benefits. The results indicate that MOF application led to significant improvements in soil conditions. Specifically, the average moisture content and profile water storage of the 0–50 cm soil layer increased by 10.98% to 36.42% and 1.8% to 26.8%, respectively. Moreover, in both the 2021 and 2022 experiments, soil saturated water content (SSWC) and water-holding capacity (WHC) increased by 6.25% to 15.98%, while soil hydraulic conductivity (Ks) and bulk density (BD) decreased by 2.91% to 9.88% and 0.63% to 8.08%, respectively. In 2021, MOF application resulted in significant enhancements in soil enzyme activities, with urease activity increasing by approximately 22.5% to 100.5%, peroxidase activity rising by around 24.2% to 148.5%, and invertase activity augmenting by about 5.4% to 32.9%. Notably, the M4 treatment in 2021 demonstrated a substantial jujube yield increase of approximately 19.22%, elevating from 7.65 t/ha to 9.12 t/ha. Based on comprehensive analysis, this study recommends an optimal MOF application rate of approximately 2.4 t/ha. This approach not only provides robust support for the sustainable development of the jujube industry but also serves as a valuable reference for enhancing local soil resilience against desertification.

Feature enhancement guided network for yield estimation of high-density jujube

BackgroundAutomatic and precise jujube yield prediction is important for the management of orchards and the allocation of resources. Traditional yield prediction techniques are based on object detection, which predicts a box to achieve target statistics, but are often used in sparse target settings. Those techniques, however, are challenging to use in real-world situations with particularly dense jujubes. The box labeling is labor- and time-intensive, and the robustness of the system is adversely impacted by severe occlusions. Therefore, there is an urgent need to develop a robust method for predicting jujube yield based on images. But in addition to the extreme occlusions, it is also challenging due to varying scales, complex backgrounds, and illumination variations.Results In this work, we developed a simple and effective feature enhancement guided network for yield estimation of high-density jujube. It has two key designs: Firstly, we proposed a novel label representation method based on uniform distribution, which provides a better characterization of object appearance compared to the Gaussian-kernel-based method. This new method is simpler to implement and has shown greater success. Secondly, we introduced a feature enhancement guided network for jujube counting, comprising three main components: backbone, density regression module, and feature enhancement module. The feature enhancement module plays a crucial role in perceiving the target of interest effectively and guiding the density regression module to make accurate predictions. Notably, our method takes advantage of this module to improve the overall performance of our network. To validate the effectiveness of our method, we conducted experiments on a collected dataset consisting of 692 images containing a total of 40,344 jujubes. The results demonstrate the high accuracy of our method in estimating the number of jujubes, with a mean absolute error (MAE) of 9.62 and a mean squared error (MSE) of 22.47. Importantly, our method outperforms other state-of-the-art methods by a significant margin, highlighting its superiority in jujube yield estimation.Conclusions The proposed method provides an efficient image-based technique for predicting the yield of jujubes. The study will advance the application of artificial intelligence for high-density target recognition in agriculture and forestry. By leveraging this technique, we aim to enhance the level of planting automation and optimize resource allocation.

Yield prediction and water‐nitrogen management of Chinese jujube based on machine learning

AbstractJujubes are a crucial characteristic industry in China. Predicting jujube production in various regions of China is significant to developing the jujube industry. This study aims to predict jujube yields across China by machine learning and optimize water‐nitrogen applications to achieve the highest yields. We utilized four machine learning methods (i.e., linear regression, support vector machine, ensemble learning and Gaussian process regression) to create predictive models based on the jujube production, irrigation, fertilization and planting density data sets. The results showed that the Gaussian process regression model best predicted jujube yield by comparing the predicted and measured data. The ensemble learning and Gaussian process regression model best optimized the optimal water and nitrogen application range. On the whole, the Gaussian process regression model is more suitable for yield prediction and water‐nitrogen management. The water‐nitrogen coupling function based on the Gaussian process regression model for predicting jujube yield in Xinjiang, Gansu and Shaanxi was developed to make suitable irrigation and fertilizer regimes. This study can provide a theoretical basis for predicting jujube production and water‐nitrogen management in China.

A Counting Method of Red Jujube Based on Improved YOLOv5s

Due to complex environmental factors such as illumination, shading between leaves and fruits, shading between fruits, and so on, it is a challenging task to quickly identify red jujubes and count red jujubes in orchards. A counting method of red jujube based on improved YOLOv5s was proposed, which realized the fast and accurate detection of red jujubes and reduced the model scale and estimation error. ShuffleNet V2 was used as the backbone of the model to improve model detection ability and light the weight. In addition, the Stem, a novel data loading module, was proposed to prevent the loss of information due to the change in feature map size. PANet was replaced by BiFPN to enhance the model feature fusion capability and improve the model accuracy. Finally, the improved YOLOv5s detection model was used to count red jujubes. The experimental results showed that the overall performance of the improved model was better than that of YOLOv5s. Compared with the YOLOv5s, the improved model was 6.25% and 8.33% of the original network in terms of the number of model parameters and model size, and the Precision, Recall, F1-score, AP, and Fps were improved by 4.3%, 2.0%, 3.1%, 0.6%, and 3.6%, respectively. In addition, RMSE and MAPE decreased by 20.87% and 5.18%, respectively. Therefore, the improved model has advantages in memory occupation and recognition accuracy, and the method provides a basis for the estimation of red jujube yield by vision.

Jujube is at a competitiveness disadvantage to cotton in intercropped system

AbstractIntercropping is a key methodology used by farmers to improve economic benefits. However, in certain areas such as Xinjiang, China, limitations in available irrigation water make intercropping difficult to implement. Farmers are therefore challenged to improve economic benefits in water‐limited conditions. We evaluated the effectiveness of intercropped common jujube (Zizyphus jujuba Mill.) and cotton (Gossypium hirsutum L.) under different irrigation regimes. Using a factorial design, crops were planted individually and together (i.e., intercropping) under five different irrigation systems. We measured growth parameters and evaluated the temporal distribution of root system growth and fruit yield. Intercropped cotton displayed higher fitness metrics and outperformed the single‐cropped cotton in crop yield. Intercropping, however, had the opposite effect on jujube plants: the overall fitness and yield of jujube were significantly curtailed under the interspecific competition induced by this planting technique. Under low irrigation levels, cotton plants tended to invade the jujube niches that reduced jujube growth and development. Our findings suggest that in a jujube/cotton intercropping system, cotton is the dominant competitor, whose ability to inhibit the development of the less competitive jujube is exacerbated under water deficit situations. Although intercropping system affected jujube development, overall cotton yield, and therefore benefit to farmers was considerably higher using this system. However, the competitive ability of jujube gradually increases as the plant aged which could reduce the economic advantages of the intercropping system.

Research on Revenue Insurance Premium Ratemaking of Jujube Based on Copula-Stochastic Optimization Model

During the process of jujube planting, there are not only natural risks caused by natural disasters but also market risks caused by price factors. In the study, firstly, wavelet analysis method was used to stabilize the jujube yield per unit area and the jujube price from 1997 to 2018 in Aksu region, Xinjiang, China. Secondly, EasyFit software was used to fit the distribution functions of yield per unit area and price, respectively. Thirdly, the optimal Copula function which connects the marginal distribution functions and its joint distribution function was selected with the principle of “the minimum square distance from the empirical Copula function.” Finally, taking the premium rate and the insurance amount as two decision variables, the farmer’s risk minimization as the objective function, around the four constraints of functions and role of insurance, the nonspeculative nature of insurance, the sustainability of insurance, and the moral hazard factors and the farmers’ willing to participate in insurance, the Copula-stochastic optimization model was set up to determine the premium rate of jujube revenue insurance in Aksu region.

The comparison of different irrigation methods on yield and water use efficiency of the jujube

Water shortage restricts the development of jujube plantation in southern Xinjiang, and the application of water–saving irrigation technology is the key to solve this problem. This study investigated the response of irrigation water use efficiency to various irrigation technologies (vertical tube irrigation and surface drip irrigation) and jujube yield and quality, and to choose a suitable irrigation method for Hui–jujube trees planting. The field experiment was conducted over 2 years. Vertical tube irrigation was implemented with three levels of water pressure by using water pressure heads 0.8, 1.0, and 1.2 m. Additionally, surface drip irrigation was used as a control, and four treatments were used in total. The results indicated that vertical tube irrigation helped save approximately 37–70% of water, and its water use efficiency was 1.4–4.3 times that of surface drip irrigation. Compared with Hui–jujube trees watered by drip irrigation, those watered by vertical tube irrigation had slightly higher yield and decreased fruit cracking (25–83%). Moreover, the sugar–acid ratio increased significantly (P < 0.05). Besides, the continuous water supply used in vertical tube irrigation allowed the maintenance of relatively stable SWC in the main root layer (20–60 cm), can provided a good soil–water–air environment for jujube growth. Vertical tube irrigation saved water primarily because it sends water directly to the main root layer through the emitters buried in the soil, reducing the evaporation of water in the upper soil layer. The irrigation water amount of vertical tube irrigation was proportional to the water supply pressure head. Water use efficiency was the highest under the lowest water supply pressure (water pressure head 0.8 m). The present findings provide a scientific basis for the application of vertical tube irrigation in arid areas.

Effects of Irrigation and Potassium Fertilizer Applications on Jujube Production

Highlights Moderate water deficit will help reduce agricultural investment. Application of potassium fertilizer can alleviate the effect of water deficit on fruit trees. Reasonable ratio of water and fertilizer is helpful to improve economic benefits. Abstract . The jujube planting industry is a key agricultural industry in Xinjiang, China. With an arid climate and limited water resources, Xinjiang must implement more efficient water-saving irrigation systems to guarantee the sustainable development of jujube planting industry. A two-factor, three-level test was adopted to explore how regulated deficit irrigation and different potassium fertilizer levels affected the growth and yield of jujube under drip irrigation. The results of analysis of variance showed that water deficit significantly affected photosynthetic characteristics, growth parameters, evapotranspiration, and yield. The effect of K-application level was focused on fruit volume and yield. However, when the ratio of water to fertilizer is unbalanced (150% K-application + severe water deficit), the growth of jujube trees be inhibited, and the fruit volume and economic benefits reduced by 7% and 11%, respectively. Means comparison indicated that growth parameters, evaporation, and yield under minor water deficit was lower than that under the adequate irrigation by 7%, 13%, and 6%, respectively; and economic performance was higher by 12%. Severe water deficit reduced growth parameters and economic benefits by 33% and 55%, respectively. Thus, minor water deficit irrigation significantly inhibited luxury transpiration and growth redundancy, improved water-use efficiency and increased economic performance. Severer water deficit may damage trees and negatively affect the jujube industry. With economic benefit analysis, 150% K-application with adequate irrigation and minor water deficit, 100% K-application with adequate irrigation and minor water deficit, 50% K-application with minor water deficit all achieve high economic benefits (14074~17261 RmB ha-1). However, when taking water restrictions, the environmental and economic costs of fertilizer, and the long-term effects of tree development into account, application of 100% K-application with minor water deficit (irrigation, 75% ETc; fertilizer, 200 kg ha-1 compound fertilizer+360 kg ha-1 potassium fertilizer) is recommended. Keywords: Deficit irrigation, Economic benefit, Potassium fertilizer, Yield.

Understory mowing controls soil drying in a rainfed jujube agroforestry system in the Loess Plateau

The widely adopted practice of clean-cultivation in rainfed orchards in the Loess Plateau has led to serious soil erosion and degradation problems. Agroforestry is a promising management practice for solving these problems, but may reduce available soil water. Thus, reasonable soil and water management strategies should be developed for agroforestry systems in this region. The objective of this study was to determine whether adopting proper mowing management of the understory intercrop limited soil drying in a rainfed jujube (Ziziphus jujuba Mill.) orchard in this region. Various mowing intensities (3-, 6-, 9-cm stubble height and unmowed treatments) were imposed on three intercrop species: bluegrass (Poa pratensis L.), white clover (Trifolium repens L.), and hairy vetch (Vicia villosa Roth) to investigate and compare their root characteristics and soil moisture responses to mowing under greenhouse and field conditions. Based on the results, the most promising intercrop species and mowing intensity to be used in a jujube orchard were selected for field validation. The results showed that mowing effectively regulated intercrop root amount and distribution, as well as associated soil moisture conditions. However, the sensitivities of root characteristics and soil moisture to mowing and growth environment were species-specific. Bluegrass mowed to a 3-cm stubble height produced the minimum root amount, the shallowest root depth, and the greatest soil water content. When this treatment was applied to a rainfed jujube orchard during the 2015 and 2016 growing seasons, average soil moisture in the 0–300 cm soil layer was essentially unaffected, while fruit yield was increased. Consequently, bluegrass mowed to a stubble height of 3 cm when intercropped with jujube trees in the Loess plateau is a feasible practice to increase jujube yield and avoid extra soil drying.

Infiltration Characteristics and Spatiotemporal Distribution of Soil Moisture in Layered Soil under Vertical Tube Irrigation

The limited quantity of irrigation water in Xinjiang has hindered agricultural development in the region and water-saving irrigation technologies are crucial to addressing this water shortage. Vertical tube irrigation, a type of subsurface irrigation, is a new water-efficient technology. In this study, field and laboratory experiments were conducted to analyze (1) the infiltration characteristics and spatiotemporal distribution of moisture in layered soil and (2) the water-saving mechanism of vertical tube irrigation. In the field experiments, we analyzed jujube yield, irrigation water productivity (IWP), and soil moisture in the jujube root zone. In the laboratory irrigation experiments, two soil types (silty and sandy loam) were selected to investigate homogeneous and layered soil, respectively. Cumulative infiltration, wetting body, and soil water moisture distribution were also analyzed. Relative to surface drip irrigation, vertical tube irrigation resulted in slightly lower jujube yields but higher savings in water use (47–68%) and improved IWP. The laboratory experiments demonstrated that layered soil had less cumulative infiltration, a larger ellipsoid wetted body, slower vertical wetting front migration (hindered by layer interface), and faster horizontal wetting front migration than homogenous soil had. The irrigation amount for vertical tube irrigation decreased in layered soil, and water content increased at the layer interface. Vertical tube irrigation in layered soil facilitates the retention of water in the root zone, prevents deep leakage, reduces irrigation amount, and improves the IWP of jujube trees. This study aids the popularization and application of vertical tube irrigation technology.

Effect of Organic Materials Amendment on Growth of Jujube (Zizyphus jujuba Mill.) and Soil Chemical Properties

Jujube is a deciduous broad-leaved tree belonging to the buckthorn family(Rhamnaceae) and is widely cultivated in Southeast Asia and Southeast Europe, including Korea and China and mainly consumed medicinal herbs or dried jujube. In recent years, consumption of fresh fruits has increased, and organic orchard has also increased. The purpose of this study was to investigate soil chemical changes and growth characteristics of jujube when replacing the total amount of nitrogen fertilizer with organic matter in rain shelter house. In March 2017, after soil testing, bark, animal compost, rice bran, oil cake and chemical fertilizers (NPK) were treated based on nitrogen content. After treatment of organic materials, by March 2020, the pH increased and organic matter, phosphoric acid and cation content in soil increased. After harvest of jujube, the yield of compost treatment was the highest and the NPK treatment was the lowest. The length, hardness and weight of fruit were greater in the NPK treatment, but the diameter and sugar content were not significantly different from the organic material treatments except rice bran. Therefore, when the cultivation of the jujube, nitrogen fertilizer was totally replaced with organic material, there was the effect of improving soil chemistry, such as an increase in the organic content of the jujube orchard and an increase in the yield of jujube but no clear effect on fruit quality. Yield of jujube by organic materials treatment.

Climate suitability of Ziziphus mauritiana in the main planting areas of Fujian Province, China

Taiwan green jujube (Ziziphus mauritiana) is a new fruit variety, with remarkable economic benefit. To achieve high quality and high yield of jujube in Fujian Province, we quantified the climate suitability model parameters of the jujube in main production areas of Fujian, and analyzed climate suitability characteristics and change trend of main production areas, based on the yield and meteorological data, combined with literature and phenological observation data and agricultural climate suitability model. The results showed that the model based on the equal weight summation method had the highest reliability. The climate suitability of jujube in main production areas of Fujian was higher, with most years being suitable or much suitable. From 1996 to 2013, the influence of climate conditions on jujube growth was generally in a good trend, which was conducive to the development of jujube production. The suitability of the main production areas in the whole growing season was ranked as temperature suitability>comprehensive climate suitability>sunshine suitability>precipitation suitability. September and October are the key period of water management. Our results are important in guiding production management and long-term planning of Taiwan green jujube in Fujian Province.

Growth simulation and yield prediction for perennial jujube fruit tree by integrating age into the WOFOST model

Mathematical models have been widely employed for the simulation of growth dynamics of annual crops, thereby performing yield prediction, but not for fruit tree species such as jujube tree (Zizyphus jujuba). The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter. The model was established using data collected from dedicated field experiments performed in 2016–2018. Simulated growth dynamics of dry weights of leaves, stems, fruits, total biomass and leaf area index (LAI) agreed well with measured values, showing root mean square error (RMSE) values of 0.143, 0.333, 0.366, 0.624 t ha−1 and 0.19, and R2 values of 0.947, 0.976, 0.985, 0.986 and 0.95, respectively. Simulated phenological development stages for emergence, anthesis and maturity were 2, 3 and 3 days earlier than the observed values, respectively. In addition, in order to predict the yields of trees with different ages, the weight of new organs (initial buds and roots) in each growing season was introduced as the initial total dry weight (TDWI), which was calculated as averaged, fitted and optimized values of trees with the same age. The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI. The modelling performance was significantly improved when it considered TDWI integrated with tree age, showing good global (R2≥0.856, RMSE≤0.68 t ha−1) and local accuracies (mean R2≥0.43, RMSE≤0.70 t ha−1). Furthermore, the optimized TDWI exhibited the highest precision, with globally validated R2 of 0.891 and RMSE of 0.591 t ha−1, and local mean R2 of 0.57 and RMSE of 0.66 t ha−1, respectively. The proposed model was not only verified with the confidence to accurately predict yields of jujube, but it can also provide a fundamental strategy for simulating the growth of other fruit trees.