Comparison between Field Measured and UAV-Derived Pistachio Tree Crown Characteristics throughout a Growing Season

Jacygrad, Ewelina; Kelly, Maggi; Hogan, Sean; Preece, John E.; Golino, Deborah A.; Michelmore, Richard W.

doi:10.3390/drones6110343

Cited by 3 publications

(3 citation statements)

References 48 publications

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“…Given the recent surge in interest around pistachios, numerous researchers have started leveraging unmanned aerial vehicles (UAVs) for pistachio management, employing aerial imagery for comprehensive field oversight. In this way, Jacygrad et al [34] used UAVs equipped with multispectral imaging to track the crown characteristics (height, size, shape, and NDVI) of pistachio trees throughout the growing season and compared UAV-derived metrics with the corresponding measurements taken in the field, highlighting the value of UAV imaging for comprehensive and real-time orchard management. Similar to our research, the study reported the highest NDVI value in June, when most trees registered between 0.9 and 1, nearing NDVI saturation.…”

Section: Discussionmentioning

confidence: 99%

“…Only a few studies have demonstrated the potential of using images for managing pistachio crops in the field. For instance, Jacygrad et al [34] exploited the power of Unmanned Aerial Vehicles (UAVs) to capture the seasonal changes of pistachio tree crowns in a pistachio orchard, providing valuable insights into tree characteristics. Vélez et al [35] developed an innovative method that leverages the shadows cast by the canopies of pistachio trees to estimate their volume in a cost-effective manner.…”

Section: Introductionmentioning

confidence: 99%

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Remote Sensing for Sustainable Pistachio Cultivation and Improved Quality Traits Evaluation through Thermal and Non-Thermal UAV Vegetation Indices

et al. 2023

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Pistachio (Pistacia vera L.) has earned recognition as a significant crop due to its unique nutrient composition and its adaptability to the growing threat of climate change. Consequently, the utilization of remote sensing techniques for non-invasive pistachio monitoring has become critically important. This research was conducted in two pistachio orchards located in Spain, aiming to assess the effectiveness of vegetation indices (VIs) in estimating nut yield and quality under various irrigation conditions. To this end, high-resolution multispectral and thermal imagery were gathered using a Micasense ALTUM sensor carried by a DJI Inspire 2 drone in order to calculate the NDRE (normalized difference red edge index), GNDVI (green normalized difference vegetation index), NDVI (normalized difference vegetation index), and CWSI (crop water stress index). Each orchard underwent two flights at distinct growth stages, totaling four flights. In June, NDRE-carbohydrates (r = 0.78) and CWSI-oleic (r = 0.77) showed the highest correlations, while in September, CWSI-carbohydrates (r = 0.62) and NDVI-iron (r = 0.54) Despite NDVI’s limitations due to saturation effects, all VIs had significant yield and quality correlations, with GNDVI proving most effective in both flights. CWSI correlated considerably on both dates in terms of several quality parameters (carbohydrate percentage, magnesium, iron, and fatty acids, namely palmitoyl, stearic, oleic, and linoleic), surpassing non-thermal indices. Finally, it is important to consider the impact of environmental factors, such as the location of the sun, when interpreting the CWSI, as it modifies the temperature distribution pattern within the canopy. This study supports the viability of remote sensing and vegetation indices as potential tools for enhancing the management of pistachio orchards.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Remote Sensing for Sustainable Pistachio Cultivation and Improved Quality Traits Evaluation through Thermal and Non-Thermal UAV Vegetation Indices

et al. 2023

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“…Mani and Shanmugam (2019) In pistachio farming, NIR spectroscopy has been applied to assess traits like adulteration, infection, and moisture content. However, its integration with precision agriculture systems remains limited (Jacygrad et al, 2022;Yaghoubi et al, 2022). In particular, no study was found on the utilization of NIRS for the assessment of nutrient levels of pistachio tree leaves.…”

Section: Introductionmentioning

confidence: 99%

Rapid and cost‐effective assessment of nutrients in pistachio (Pistacia vera L.) leaves through Fourier transform near‐infrared spectroscopy (FT‐NIRS)

Sekerli,

Buyuk,

Keskin

et al. 2024

J. Plant Nutr. Soil Sci.

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BackgroundPistachio nuts provide many health benefits in human diet. Nutrient levels in plant leaves and fertilizer schedules are determined based on traditional soil and leaf chemical analyses. However, these methods require additional labor, time, and cost, which is why most farmers do not prefer them and cannot detect nutrient deficiencies in time. Fast, easy‐to‐use and low‐cost nutrient level assessment techniques are needed.AimThis study aims to explore the viability of near‐infrared reflectance spectroscopy (NIRS) as a fast, user friendly, and cost effective technique for evluating the major macro‐ and micronutrient contents of dried and ground pistachio leaf sample.MethodsThe feasibility of NIRS for estimating nutrient contents was investigated by analyzing samples from 200 pistachio trees. Dried and ground pistachio leaves were subjected to NIRS analysis. PLSR (Partial least square regression) analyses were performed to develop nutrient content prediction models using spectral information of samples.ResultsIt was found that the NIRS system had a very good potential to estimate the K, Ca, Cu, and Mg contents of the leaf samples (R2 > 0.80). It was also found that Fe and Mn concentrations could also be estimated with good accuracy (R2 = 0.70–0.80). However, the NIRS system did not give good results for the prediction of N, P, and Zn (R2 < 0.40).ConclusionIn conclusion, the NIRS system can be used to quickly, easily, and economically assess the K, Ca, Cu, Mg, Fe, and Mn contents of dried and ground pistachio leaves. This technique has the potential to improve nutrient management practices in pistachio farming within a sustainable and environmentally conscious framework. Fourier transform NIRS (FT‐NIRS) can provide valuable insights by complementing rather than replacing traditional chemical analysis. Laboratory analysis is still required for definitive nutrient content information, but FT‐NIRS can significantly reduce the reliance on such analysis, thereby mitigating the environmental impact caused by the excessive use of chemical fertilizers and minimizing the health risks to laboratory staff. In addition, the rapid information‐gathering capabilities of the FT‐NIRS can be emphasized.

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UAV Autonomous Navigation Based on Deep Reinforcement Learning in Highly Dynamic and High-Density Environments

Sheng,

Liu,

et al. 2024

Drones

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Autonomous navigation of Unmanned Aerial Vehicles (UAVs) based on deep reinforcement learning (DRL) has made great progress. However, most studies assume relatively simple task scenarios and do not consider the impact of complex task scenarios on UAV flight performance. This paper proposes a DRL-based autonomous navigation algorithm for UAVs, which enables autonomous path planning for UAVs in high-density and highly dynamic environments. This algorithm proposes a state space representation method that contains position information and angle information by analyzing the impact of UAV position changes and angle changes on navigation performance in complex environments. In addition, a dynamic reward function is constructed based on a non-sparse reward function to balance the agent’s conservative behavior and exploratory behavior during the model training process. The results of multiple comparative experiments show that the proposed algorithm not only has the best autonomous navigation performance but also has the optimal flight efficiency in complex environments.

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Comparison between Field Measured and UAV-Derived Pistachio Tree Crown Characteristics throughout a Growing Season

Cited by 3 publications

References 48 publications

Remote Sensing for Sustainable Pistachio Cultivation and Improved Quality Traits Evaluation through Thermal and Non-Thermal UAV Vegetation Indices

Remote Sensing for Sustainable Pistachio Cultivation and Improved Quality Traits Evaluation through Thermal and Non-Thermal UAV Vegetation Indices

Rapid and cost‐effective assessment of nutrients in pistachio (Pistacia vera L.) leaves through Fourier transform near‐infrared spectroscopy (FT‐NIRS)

UAV Autonomous Navigation Based on Deep Reinforcement Learning in Highly Dynamic and High-Density Environments

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