Peanuts (Arachis hypogaea L.) originated from South America and are now grown in every continent but Antarctica. Within the U.S. this crop is grown in Southeastern US on about 600 thousand hectares, averaging 4500 kg/ha [1] . Peanuts were shown to have health benefits that protect cardio systems and have an overall healthy nutrient profile. They are rich in unsaturated fatty acids in the form of monosaturated fatty acids. These healthy fats found in peanuts and tree nuts contribute to the prevention of coronary heart disease and diabetes when consumed frequently. Consumption is also reported to lower cholesterol. Peanuts and tree nuts are also good sources of vegetable protein and fiber, potassium, calcium, magnesium, tocopherols, phytosterols, phenolic compounds, resveratrol, and arginine [2] . Studies show that peanuts, peanut butter, and peanut oil significantly reduce heart disease risk when consumed daily [2] .

As the demand for organic products in the U.S. increased, the same trend occurred for organic peanuts and processed peanut foods [3] [4] [5] [6] . Consumption of organic peanut products is health promoting because it provides high quality nutrients required for human health. This is considered the fastest-growing sector in the peanut industry and there was a supply shortage of nearly 5000 tons of organic peanut in the U.S. [4] [5] [7] [8] . It is predicted that if the demand for organic peanuts increases like that of other organic products, then there will be a need for 125,000 tons in 15 years [6] .

Economic incentives exist for organic peanut production, but there are additional costs and lower yields experienced in organic systems due to certification costs, weed management, and diseases with restricted chemical use. During the time of a study conducted by Wann et al. [9] , certified organic runner-type peanut contract prices were reaching $1100/Mg compared to $390/Mg for conventional runner-type peanuts. Numerous runner-type peanut cultivars with excellent disease resistance and productive capacities in organic production have been released [10] [11] [12] .

Manual phenotyping for traits that can predict pod yield, disease resistance, and drought tolerance has been used for many years by breeders. For example, early biomass accumulation and leaf area index are shown to be correlated with pod yield under drought stress in peanuts [13] [14] [15] [16] . In addition, canopy coverage and structure can affect both disease resistance and water use, which in turn affect yield [17] [18] . Previous studies showed that reduced biomass, caused by drought stress, resulted in significant pod yield losses [19] [20] [21] .

Direct manual phenotyping of traits for pod yield is used extensively but is time consuming, expensive, and challenging to do on a large scale. However, utilizing unmanned aerial system (UAS) to phenotype traits for predicting peanut yield would be of interest [22] . This is due to UAS utilization allowing the gathering of precise and very detailed imagery for making breeding decisions such as canopy height and canopy volume in a short time with minimal labor involved [23] .

Unmanned aerial vehicles (UAVs) have been used in peanuts to monitor seedling emergence rate, variety selection, maturity variability on irrigated and rainfed fields, early detection of bacterial wilt, drought tolerance phenotyping, and canopy height measurements [23] - [29] . However, this has not been done for a certified organic field to predict peanut yield, which would be a valuable tool for organic peanut breeders. Therefore, the objective of this study was to assess the accuracy of UAS data to phenotype pod and seed yield using organic Spanish-type peanuts which can be identified and released in the future.

Pod and seed yield data were taken at the end of the season. The seed yield was 56.5% less than the pod yield. This could be due to having pods that weren’t completely full and some which had small seeds. The seed weight collected for each line was that of the ELK, medium, and #1 seeds during grading. During grading, anything that falls through all three screens (for ELK, medium, and #1) is then subjected to further grading as being splits, ok, damaged/diseased, and foreign matter. Hence, not every seed was included in the seed weight. A lot of variation was observed among the different lines for pod and seed yield as indicated

by the large standard deviation value. This could be due to genetic differences. NDRE, SRRE, and CIRE use RE and NIR values to be calculated. During Flight 1, even though RE and NIR are smaller than Flight 2 they are also further apart from each other instead of being equal. This difference accounts for NDRE, SRRE, and CIRE being higher during Flight 1 than Flight 2.

Genotypes had a statistically significant effect on pod and seed yield as well as all twenty-five vegetation indices calculated. This is due to the variation seen among the 16 breeding lines and 4 commercial cultivars involved and not due to the environment.

Overall, the red edge (RE) vegetation index correlated the best with both pod and seed yield based on data from the first flight on July 07, 2021, and a correlation was not present between pod and seed yield from Flight 2 data taken September 27th, 2021. The two flights were 2 months and 20 days apart so there may not have been a lot of change in plant growth during that time and even with the average RE and NIR values, in Table 1, these values were equal during Flight 2 unlike Flight 1. Hence, the peanut plants may have been in the reproductive phase during Flight 2 and not growing as much as they were already established.

The study done by Sarkar et al. [29] , measuring canopy height in peanuts found that the red-green-blue (RGB) aerial images which derived canopy height were highly correlated to manually measured height data (R2 = 0.953). We gathered canopy information quickly using UAS as red edge (RE) looks at the vegetation reflectance and with more vegetation present, the image becomes redder. In this study, genotypic differences were observed based on the twenty-five vegetation indices which can be used to develop a way to distinguish one variety from another as suggested for guar and soybean cultivars [31] [32] . This will give breeders the ability to identify varieties faster as previously reported by Balota and Oakes [25] who used a UAS platform for variety selection in peanuts. Further studies involving more breeding lines will aid in building learning models which can improve the estimates obtained for seed and pod yield.

Overall, genotypic effects on pod and seed yield were statistically significant. Also, genotypic effects on all twenty-five vegetation indices were significant during both flights. Red edge (RE) is a good indicator of pod and seed yield for the 20 lines tested, based on UAS data collected earlier during the growing season. Since there was no correlation during the second flight, temporal analysis of vegetation indices to model both pod and seed yield in organic peanuts are needed.

This project was funded in part by the National and Texas Peanut Producers Board, the USDA Hatch Accession Number 1025956, the USDA Multi-State Hach 7003209, and the Governor’s University Research Initiative grant.

The authors declare no conflicts of interest regarding the publication of this paper.

Manley, A., Ravelombola, W., Cason, J., Bennett, B., Pham, H., Kimura, E., Ruhl, C., Ahmad, W. and Brown, M. (2023) Use of Unmanned Aerial System (UAS) Phenotyping to Predict Pod and Seed Yield in Organic Peanuts. American Journal of Plant Sciences, 14, 415-426. https://doi.org/10.4236/ajps.2023.143027