**1. Introduction**

Upland cotton (*Gossypium hirsutum* L.) is an important crop in the lower Mississippi River Basin (MRB) of the United States (US) that includes the states of Louisiana, Mississippi, Missouri, and Tennessee [1].

Cotton area planted in the four states was 700,405 ha in 2019 [2]. Nitrogen (N) is the plant nutrient most often applied in the largest amounts by farmers growing upland cotton [3,4]. Nitrogen is especially important for lint yield formation after the cotton plant's first bloom [5]. Under application of fertilizer N reduces lint yield and profit. However, over application of fertilizer N in cotton increases fertilizer costs and can also cause excessive vegetative plant growth rather than increased production of cotton bolls that contribute to lint yield and profit [6]. Excessive vegetative growth can decrease lint yield due to boll rot and insects, reduce lint fiber quality, and cause increased expenses due to additional applications of pesticides and plant growth regulators to prevent lint yield losses [6].

Over application of fertilizer N can also negatively affect water quality. Nitrogen, especially in the form of nitrates, can leach from farm fields into surface and ground water [7]. This may be especially true if farmers apply a uniform N rate across individual fields. Efficient N managemen<sup>t</sup> on fields in the lower MRB is an important priority for the US Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) [1]. The goal of the USDA NRCS is to reduce nutrient and sediment loading to local and regional water bodies and to improve water use efficiency. The USDA NRCS promotes the use of variable rate N (VRN) managemen<sup>t</sup> to apply different rates of fertilizer N across farm fields based upon soil N and crop needs through the Environmental Quality Incentives Program (EQIP) [8]. However, by 2017, only 9.5% of upland cotton growers adopted VRN [9]. Grower uncertainty about the profitability of managing soil N spatial and temporal variability may be an important factor influencing VRN adoption by farmers [10].

Optimal fertilizer N managemen<sup>t</sup> depends on the amount of available N derived from the soil and fertilizer [11]. Complex interactions between land use, crop management, landscape characteristics, soil properties, and weather influence N soil availability to plants [12]. Soil properties and soil N can vary substantially within farm fields [11]. Alluvial soils in the floodplains of the lower MRB (USDA NRCS Major Land Resource Area 131) frequently exhibit significant variation in texture and N availability [6]. Loess soils are common on cotton fields located in the lower MRB (USDA NRCS Major Land Resource Area 134) and are subject to water-induced soil erosion because of the rolling landscapes upon which these soils occur in the region [13]. Soils redistributed by water-induced soil erosion cause variation in a field's soil properties and, consequently, field soil N [14].

Rainfall and temperature also interact with soil and landscape attributes to cause spatial and temporal variability of soil N that complicates cotton N managemen<sup>t</sup> [15]. Soil testing for N is unreliable in the warm, humid climate of the lower MRB because soil N varies greatly with soil organic matter, soil texture, tillage, and other factors [16]. Consequently, lower MRB cotton growers generally do not completely rely on soil test information to manage N [6]. Growers and their crop consultants develop a single (uniform) rate for the field using Land Grant University fertility recommendations, their experience, and other considerations, including cotton variety, soil texture, and crop rotation.

Given the unreliability of N soil tests, plant-based measurements can be used to determine crop demand for N. For example, in-season N status can be assessed using visual inspection of plants for N deficiency symptoms, petiole NO3-N or leaf tissue sampling, or chlorophyll meters to determine N status in the growing cotton for in-season fertilizer N applications up to the early bloom stage [16,17]. However, assessing plant N status using hand-held devices is labor intensive and may not provide sufficient information to determine N rates for VRN management. Ground-based optical sensing (OS) of the growing crop canopy facilitates assessment of crop N status throughout the field and provides growing spatial plant canopy data useful for determining VRN rates that vary across the field [11,17].

Most of the studies evaluating OS-based VRN reported crop yields similar to yields for the uniform fertilizer N rate (i.e., conventional or farmer practice) [18–25]. Thus, an important factor driving the profitability of OS-based VRN is lower fertilizer N rates relative to the uniform rate. Researchers have reported fertilizer N savings with OS-based VRN of as much as 69 kg ha−<sup>1</sup> [22]. However, other studies have reported increased applications of fertilizer N relative to the uniform rate of as much as 84 kg ha−<sup>1</sup> with OS-based VRN [24]. Researchers evaluating the economic feasibility of OS-based VRN have found mixed profitability results. Studies that reported a lack of profitability found similar yields but did

not find su fficient fertilizer N cost savings to provide a profit [18–20,24]. Research reporting positive profitability through enhanced yields and N cost savings did not include the costs of OS information and VRN application [22,23,25]. Costs of information used to produce the VRN prescription and VRN application costs are also important factors influencing the profitability of the technology [26]. VRN managemen<sup>t</sup> may also mitigate yield and profit risk compared to uniform N managemen<sup>t</sup> by reducing the probability of yield or profit below a threshold level [27,28].

Farmers are often unwilling to adopt technologies such as OS-based VRN unless they see the potential for positive profits [26]. This is especially a problem for N managemen<sup>t</sup> in the lower MRB because plant response to N is influenced by landscape, soil, and weather characteristics. Quantifying how spatial and temporal factors affect yields, N use, profitability, and the risk managemen<sup>t</sup> potential of VRN may be useful to cotton farmers in the lower MRB interested in adopting OS-based VRN. The objective of this research was to determine how landscape, soil, and weather influence fertilizer N use, lint yields, and profitability of OS-based VRN for cotton in the lower MRB.
