Assessing Dry Matter Content of Potato Affected by Irrigating with Fish Effluent Through Sensitivity Analysis of Nutrient Concentration Impact

Fathi, Zeynab, Abyaneh, Hamid Zare, Sedighkia, Mahdi, Maroufpoor, Eisa, and Hosseinpanahi, Farzad (2025) Assessing Dry Matter Content of Potato Affected by Irrigating with Fish Effluent Through Sensitivity Analysis of Nutrient Concentration Impact. Potato Research, 68 (1). pp. 89-109.

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Abstract

The dry matter content (DMC) is a critical factor for assessing the quality of the potato. Using a fish effluent in the sprinkler irrigation has unknown impacts on the DMC of the tuber. Hence, different irrigation treatments were carried out for the irrigation of potato, including T1: fresh water treatment, T2: fish effluent treatment and T3: combined fresh water and fish effluent treatment in which leaf washing was used. A multiple regression model (MLR) was developed in which nutrient concentrations were considered as the input while DMC was the output of the model. The model was evaluated by the root mean squared error (RMSE) as well as the mean absolute percentage error (MAPE). Then, sensitivity analysis of DMC due to changing the nutrient concentration was carried out through regression models by the sensemaker package. The results illustrate that the developed regression model is highly accurate due to low RMSE and MAPE. The results of the sensitivity analysis indicate that the impact of nitrate on the DMC due to adding a confounder is weak. In other words, nitrate can be removed from the list of independent variables for developing regression models to simulate DMC. The results show that the averages of dry matter content in T1, T2 and T3 were 20.26%, 21.53 and 25.72%, respectively. The results indicate that DMC is increased in the irrigation treatment in which leaf washing is used to mitigate the impact of fish effluent. It is recommendable to utilize the leaf washing with fresh water when using fish effluent is planned for irrigating potato.

Item ID: 88248
Item Type: Article (Research - C1)
ISSN: 1871-4528
Keywords: Fish farm effluent, Multiple regression model, Sensemaker package, Washing leaf treatment
Copyright Information: © The Author(s), under exclusive licence to European Association for Potato Research 2024.
Date Deposited: 07 Apr 2026 01:05
FoR Codes: 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3004 Crop and pasture production > 300411 Fertilisers (incl. application) @ 100%
SEO Codes: 26 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 2605 Horticultural crops > 260505 Field grown vegetable crops @ 100%
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