Evaluation of Integrated (Irrigation-Fertigation) Measures Taken Against Drought in Potatoes in Terms of Mathematical Modeling of Crop Water Production Functions (CWPF)

As the planet warms, the patterns of rain and heat that farmers have relied on for generations are shifting, bringing longer dry spells and more intense droughts. For crops like potatoes, which are vital to global food security, these changes pose a serious threat. The challenge is not just about keeping plants alive, but about knowing exactly when they need water and nutrients to survive without wasting precious resources. Scientists have long known that plants go through distinct life stages, from sprouting to flowering and finally to producing the tubers we eat. The core idea driving recent research is that a plant's need for water is not constant; it changes depending on which stage of life it is in. If a farmer waters a plant too much or too little at the wrong time, the crop might survive but produce less food or lower-quality potatoes. To solve this, researchers use mathematical models to map out exactly how much water a plant needs at each stage to produce the best harvest. These models act like a guidebook, helping farmers decide when to irrigate and when to hold back, especially when water is scarce.

In a recent study conducted in the Marmara region of Turkey, a researcher set out to test these ideas on potato crops facing real-world drought conditions. They worked in a research field near Bursa, planting a popular industrial potato variety known as Hermes, which is often used for making chips. Over two growing seasons, from 2019 to 2020, the researcher experimented with different strategies. They divided their potato plots into groups and applied water at six-day intervals. Specific plant nutrients—phosphorus, potassium, calcium, and sulfur—were applied via drip irrigation at times corresponding to the potato's four main life stages: the initial vegetative growth, flowering, tuber formation, and the final ripening period. The goal was to see which combination of water and nutrients produced the most potatoes and the highest quality, measured by the amount of solid, dry matter inside the tuber. High dry matter is crucial for potatoes because it means better texture and flavor, especially for processing into chips. The researcher also tracked how much water the plants actually used by measuring the water lost to the air through the leaves and soil, a process known as evapotranspiration.

The researcher found that the potatoes were not equally sensitive to water shortages at every stage of their life. The most critical time for water was when the tubers were forming. If the plants did not get enough water during this specific window, the yield dropped significantly. The flowering stage and the early vegetative growth were also important, but slightly less so than the tuber formation period. Surprisingly, the final ripening stage was the time when the potatoes could handle the least amount of water without suffering a major loss in total weight. This means that a farmer could potentially save a significant amount of water by reducing irrigation during the very end of the season without hurting the total harvest size. However, the study revealed a complex trade-off regarding quality. While giving the plants plenty of water throughout the entire season produced the highest total weight of potatoes, it actually lowered the quality. The more water the plants received, the lower the dry matter content became, resulting in potatoes that were less dense and potentially less suitable for processing.

To make sense of these results, the researcher tested five different mathematical models to see which one could best predict the relationship between water use and potato production. These models are essentially different ways of calculating how a plant's growth responds to water stress. The researcher compared the predictions from each model against the actual data they collected from the field. They discovered that two specific models, known as the Rao and Minhas models, were far more accurate than the others. These two models correctly predicted how the potatoes would respond to water shortages at each stage, matching the real-world observations with remarkable precision. The other models tended to be less reliable, either overestimating or underestimating the impact of water stress. This finding is significant because it gives agricultural planners a better tool for decision-making. By using the more accurate models, farmers can create irrigation schedules that maximize the amount of food produced while minimizing the amount of water used.

The study also highlighted the importance of timing when it comes to nutrients. The researcher applied specific nutrients via drip irrigation at times corresponding to the four different phenological stages alongside the regular water schedule to help the plants resist drought. They found that while these nutrients helped, the timing of the water application remained the dominant factor in determining the final outcome. The data showed that in years with heavy rainfall, the plants were less sensitive to water stress, but in drier years, the differences between the irrigation strategies became much more pronounced. The researcher concluded that for the Marmara region, and likely for similar climates, the best approach is to focus water resources on the tuber formation stage. They also noted that while the models are powerful tools, they need to be tested and adjusted for different local conditions to ensure they remain accurate. The work provides a clear path forward for managing potato crops in a warming world, showing that careful, science-based water management can help farmers maintain both high yields and high quality even when the rains are unreliable.