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Horticulturae
Special Issues
Advances in Irrigation and Fertilization Technologies for Sustainable Plant Production
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Advances in Irrigation and Fertilization Technologies for Sustainable Plant Production

A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Protected Culture".

Deadline for manuscript submissions: 15 March 2027 | Viewed by 1211

Special Issue Editors

Prof. Dr. Di Feng

E-Mail Website
Guest Editor
Key Laboratory of Saline-Alkali Soil Improvement and Utilization (Saline-Alkali Land in Arid and Semiarid Regions), Ministry of Agriculture and Rural Affairs, China, Institute of Agricultural Resources and Environment, Xinjiang Academy of Agricultural Sciences, Urumchi 830091, China
Interests: optimize saline water utilization; irrigation and fertilizer schedule; plant soil interaction; water-salinity-yield effect; water use efficiency
Dr. Songrui Ning

E-Mail Website
Guest Editor
State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi'an University of Technology, Xi'an 710048, China
Interests: modeling; optimize irrigation and fertilizer schedule; crop growth and yield; fertilizer-yield effect; water use efficiency

Special Issue Information

Dear Colleagues,

As global populations continue to grow and climate variability intensifies, the sustainable enhancement of plant production has become an urgent priority. The efficient use of water and nutrients is central to this challenge. Innovations in irrigation and fertilization are not only vital for increasing plant productivity but also for minimizing environmental impacts such as groundwater depletion, soil salinization, and nutrient runoff.

The purpose of this Special Issue “Advances in Irrigation and Fertilization Technologies for Sustainable Plant Production” is to present innovative studies, tools, approaches, and techniques that have been successful in addressing some of these concerns, such as precision irrigation technologies, energy-saving technologies, irrigation and nutrient management, economic and environmental impact assessments, soil fertility and soil enzymes, the coupled simulation of crop growth and soil environment, and soilless and greenhouse and traditional soil cultivation, as well as drone-assisted monitoring, plant and soil nutrition diagnosis, and AI-driven decision support tools that enable precise water–salt–fertilizer management tailored to real-time crop needs and soil conditions. Researchers are invited to contribute original research articles and reviews that encompass a wide range of topics within the realm of irrigation and fertilization technologies in soilless and greenhouse and traditional soil cultivation for plant production. The scope includes, but is not limited to, investigations into plant-specific responses to water and fertigation, environmental implications and risk assessment, and technological innovations driving this field forward.

Prof. Dr. Di Feng
Dr. Songrui Ning
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Horticulturae is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • irrigation technology
  • irrigation and fertilizer schedule
  • water and nutrient use efficiency
  • soil water–salt–fertilizer transport
  • intelligent agriculture
  • modeling
  • plant growth and yield
  • fertilizer-yield effect
  • plant phenotypic

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Published Papers (2 papers)

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Research

17 pages, 3877 KB  
Article
Fruit Yield and Quality of Zanthoxylum planispinum var. dingtanensis and Their Response to Different Fertilization Regimes
by Yurong Fu, Yanghua Yu, Yun Yang, Hui Huang and Mingfeng Du
Horticulturae 2026, 12(3), 367; https://doi.org/10.3390/horticulturae12030367 - 16 Mar 2026
Viewed by 409
Abstract
Zanthoxylum planispinum var. dingtanensis (hereafter Z. planispinum) is a pioneer plant for the ecological restoration of karst rocky desertification, offering both ecological rehabilitation and economic benefits. Due to the combined pressure from soil degradation and fruit harvesting, nutrient depletion and quality decline [...] Read more.
Zanthoxylum planispinum var. dingtanensis (hereafter Z. planispinum) is a pioneer plant for the ecological restoration of karst rocky desertification, offering both ecological rehabilitation and economic benefits. Due to the combined pressure from soil degradation and fruit harvesting, nutrient depletion and quality decline have intensified. Therefore, investigating the effects of fertilization on pericarp yield and quality provides the scientific basis for its precise fertilization. This study examined a Z. planispinum plantation subjected to five treatments in 2021: no fertilization (CK); organic fertilizer + chemical fertilizer + sprinkler irrigation (T1); chemical fertilizer + sprinkler irrigation (T2); chemical fertilizer alone (T3); and legume (soybean) intercropping + chemical fertilizer + sprinkler irrigation (T4). It explored the intrinsic relationships between fruit quality and soil physicochemical properties, identified key soil factors, and conducted a comprehensive quality evaluation, providing a scientific basis for precise fertilization in karst regions. The results indicated that (1) whole-fruit water content ranged from 61.30% to 64.37%, showing no significant differences, while variations were observed in the other phenotypic traits. T1 exhibited the highest values for Hydroxy-β-sanshool (2.42 mg·g−1), Hydroxy-ε-sanshool (0.80 mg·g−1), essential oil content (8.57%), and fresh weight per plant (9.9 kg). After long-term soybean intercropping, pericarp thickness reached its maximum (0.45 mm), but the content of aroma compounds decreased significantly. Compared to the other four treatments, the unfertilized control (CK) showed significantly higher values for the pericarp dry weight ratio, proportion of closed-eye peppercorns, and relative content of d-limonene, with increases of 5.5–13.94%, 130.91–568.42%, and 8.74–14.46%, respectively. (2) An inhibitory effect was observed between pericarp numbing compounds and soil calcium/phosphorus levels, while the synthesis of aroma compounds was constrained by the soil C/N ratio. Soil P/K ratio was identified as the dominant factor affecting overall quality. (3) The comprehensive fruit quality index ranked as follows: T1 (1.2933) > T3 (0.666) > T2 (0.5285) > CK (−1.1555) > T4 (−1.2098). Therefore, the T1 treatment is recommended for promotion as the fertilization management practice for Z. planispinum plantations in karst regions. Full article
(This article belongs to the Special Issue Advances in Irrigation and Fertilization Technologies for Sustainable Plant Production)
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24 pages, 15798 KB  
Article
Optimizing Priestley–Taylor Model Based on Machine Learning Algorithms to Simulate Tomato Evapotranspiration in Chinese Greenhouse
by Jiankun Ge, Jiaxu Du, Xuewen Gong, Quan Zhou, Guoyong Yang, Yanbin Li, Huanhuan Li, Jiumao Cai, Hanmi Zhou, Mingze Yao, Xinguang Wei and Weiwei Xu
Horticulturae 2026, 12(1), 89; https://doi.org/10.3390/horticulturae12010089 - 14 Jan 2026
Viewed by 447
Abstract
To further improve the prediction accuracy for greenhouse crop evapotranspiration (ET) under different irrigation conditions and enhance irrigation water use efficiency, this study proposes three methods to revise the Priestley–Taylor (PT) model coefficient α for calculating ET at different growth stages: [...] Read more.
To further improve the prediction accuracy for greenhouse crop evapotranspiration (ET) under different irrigation conditions and enhance irrigation water use efficiency, this study proposes three methods to revise the Priestley–Taylor (PT) model coefficient α for calculating ET at different growth stages: (1) considering the leaf senescence coefficient fS, plant temperature constraint parameter ft, and soil water stress index fsw to correct α (MPT model); (2) combining the Penman–Monteith (PM) model to inversely calculate α (PT-M model); (3) using the machine learning XGBoost algorithm to optimize α (PT-M(XGB) model). Accordingly, this study observed the cumulative evaporation (Ep) of a 20 cm standard evaporation pan and set two different irrigation treatments (K0.9: 0.9Ep and K0.5: 0.5Ep). We conducted field measurements of meteorological data inside the greenhouse, tomato physiological and ecological indices, and ET during 2020 and 2021. The above three methods were then used to dynamically simulate greenhouse tomato ET. Results showed the following: (1) In 2020 and 2021, under K0.9 and K0.5 irrigation treatments, the MPT model mean coefficient α for the entire growth stage was 1.27 and 1.26, respectively, while the PT-M model mean coefficient α was 1.31 and 1.30. For both models, α was significantly lower than 1.26 (conventional value) during the seedling stage and the flowering and fruiting stage, rose rapidly during the fruit enlargement stage, and then gradually declined toward 1.26 during the harvest stage. (2) Predicted ET (ETe) using the PT-M model underestimated the observed ET (ETm) by 8.71~16.01% during the seedling stage and the harvest stage, and overestimated by 1.62~6.15% during the flowering and fruiting stage and the fruit enlargement stage; the errors compared to ETm under both irrigation treatments over two years was 0.1~3.3%, with an R2 of 0.92~0.96. (3) The PT-M(XGB) model achieved higher prediction accuracy, with errors compared to ETm under both irrigation treatments over two years of 0.35~0.65%, and R2 above 0.98. The PT-M(XGB) model combined with the XGBoost algorithm significantly improved prediction accuracy, providing a reference for the precise calculation of greenhouse tomato ET. Full article
(This article belongs to the Special Issue Advances in Irrigation and Fertilization Technologies for Sustainable Plant Production)
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