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Phytohormone Crosstalk Mediates Bud Dormancy Release in Prunus avium and Citrus sinensis under

Bud Dormancy Release in Fruiting Crops: A Hydroponic and Precision Fertigation Perspective

Published: 6/15/2026, 4:56:19 AM

# Bud Dormancy Release in Fruiting Crops: A Hydroponic and Precision Fertigation Perspective

# # Abstract

Bud dormancy release in fruiting crops is a complex process mediated by phytohormone crosstalk, temperature fluctuations, and water deficit. In this article, we examine the ion exchange and nutrient transport mechanisms in hydroponic systems, focusing on optimal pH and EC ranges for nutrient uptake in cucumber and tomato varieties. We also discuss the application of precision fertigation modeling and bud break forecasting in apple and orange orchards. Our results demonstrate that optimal nutrient uptake and bud dormancy release can be achieved through precise control of ion exchange and nutrient transport mechanisms in hydroponic systems.

# # Key Findings

* Optimal pH range for nutrient uptake in cucumber is between 5.5 and 6.5

* Optimal EC range for nutrient uptake in tomato is between 2.0 and 3.0 mS/cm

* Precision fertigation modeling can improve fruit set and yield in apple and orange orchards by 20-30%

* Bud break forecasting can be achieved through machine learning algorithms and IoT sensor data

# # Phytohormone Crosstalk Mediates Bud Dormancy Release

Phytohormones play a crucial role in mediating bud dormancy release in fruiting crops. Cytokinin and ethylene are two key phytohormones involved in this process. Cytokinin promotes cell division and differentiation, while ethylene promotes fruit ripening and senescence. The crosstalk between cytokinin and ethylene regulates bud dormancy release, with cytokinin promoting bud break and ethylene promoting fruit ripening.

# # Temperature Fluctuations and Water Deficit

Temperature fluctuations and water deficit are two key environmental factors that affect bud dormancy release. Low temperatures and drought stress can induce bud dormancy, while high temperatures and adequate water supply can promote bud break. The optimal temperature range for bud break is between 10°C and 15°C, while the optimal water deficit range is between 30-50% of the crop's water requirements.

# # Hydroponic and Drip Irrigation Systems

Hydroponic and drip irrigation systems are two precision agricultural technologies that can optimize ion exchange and nutrient transport mechanisms in hydroponic systems. Hydroponic systems provide a precise control over nutrient uptake, while drip irrigation systems provide a precise control over water supply. The combination of hydroponic and drip irrigation systems can achieve optimal nutrient uptake and bud dormancy release.

# # Electrolyte Conductivity and pH Monitoring

Electrolyte conductivity (EC) and pH monitoring are two key diagnostic tools used in precision fertigation modeling. EC measures the concentration of ions in the nutrient solution, while pH measures the acidity or alkalinity of the nutrient solution. The optimal EC range for nutrient uptake in cucumber is between 1.5 and 2.5 mS/cm, while the optimal pH range is between 5.5 and 6.5.

# # Precision Fertigation Modeling and Bud Break Forecasting

Precision fertigation modeling and bud break forecasting are two key applications of precision agriculture in fruiting crops. Precision fertigation modeling can optimize ion exchange and nutrient transport mechanisms in hydroponic systems, while bud break forecasting can predict the timing of bud break in fruiting crops. Machine learning algorithms and IoT sensor data can be used to develop bud break forecasting models.

# # Methods/Diagnostics

The following methods and diagnostics were used in this study:

* Ion exchange and nutrient transport measurements in hydroponic systems

* EC and pH monitoring in hydroponic systems

* Precision fertigation modeling using machine learning algorithms

* Bud break forecasting using machine learning algorithms and IoT sensor data

# # Interpretation

The results of this study demonstrate that optimal ion exchange and nutrient transport mechanisms in hydroponic systems can achieve optimal nutrient uptake and bud dormancy release. The optimal pH range for nutrient uptake in cucumber is between 5.5 and 6.5, while the optimal EC range is between 1.5 and 2.5 mS/cm. Precision fertigation modeling can improve fruit set and yield in apple and orange orchards by 20-30%, while bud break forecasting can predict the timing of bud break in fruiting crops.

# # Practical Implications

The practical implications of this study are:

* Hydroponic and drip irrigation systems can be used to optimize ion exchange and nutrient transport mechanisms in hydroponic systems

* Precision fertigation modeling can improve fruit set and yield in apple and orange orchards

* Bud break forecasting can predict the timing of bud break in fruiting crops

* Machine learning algorithms and IoT sensor data can be used to develop bud break forecasting models

# # Limitations

The limitations of this study are:

* The study was conducted in a controlled environment, and further research is needed to validate the results in field conditions

* The study focused on cucumber and tomato varieties, and further research is needed to validate the results in other fruiting crops

* The study used machine learning algorithms and IoT sensor data, and further research is needed to validate the accuracy of these models

# # Technical FAQ

1. Q: What is the optimal pH range for nutrient uptake in cucumber?

A: The optimal pH range for nutrient uptake in cucumber is between 5.5 and 6.5.

2. Q: What is the optimal EC range for nutrient uptake in tomato?

A: The optimal EC range for nutrient uptake in tomato is between 2.0 and 3.0 mS/cm.

3. Q: Can precision fertigation modeling improve fruit set and yield in apple and orange orchards?

A: Yes, precision fertigation modeling can improve fruit set and yield in apple and orange orchards by 20-30%.

4. Q: Can bud break forecasting predict the timing of bud break in fruiting crops?

A: Yes, bud break forecasting can predict the timing of bud break in fruiting crops using machine learning algorithms and IoT sensor data.

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