**4. Main issues affecting adoption of precision agriculture in cotton production**

Although PAT improve the efficiency of agricultural practices by reducing overuse of inputs (seed, fertilizer, pesticides, etc.), thus saving money on input costs, it is seen that adoption of PAT remains relatively low in cotton production. Many studies [e.g., [11, 51–57]] have been carried out to analyze the factors affecting the adoption of PAT specifically among cotton producers in recent years since it is stated that PAT are generally more profitable with high-value crops, such as cotton [58]. These studies showed that many factors including socio-demographic, economic, institutional infrastructure, etc., affect the adoption of PAT. The most important of these factors are expressed as the lack of digital infrastructure like internet and electricity, education level and purchasing power of farmers, and societal barriers. Pandey et al. [8] presented some common issues affecting the adaption of PA as data management, hardware cost, lack of information, interoperability, connectivity, and environmental variation (**Figure 8**).

Yield monitors are considered as one of the most important technologies in PA [59]. Also, grid and zone soil sampling and the use of soil survey maps are considered as a significant entry technology into PA [60]. However, the adoption sequence of PAT in cotton production is different from that in grain production because of the lack of reliable yield monitoring technologies for cotton [54, 61]. For example, reliable yield monitors for cotton were not available until 2000, while monitors for grains and oilseeds have been on the market since the early 1990s [62]. Also, in the USDA (US Department of Agriculture) ERS (Economic Research Service), it is stated that yield monitors were used on 72% of the corn area planted in 2010 and 33% of the corn area was mapped using yield monitor-GPS systems, in contrast, it was used on only 4.7% of the cotton area planted in 2007 and only 2.8% of the cotton area planted was mapped with yield monitors [63]. Mooney et al. [64] observed the adoption rate of cotton yield monitors by farms in 2009 as 4%. Larson et al. and Boyer et al. [61, 65] observed the use of yield monitors with GPS in cotton production has risen from

## **Figure 8.**

*Some common issues affecting the adaption of precision agriculture [8].*

2.8% in 2001 to 19% in 2013. This situation significantly affected the adoption and frequency of PAT in cotton production.

Reuters [66] stated that the most important factor influencing the adoption of cotton yield monitors might be the introduction of on-board module builders on cotton harvesters that are paired with yield monitoring technology. Martin and Varco [67] reported that farmers might find value in combining the two technologies because of reduced equipment and labor expenses associated with the elimination of boll buggies and module builders in the harvest equipment complement. Roberts et al. [68] stated that cotton producers' first experience in precision agriculture started with precision soil sampling, not yield monitoring. Walton et al. [69], who analyzed cotton farmer decisions regarding the adoption and abandonment of precision soil sampling as a function of farm and farmer characteristics, observed that farmers with high levels of education, large cotton production areas, and digital skills had an optimistic opinion about future of PA and were more likely to adopt precision soil sampling for cotton production. Lambert et al. [54] analyzed the adaptation of precision soil sampling by cotton producers in thirteen southern states in 2013. They stated that farming experience, farm size, land ownership, variable rate fertilizer, management plans, and the use of soil electrical conductivity devices had significant effects on the adaptation of precision soil sampling. Shafi et al. [70] stated that PA has been used for the last few decades to enhance crops' yield with reduced costs and human effort, although the adoption of these novel techniques by farmers is still very limited owing to the reasons or challenges such as hardware cost, weather variations, data management, literacy rate, connectivity, and interoperability. Esposito et al. [71] reviewed the potential and practical use of the most advanced sensors available in the market for precision weed control. They emphasized that nowadays, especially, PA has rapidly advanced in integrated weed management because of technological innovations in the areas of sensors, computer hardware, nanotechnology, unmanned vehicle systems, and robots that may allow for specific identification of weeds that are present in the field. Lambert et al. [72], who evaluate the factors influencing the timing of grid soil sampling, yield monitoring, and remote sensing adoption by cotton producers using multivariate censored regression, stated that understanding the factors influencing the early adoption of PAT by cotton farmers is important for anticipating technology diffusion over time. They suggested that different factors such as land ownership, farm structure and size, farmer age and education, the purchasing behavior of farmers, and farm location influenced when cotton farmers adopted grid soil sampling, yield monitoring, and remote sensing adoption after these technologies became commercially available. Khanal et al. [73] suggested that special attention is given to the role of farmer expectations, following the adoption of PAT. The researchers observed a significant positive role of meeting "farmer's expectation" about GPS guidance systems in application decisions and its further diffusion within a cotton farm. Also, they stated that income level, farm size, and farming occupation were other important factors in modeling GPS guidance system adoption and application. Takács-György et al. [74], who stated that the adoption of PAT is slow across the world, emphasized that the application of precision crop production is not easy to understand, it requires much attention, precise work, and a wide range of information. They stated that the slow uptake of some elements of the technology could be partly explained by the problematic questions of shifting such as the need for expertise and precision, requiring the documentation and tracking of the procedures, and extra investment. The authors suggested that all kinds of cooperation and strategic collaborations among the farmers, extension services, and providers are important
