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=== 智能灌溉与养分管理 === 水资源管理和施肥策略对香蕉产量和成本有直接影响。AI可以通过物联网(IoT)传感器收集土壤湿度、温度以及作物生长阶段信息,实时评估香蕉对水分和养分的需求,并智能控制灌溉和施肥(即精准灌溉与精确施肥)。实践证明,这种数据驱动的灌溉系统能够明显提高资源利用效率。例如,在印度的一项研究中,研究人员在香蕉园部署了土壤水分传感器和自动灌溉装置,由AI根据传感器读数和天气预测调整灌溉频率和施肥量。结果表明,与传统经验法相比,精准灌溉方案将化肥施用量减少了50%,灌溉用水减少26%,而收益成本比提高到1.61,显示出显著的经济效益 (IoT and Sensor-Based Irrigation: Transforming Banana Farming) (IoT and Sensor-Based Irrigation: Transforming Banana Farming)。这意味着农户用一半的肥料和四分之一本的节约水,就获得了相当或更高的产量和收益。不仅投入成本降低,这种优化还防止过量肥料淋溶浪费,保护土壤和地下水环境 (IoT and Sensor-Based Irrigation: Transforming Banana Farming) (IoT and Sensor-Based Irrigation: Transforming Banana Farming)。对于柬埔寨雨季旱季分明的气候,智能灌溉系统可以在旱季精确供水、防止干旱胁迫,在雨季根据土壤含水量避免过度灌溉,保证香蕉稳产高产并节约水肥开支。
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