Detection and prevalence of Cryptosporidium in irrigation water, soil, and fresh produce : spiking experiments and environmental monitoring

There are four datasets, two detailing the materials and methods used in the study and two presenting the results obtained. These datasets provide a comprehensive overview of the experimental design, data collection, and findings.

1. Dataset 1: Materials and Methods – Spiking Trials
   This file contains detailed information on the methodology used for spiking Cryptosporidium oocysts into distilled water, commercial soil, and RTE spinach and lettuce. The methodology included sample spiking, DNA extraction and molecular detection using both Real-Time PCR and Droplet Digital PCR (ddPCR).
2. Dataset 2: Results – Spiking Trials
   This dataset presents the results obtained from the spiking trials, including recovery rates, detection efficiencies using real-time PCR and ddPCR, and variations across different sample matrices.
3. Dataset 3: Materials and Methods – Environmental Detection
   This file describes the protocols used for detecting Cryptosporidium in environmental samples collected from the water-soil-plant nexus from smallholder farms in South Africa. It details the sampling strategy, DNA extraction methods, and molecular detection techniques applied. The methodology involved collecting water, soil, and fresh produce samples from various farms and sample processing. Thereafter, DNA extraction using the best methods from results from dataset 2 and molecular detection using both Real-Time PCR and Droplet Digital PCR (ddPCR) were performed.
4. Dataset 4: Results – Environmental Detection
   This dataset contains the findings from environmental sample testing, including Cryptosporidium prevalence in various matrices.