Low-cost GPS (Global Positioning System) speed sensors have been available to quantify vehicle speed on different platforms including agricultural tractors in precision agriculture applications such as yield monitoring, variable rate fertilizer and pesticide applications. One of the advances in low-cost GPS receivers is the higher data update frequencies. However, we found no studies on the accuracy of low-cost GPS speed sensors with different update frequencies, especially under variable speed conditions. Thus, this work investigated the effect of the update frequency on the accuracy of low-cost GPS speed sensors under both constant and varying speed conditions. Three GPS speed sensors with update frequencies of 1 Hz, 5 Hz and 7 Hz (GPS1Hz, GPS5Hz and GPS7Hz) were simultaneously tested under the same conditions. A total of 144 tests were conducted on three different days and at three different times of each day with four speed levels and four repetitions. The percent errors were found to be up to 2.3%, 1.8% and 1.4% at constant speeds; up to −47%, −16% and −12% at the increasing speeds and 24%, 6% and 5% at the decreasing speeds, depending on the acceleration and deceleration levels, for GPS1Hz, GPS5Hz and GPS7Hz, respectively. The differences among the error values of the GPS speed sensors were found to be statistically significant (p < 0.05). The GPS speed sensors with higher update frequencies (5 and 7 Hz) provided higher accuracy compared to the one with lower frequency (1 Hz), particularly in the case of higher acceleration conditions. In sum, low-cost GPS speed sensors with higher update frequencies should be used for better accuracy, especially in variable speed conditions.

Hassas tarım (HT), toprak işlemeden hasada kadar tarımsal faaliyetlerin verimliliğini ve kârlılığını artırmayı, doğal kaynakların ve çevrenin korunmasını ve böylelikle sürdürülebilirliği hedefleyen ileri teknolojileri içerir. Otomatik dümenleme (OD), dünyada ve Türkiye'de en yaygın kullanılan ve birçok fayda sağlayan HT teknolojisidir. OD; sırta toprak işleme ve ekim dâhil olmak üzere tarımsal işlemlerde verimli ve sürdürülebilir uygulamalara imkân sağlar. Makinalı hassas ekimde, her bitkiye eşit yaşam alanı sağlamak için bitki sıra aralarında yeterli boşluk gereklidir. Bu nedenle makinalı ekimde paralel yan yana geçişlerde bitki sıra arası mesafesi (BSAM) eşit olmalıdır. Ekimde eşit BSAM sağlamak için OD'nin faydalarına ilişkin yapılan araştırmalar oldukça sınırlıdır. Bu çalışma, üç farklı sinyal düzeltme kaynağı (RTK, CORS, SBAS) kullanan GNSS esaslı OD ile ekimde yan yana paralel geçişlerdeki PIRS sapmalarını karşılaştırmak amacıyla yapılmıştır. Çalışmada OD kullanılmayan (manuel yönlendirmeli) tarlalardaki BSAM değerleri de karşılaştırma amacıyla incelenmiştir. Veriler, Çukurova bölgesinde, sıra arası mesafe değerleri 70-75 cm olan 24 çiftçi tarlasından (pamuk ve mısır) elde edilmiştir. Paralel yan yana geçişlerdeki BSAM değerleri manuel olarak ölçülmüş ve ayarlanan değerden olan sapmalar hata kareler ortalamasının karekökü (RMSE) değeri ile analiz edilmiştir. Manuel dümenlemeli ekimde ortalama BSAM sapmaları (7.4 cm), OD ile yapılan sırta toprak işleme ve/veya ekime göre daha yüksek bulunmuştur (CORS: 5.0 cm, SBAS: 5.9 cm, RTK: 6.7 cm) (p<0.05). Özetle, OD teknolojisinin yan yana paralel geçişlerde BSAM değişimlerini azaltmada fayda sağladığı ancak fayda düzeyinin çiftçiden çiftçiye değiştiği belirlenmiştir. Bu nedenle, ileri düzeyde faydalar elde edebilmek için OD sistemleri uygun ayarlarla dikkatli bir şekilde kullanmalıdır. Precision agriculture (PA) includes advanced technologies to increase efficiency and profitability of agricultural operations from tillage to harvest and offers sustainability of the natural resources and the environment. Automatic steering (AS) is the mostly-used PA technology in the world and in Türkiye providing many benefits. It has potential for efficient and sustainable agronomic practices including soil ridge tillage and sowing. Adequate spacing is needed to provide equal living area for each plant in sowing. Thus, in mechanized planting, pass-to-pass plant inter-row spacing (PIRS) should be equal in parallel passes. Research on the benefits of the AS for providing uniform PIRS in sowing is very limited. This work aimed to appraise the pass-to-pass PIRS deviations in planting with GNSS-based AS with three signal correction sources (RTK, CORS, SBAS) and without AS (manual steering) for comparison. The data were obtained from 24 farmer fields (cotton and corn) with PIRS set values of 70-75 cm located in the Cukurova region of Türkiye. Pass-to-pass PIRS values were manually measured and the deviations from the set value were analyzed in terms of root mean square error (RMSE). The mean PIRS variations in sowing by manual steering (7.4 cm) were found as significantly higher than the AS based soil ridge tillage and / or sowing (CORS: 5.0 cm, SBAS: 5.9 cm, RTK: 6.7 cm) (p<0.05). In sum, it was found that the AS technology offers benefits in lowering the pass-to pass PIRS variations but the level of benefit changes from farmer to farmer; hence, the AS should be used cautiously with proper settings for greater benefits.

Background: Pistachio 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.Aim: This 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.Methods: The 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.Results: It 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).Conclusion: In 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.

Chemical soil and plant analyses are time-consuming, expensive, and labor-intensive. There are some optical systems used for this purpose; however, they are expensive and require expertise for their operation. The aim of this study was to develop a low-cost prototype optical sensor and compare it with three commercial systems (GreenSeeker NDVI (Normalized Difference Vegetation Index) meter, chromameter, Fourier transform-near infrared reflectance spectroscopy (FT-NIRS)) to determine water and nutrient concentrations including nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn) of turfgrass (Lolium perenne L.). Study was conducted on an experimental field to which four different levels of nitrogen fertilizer were applied. Prediction models were developed using PLSR (Partial Least Square Regression) and their performances were evaluated using the criteria of SEP (Standard Error of Prediction) and R². With the prototype optical sensor, NDVI gave the best result among 10 different vegetation indices for the prediction of water (SEP = 1.43%) and N (SEP = 0.28%). The best results (lowest SEP) were obtained with the FT-NIRS. However, there are some disadvantages of this system along with the other two instruments (chromameter and NDVI meter) of being expensive and requiring expertise in their operation. Low-cost and easy-to-use prototype optical sensor gave similar results with the NDVI meter and chromameter to predict water and nutrient concentrations except K, Cu, and Zn. An optical sensor similar to the prototype sensor could be developed commercially with low cost and used to estimate the water and nutrient concentration of turfgrass.