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Optimal Seed Rates for Crop Yield: Precision agriculture and PLS calculations.


Seed rates, defined as the quantity of seeds sown per unit area, significantly impact agricultural production. Proper seed rate selection is pivotal for attaining optimal plant populations and maximizing potential yield. This study explores the factors that influence seed rates, the application of precision agriculture in determining optimal seed rates, and the benefits and drawbacks of various seeding methods and crop combinations.



Introduction

Seed rate selection is crucial for balancing crop population and yield potential. Over-seeding can lead to resource competition, while under-seeding may end in diminished yields. Precision agriculture, which employs historical crop performance data, soil conditions, remote sensing and drone data, and environmental factors, has demonstrated utility in determining ideal seed rates. Furthermore, variable rate seeding technology enables seed rate adjustments based on soil variability and other field-specific conditions.




Determinants of Seed Rates

Seed rates are influenced by several factors including seeding machinery, seedbed conditions, planting depth, purity of live seed ratio, crop purpose, water availability, yield potential, seed price, and planting time. Moreover, the leaf area of the crop, cultivar characteristics, and crop type significantly affect planting pattern.


Seeding Methods

Common seeding methods include grain drills, cultipacker seeders, fluid seeders (for forage legumes), band seeding, and broadcast seeding. The complexities of forage crop establishment, owing to factors such as small seed size, higher percentage of hard seed in legumes, and planter adjustments' criticality for small seeds, often necessitate earlier seeding dates.


Seed Rates for Major Crops

The recommended seeding rates for major crops are as follows:

Corn:

  • Seeding depth: 1.5 to 2.5 inches

  • Seeding rate: Target a final stand of 26,000 to 34,000 plants per acre (ppa); seeding rates should be 5 to 10% higher than target plant populations.

  • Planting time: Usually late March to mid-April, depending on soil temperature (at least 50°F).

Soybeans:

  • Seeding depth: 1 to 1.5 inches

  • Seeding rate: 150,000 ppa for full-season and 200,000 ppa for double-crop.

  • Planting time: Generally, early May when soil temperature has reached 50 to 55°F.

Cotton:

  • Seeding depth: 0.75 to 1.25 inches

  • Seeding rate: 32,000 to 43,000 ppa for non-irrigated fields and 43,000 to 54,000 ppa for irrigated fields.

  • Planting time: Mid-April to early June, depending on soil temperature (at least 65°F).

Peanuts:

  • Seeding depth: 1 to 2 inches

  • Seeding rate: 4 to 6 seed per foot of row or around 100 to 120 lbs per acre

  • Planting time: Mid-April to mid-May, depending on soil temperature (at least 68°F).

Wheat:

  • Seeding depth: 1 to 2 inches

  • Seeding rate: 1.3 to 1.5 million ppa (30 plants/sqft); increase with delayed seeding.

  • Planting time: Mid-October to early November for winter wheat.

Apple:

  • Planting depth: The graft union should be 2 to 4 inches above the soil line.

  • Spacing: 10 to 20 feet apart for dwarf varieties, 18 to 25 feet apart for semi-dwarf varieties, and 25 to 35 feet apart for standard varieties.

  • Planting time: Late winter to early spring when the trees are dormant.

Peach:

  • Planting depth: The graft union should be 2 to 3 inches above the soil line.

  • Spacing: 15 to 20 feet apart for standard varieties and 10 to 12 feet apart for dwarf varieties.

  • Planting time: Late winter to early spring when the trees are dormant.

Blueberry:

  • Planting depth: The same depth as they were in the nursery, with the root crown slightly above the soil line.

  • Spacing: 4 to 5 feet apart for highbush blueberries, and 6 to 8 feet apart for rabbiteye blueberries, with rows spaced 10 to 12 feet apart.

  • Planting time: Late fall to early spring when the plants are dormant.


Pure Grass versus Mixed Stands

Mixed stands offer several advantages, including improved management, higher yields, enhanced nitrogen supply from legumes to grasses, better adaptation in variable soil conditions, and increased resistance to soil erosion. Despite these benefits, the necessity of managing cutting and fertility for multiple cultivars and potential for soil heaving in pure stands present notable drawbacks.

The Impact of Drone Technology on Seed Rates

The application of drone technology in agriculture, specifically multispectral imaging and digital surface models (DSMs), has revolutionized the determination of seed rates. These tools provide high-resolution spatial data which allows for improved decision-making in seed rate selection, enhancing both efficiency and yield.


Drone Imagery and Mapping


Drone imagery and mapping have been instrumental in providing high-resolution spatial data that are valuable for determining appropriate seed rates. These technologies enable real-time monitoring of field conditions, offering invaluable insights on soil fertility, moisture levels, and pest or disease presence. These factors are critical in determining the optimum seed rate for a particular field, as they directly influence seed germination and the subsequent growth and development of the crop.


The spatial data obtained from drones provide a more detailed understanding of field variability, enabling farmers to adopt precision farming practices such as variable rate seeding. This method allows for the adjustment of seed rates based on the specific conditions of different sections of a field, promoting resource efficiency and potentially increasing overall crop yield.


Multispectral Imaging

Multispectral imaging, a technique that captures image data at specific frequencies across the electromagnetic spectrum, offers unique insights into plant health and soil properties that are not discernible through the naked eye. For instance, this technology can identify nutrient deficiencies, water stress, and disease presence, which significantly impact seed germination and growth.


By determining the health and vigor of a crop, multispectral imaging can inform adjustments to seed rates for the following growing season. Furthermore, real-time data from multispectral imaging can aid in managing current crop growth, enabling farmers to mitigate issues swiftly and potentially salvage their yield.


Digital Surface Models (DSMs)

DSMs, which provide a topographic model of the earth's surface, are an additional tool offered by drone technology that can influence seed rates. These models allow for the visualization and quantification of field variations, such as changes in elevation, slope, and surface roughness, that may impact the suitability of certain areas for planting. (Refer to our article on the RUSLE https://www.aeroagsc.com/post/harnessing-the-power-of-drones-and-rusle-to-optimize-soil-conservation).


For instance, areas with steep slopes or surface depressions may require different seed rates due to variations in water availability and retention. Understanding these variations allows for the application of seed rates tailored to specific field conditions, thus optimizing plant populations and potential yield.


Drone technology, through high-resolution drone imagery, multispectral imaging, and DSMs, has significantly advanced the process of determining seed rates. By offering a detailed understanding of field conditions and crop health, these technologies enable farmers to adopt precision agriculture practices, ultimately promoting efficiency and maximizing yield.



Pure Live Seed (PLS) and the Role of Drone Technology

Defining Pure Live Seed (PLS)

Pure Live Seed (PLS) is a measure of the proportion of viable seeds in a seed lot, serving as an indicator of the quality of the seed stock. The PLS calculation involves multiplying the purity percentage by the germination percentage. Purity percentage refers to the proportion of desired seed type in a seed lot, while germination percentage represents the proportion of seeds that can germinate under ideal conditions.


Thus, if an alfalfa seed lot has a purity of 99% and a germination rate of 90%, the PLS percentage is calculated by multiplying 0.99 (purity) by 0.90 (germination), yielding a PLS value of 0.89 or 89%. This means that 89% of the seed lot comprises viable alfalfa seeds. PLS plays a crucial role in determining the amount of seed required per acre to achieve the desired plant population, accounting for both purity and germination rates.


Drone Technology and PLS

While traditionally PLS is determined through laboratory tests, drone technology offers potential to inform these calculations and their practical applications. With the high-resolution data provided by drone imagery and multispectral imaging, it's possible to assess the germination success of a seed lot after it has been sown.


Through periodic drone surveys during the early growth stages, farmers can monitor the emergence of seedlings, enabling an evaluation of the germination percentage in the field conditions. This real-world data can provide a more accurate measure of germination success, reflecting the impact of environmental and soil conditions on seed germination and growth.


Moreover, through drone imagery, farmers can identify sections of the field with poor seedling emergence, suggesting areas where the seed may not have been viable, or where conditions may not have been suitable for germination. This data can be used to adjust the calculations of PLS for future plantings, ensuring a more accurate seeding rate that will achieve the desired plant population.


Additionally, drone technology can be beneficial in validating the purity percentage of a seed lot. For instance, multispectral imaging can potentially differentiate between plant species based on their unique spectral signatures. Through this technology, farmers can detect the presence of weed seedlings or other undesired plant species in their fields, suggesting a lower purity percentage in the seed lot.


Drone technology not only provides an enhanced understanding of field conditions for improved seed rate determination but also holds the potential to inform the calculations of PLS, enhancing the accuracy of seed rate adjustments for optimal crop yield.



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