On the basis of the existing query algorithms in wireless sensor networks, with the target to extend the life cycle, the energy-efficient query algorithms for moisture sensor networks based on fine-grain gradient (EEQA-FGG) was proposed by binding the excellent idea of the aggregation tree with location-assisted querying. Further more, three sub-modules of EEQA-FGG about query routing, query processing, and query unconventionality processing were designed in detail. The EEQA-FGG in regional query and whole network query from small to ultra-large-scale network was simulated, and was compared with aggregation tree query and location-assisted query. Simulation shows that EEQA-FGG can effectively reduce energy consumption, uniform network load and extend network life cycle, and it is especially suitable for large-scale farmland monitoring data query. Particularly in regional query, the life cycle of EEQA-FGG is longer than SPT querying and Compass querying by 10% to 50%. 