{"id":51148,"date":"2023-01-13T12:54:56","date_gmt":"2023-01-13T12:54:56","guid":{"rendered":"https:\/\/dev.metos.global\/?p=51148"},"modified":"2023-06-21T08:02:36","modified_gmt":"2023-06-21T08:02:36","slug":"farm-weather-talk-003-yield-prediction","status":"publish","type":"post","link":"https:\/\/metos.global\/en\/farm-weather-talk-003-yield-prediction\/","title":{"rendered":"Farm Weather Talk #003 \u2013 Yield Prediction"},"content":{"rendered":"\t\t
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Just because you kick some soil around in the spring and guess that you have enough soil moisture, you really have no idea what\u2019s actually going on until you dig down and take a look (which takes time) or use IoT technology (easier approach) to know what you have. Here comes Yield Prediction.<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Yield Prediction – Dig that?<\/h2>

In the\u00a0second installment of Farm Weather Talk<\/a><\/span>, we discussed the benefits of\u00a0site-specific weather forecasts<\/a><\/span>\u00a0and why they are\u00a0a must<\/strong>\u00a0for integration into all farm-field decision support tools since they are a part of the solution to reduce the \u201cUncontrollable Risk\u201d that farmers face on a day-by-day basis. In this installment, we are going to dig into how a\u00a0weather station<\/a><\/span>\u00a0or IoT device with a\u00a0forecast<\/a><\/span> can be used to make yield prediction to the current date but also to maturity.<\/p>

\"Yield<\/p>

Just because you kick some soil around in the spring and guess that you have enough soil moisture, you really have no idea what\u2019s actually going on until you dig down and take a look (which takes time) or use IoT technology (easier approach) to know what you have. Soil type-specific data can be collected and translated into exactly where you are at in terms of soil moisture in a water-driven crop yield and provide a very good answer to a particular problem, such as nutrition. If you know you only have five inches of stored water versus nine inches of stored water in a different soil profile, you are going to manage nutrients and the crop differently.<\/p><\/blockquote>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Yield Prediction Backgrounds<\/h3>

The yield of any crop is based on the genetic potential of the seed, the amount of soil moisture at seeding, growing season precipitation (and irrigation), proper fertility rates and other timely management decisions: weed control, disease management, insect control and of course weather factors<\/a><\/span> which is usually the most significant uncontrollable risk.<\/p>

In simplistic terms, a plant or crop development is very similar to a checkbook (inputs and outputs), where you have supplied (precipitation and\/or irrigation) and demand (temperature) side. Therefore, the two most important factors for yield are moisture supply and temperature, given that all other field management decisions are carried out properly.<\/p>

Temperature or heat is important since it determines the water use and whether a crop will mature or suffer heat stress, but the moisture supply has the most significant impact on yield potential since its responsible for carrying nutrients to the plant for photosynthesis. This is why moisture supply is often referred to as the\u00a0CROPS GAS TANK<\/strong>\u00a0for yield potential.<\/p>

Each crop has water use efficiency curves related to yield. Research and field trials over years have identified the number of bushels produced from each inch or 25mm of soil water used by a crop. For some common crops this equates to 5-6 bu in canola, 7-8 bu for wheat and 10 to 12 bu of corn yield increase for each additional inch or 25mm of soil water added. The number of bushels produced per inch or 25 mm of soil water will change over time as new varieties are released with better genetics.<\/p>

Therefore, the total amount of soil water available (supply) to a crop during the growing season is equal to the amount of soil moisture available at seeding time (determined by soil type) plus the amount of precipitation and\/or irrigation (soil moisture) received over the growing season. The use or demand of soil water is determined by temperature and soil type\/texture. These two factors (supply and demand) define the yield potential.<\/p>

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As mentioned, soil type\/texture is a critical factor in determining how much soil water plants have available for development. In fact, plants can\u2019t use all the water held in the soil. The upper limit is Field Capacity, while the lower limit is Permanent Wilting Point.<\/p>

Field Capacity<\/strong>\u00a0is the maximum amount of water held in the soil, measured a couple of days after a saturation event (heavy rainfall or irrigation event).<\/p>

Permanent Wilting Point<\/strong>\u00a0occurs if a plant can longer withdraw water from the soil to meet its needs, then it will begin to wilt, that is the point at which water is no longer available to the plant.<\/p>

Plant Available Water<\/strong>\u00a0is the difference between field capacity and the wilting point where the plant can no longer extract water from the soil. In other words, not all water held in soil is available to plants.<\/p>

This is why an\u00a0Allowable Depletion level<\/strong>\u00a0is used based on soil type and crop. In most cereal and oilseed crops, the allowable depletion levels are 50% of field capacity, while for vegetables and root crops, this level is at 65% of field capacity.<\/p>

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The illustration clearly shows that sand or sandy loam soil has limited soil water available for crop development, while a silt loam or clay loam has a much larger gas tank of soil water, and hence higher yield potential typically. In other words, the sandy loam soil needs to be recharged more often than clay loam soil. The table below illustrates that coarse soil can store 5.7 inches (145 mm) of water to 4 feet or 120 cm, while fine soil can store 10.4 inches (265 mm) of water in the same depth of profile.<\/p>

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Ok, we\u2019ve talked about the factors that drive yield in a crop, but how do we make an estimate of yield to the current date and then to maturity for a field? This is where the field IoT device<\/a><\/span> and forecast<\/a><\/span> come in.\u00a0Let\u2019s explore how this is done.<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Yield Prediction Setup<\/h3>

First, you need to spatially define the field location or Cropzone(s) that you want to make the yield estimate for. The illustration below shows how this is done, by defining the cropzone within a field. Cropzones are usually defined based on soil type and topography.<\/p>

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Since we are using a model to predict water use by the crop, we need to set several parameters:\u00a0crop type, seeding and expected harvest date, best possible average yield, initial soil moisture, soil type, field capacity and wilting point, air temperature station and rain source as shown in the illustration below<\/strong>.<\/p>

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For the\u00a0selection of IoT devices<\/strong>, the temperature is used to estimate crop development, while the precipitation gauge is used to capture the amount of water added to the soil. So, the station with the precipitation gauge should be in or at the edge of the field to make sure that the values are representative of that field.<\/p>

The temperature device can be on the same station or from a station that is nearby, since temperature does not change much over a short spatial distance like precipitation. The illustrations below show two types of stations that can be used\u00a0\u00b5METOS<\/a><\/span>\u00a0or\u00a0nMETOS<\/a><\/span>\u00a0for this type of application.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The initial soil moisture is important since it sets how much soil water is available at the time of seeding based on the soil type (how much water is in the gas tank at the start of the year). Changing these two values will create different yield scenarios (planning tools) for the cropzone.<\/p>

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Yield Prediction Results<\/h3>

Ok, we discussed the importance of having an IoT device with a forecast to help reduce the uncontrollable risk farmers face, but how does this work for yield prediction?<\/p>

For the yield prediction solution, we use\u00a0Long Term Normal forecast<\/strong>\u00a0(average normal rainfall) to the current date and to physiological maturity. We also use a\u00a0Seasonal Adjust forecast<\/strong>\u00a0which uses the observed conditions (precipitation) to date plus a seasonal adjusted forecast based on the type of season (wet, normal, or dry). These terms and illustrations are described below.<\/p>

Terms Used on the Yield Prediction Graph:<\/h4>