Proposed regulations mandating lower nicotine concentrations in tobacco (Nicotiana tabacum L.) products will likely require changes in tobacco production to reduce nicotine while maintaining yield and quality. The agronomic practices used for tobacco production have a significant impact on the synthesis and accumulation of nicotine in flue‐cured tobacco. Nicotine is the primary alkaloid in flue‐cured tobacco and is one of the main reasons for its commercial production. Most agronomic practices that improve plant health and yield have a positive effect on nicotine production and accumulation. Some of the most important factors that affect nicotine concentrations are N fertilization, planting density, topping practices, sucker control, and harvesting practices. The amount of N available to the plant has a substantial effect on nicotine, as N is a primary component of the nicotine molecule. Factors leading to higher N uptake lead to higher nicotine concentrations. Plant and leaf densities within the field also have a significant effect on nicotine, where increasing densities leads to lower nicotine concentrations. Flowering and sucker production are both significant sinks of energy and other resources. Eliminating the inflorescence via topping and controlling suckers lead to higher nicotine concentrations. In fact, substantial nicotine synthesis and accumulation occurs in the days and weeks following topping. This comprehensive review discusses the agronomic factors affecting alkaloid production in flue‐cured tobacco, and how these factors can be adjusted to manipulate the ultimate nicotine concentration.Core Ideas Proposed regulations may require lower tobacco nicotine concentrations. Production practices and timing significantly influence nicotine and leaf quality. Nitrogen fertility, crop density, growth regulation, and harvesting are paramount. Low density, high N, and increased maturity enhance nicotine accumulation. Flowers and axillary shoots are sinks that limit foliar nicotine concentrations.

Essential plant nutrients are needed at crop-specific concentrations to obtain optimal growth and yield. Foliar tissue analysis is the standard method for assessing nutrient levels in plants. Symptoms of nutrient deficiency or toxicity occur when the foliar tissue values become too low or high. Diagnostic nutrient deficiency criteria for Brassica rapa var. Chinensis (bok choy) is lacking in the current literature. In this study, green (‘Black Summer’) and purple (‘Red Pac’) bok choy plants were grown in silica sand culture, with control plants receiving a complete modified Hoagland’s all-nitrate solution, and nutrient-deficient plants induced by using a complete nutrient formula withholding a single nutrient. Tissue samples were collected at the first sign of visual disorder symptoms and analyzed for dry weight and nutrient concentrations of all plant essential elements. Six weeks into the experiment, the newest matured leaves were sampled for chlorophyll a, b, and total carotenoids concentrations for both cultivars, and total anthocyanin concentration in ‘Red Pac’. Compared to control plants, the dry weight of ‘Black Summer’ green bok choy was significantly lower for nitrogen (N), phosphorus (P), calcium (Ca), or boron (B) deficiency treatments, and nutrient concentrations were lower for all variables except iron (Fe) deficiency. Dry weight was less in ‘Red Pac’ plants grown without N, potassium (K), Ca, B, or molybdenum (Mo), and nutrient concentrations were lower for all except Mo-deficiency compared to controls. Total chlorophyll and total carotenoid concentrations were lower in leaves from N−, Fe-, and manganese- (Mn) deficient plants of both cultivars. Leaf anthocyanin concentration was lower only for K-, Ca-, and B-deficiencies in ‘Red Pac’. Our results indicate that visual symptoms of nutrient deficiency are well correlated with nutrient disorders. In contrast, changes in dry weight, chlorophyll, and anthocyanin did not show consistent changes across nutrient disorders.

Deriving crop information from remotely sensed data is an important strategy for precision agriculture. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool that can provide precisely-timed, fine-grained data for informing management responses to intra-field crop variability (e.g., nutrient status and pest damage). UAS sensors with high spectral resolution used to compute informative vegetation indices, however, are practically limited by high cost and data dimensionality. This research extends spectral analysis for remote crop monitoring to investigate the relationship between crop health and 3D canopy structure using low-cost UAS equipped with consumer-grade RGB cameras. We used flue-cured tobacco as a case study due to its known sensitivity to fertility variation and nutrient-specific symptomology. Fertilizer treatments were applied to induce plant health variability in a 0.5 ha field of flue-cured tobacco. Multi-view stereo images from three UAS surveys collected during crop development were processed into orthoimages used to compute a visible band spectral index and photogrammetric point clouds using Structure from Motion (SfM). Plant structural metrics were then computed from detailed high resolution canopy surface models (0.05 m resolution) interpolated from the photogrammetric point clouds. The UAS surveys were complimented by nutrient status measurements obtained from plant tissues. The relationships between foliar nitrogen (N), phosphorus (P), potassium (K), and boron (B) concentrations and the UAS-derived metrics were assessed using multiple linear regression. Symptoms of N and K deficiencies were well captured and differentiated by the structural metrics. The strongest relationship observed was between canopy shape and N foliar concentration (adj. $r^2$ = 0.59, increasing to adj. $r^2$ = 0.81 when combined with the spectral index). B foliar concentration was consistently better predicted by canopy structure with a maximum adj. $r^2$ = 0.41 observed at the latest growth stage surveyed. Overall, combining information about canopy structure and spectral reflectance increased model fit for all measured nutrients compared to spectral alone. These results suggest that an important relationship exists between relative canopy shape and crop health that can be leveraged to improve the usefulness of low cost UAS for precision agriculture.

A series of experiments investigated the effects of increasing phosphate–phosphorus (P) concentrations on the growth and development of four horticultural species. In experiment 1, petunia [ Petunia atkinsiana (Sweet) D. Don ex W.H. Baxter] plants were grown using eight P concentrations, and we found that the upper bound for plant growth was at 8.72–9.08 mg·L ⁻¹ P, whereas concentrations ≤2.5 mg·L ⁻¹ P caused P deficiency symptoms. Experiment 2 investigated P growth response in two cultivars each of New Guinea impatiens ( Impatiens hawkeri W. Bull) and vinca [ Catharanthus roseus (L.) G. Don]. Growth for these plants was maximized with 6.43–12.42 mg·L ⁻¹ P. In experiment 3, ornamental peppers ( Capsicum annuum L. ‘Tango Red’) were given an initial concentration of P for 6 weeks and then switched to 0 mg·L ⁻¹ P to observe whether plants could be supplied with sufficient levels of P, and finished without P to keep them compact. Plants switched to restricted P began developing P deficiency symptoms within 3 weeks; however, restricting P successfully limited plant growth. These experiments indicated that current P fertilization regimens exceed the P requirements of these bedding plants, and depending on species, concentrations of 5–15 mg·L ⁻¹ P maximize growth.

Remote sensing of nutrient disorders has become more common in recent years. Most research has considered one or two nutrient disorders and few studies have sought to distinguish among multiple macronutrient deficiencies. This study was conducted to provide a baseline spectral characterization of macronutrient deficiencies in flue-cured tobacco (Nicotiana tabacum L.). Reflectance measurements were obtained from greenhouse-grown nutrient-deficient plants at several stages of development. Feature selection methods including information entropy and first and second derivatives were used to identify wavelengths useful for discriminating among these deficiencies. Detected variability was primarily within wavelengths in the visible spectrum, while near-infrared and shortwave-infrared radiation contributed little to the observed variability. Principal component analysis was used to reduce data dimensionality and the selected components were used to develop linear discriminant analysis models to classify the symptoms. Classification models for young, intermediate, and mature plants had overall accuracies of 92%, 82%, and 75%, respectively, when using 10 principal components. Nitrogen, sulfur, and magnesium deficiencies exhibited greater classification accuracies, while phosphorus and potassium deficiencies demonstrated poor or inconsistent results. This study demonstrates that spectral analysis of flue-cured tobacco is a promising methodology to improve current scouting methods.