Estimating yield-contributing physiological parameters of cotton using UAV-based imagery.

Lint yield in cotton is governed by light intercepted by the canopy (IPAR), radiation use efficiency (RUE), and harvest index (HI). However, the conventional methods of measuring these yield-governing physiological parameters are labor-intensive, time-consuming and requires destructive sampling. This study aimed to explore the use of low-cost and high-resolution UAV-based RGB and multispectral imagery 1) to estimate fraction of IPAR (IPARf), RUE, and biomass throughout the season, 2) to estimate lint yield using the cotton fiber index (CFI), and 3) to determine the potential use of biomass and lint yield models for estimating cotton HI. An experiment was conducted during the 2021 and 2022 growing seasons in Tifton, Georgia, USA in randomized complete block design with five different nitrogen treatments. Different nitrogen treatments were applied to generate substantial variability in canopy development and yield. UAV imagery was collected bi-weekly along with light interception and biomass measurements throughout the season, and 20 different vegetation indices (VIs) were computed from the imagery. Generalized linear regression was performed to develop models using VIs and growing degree days (GDDs). The IPARf models had R2 values ranging from 0.66 to 0.90, and models based on RVI and RECI explained the highest variation (93%) in IPARf during cross-validation. Similarly, cotton above-ground biomass was best estimated by models from MSAVI and OSAVI. Estimation of RUE using actual biomass measurement and RVI-based IPARf model was able to explain 84% of variation in RUE. CFI from UAV-based RGB imagery had strong relationship (R2 = 0.69) with machine harvested lint yield. The estimated HI from CFI-based lint yield and MSAVI-based biomass models was able to explain 40 to 49% of variation in measured HI for the 2022 growing season. The models developed to estimate the yield-contributing physiological parameters in cotton showed low to strong performance, with IPARf and above-ground biomass having greater prediction accuracy. Future studies on accurate estimation of lint yield is suggested for precise cotton HI prediction. This study is the first attempt of its kind and the results can be used to expand and improve research on predicting functional yield drivers of cotton.

Cotton leafroll dwarf disease: An enigmatic viral disease in cotton.

TAXONOMY: Cotton leafroll dwarf virus (CLRDV) is a member of the genus Polerovirus, family Solemoviridae. Geographical Distribution: CLRDV is present in most cotton-producing regions worldwide, prominently in North and South America. PHYSICAL PROPERTIES: The virion is a nonenveloped icosahedron with T = 3 icosahedral lattice symmetry that has a diameter of 26-34 nm and comprises 180 molecules of the capsid protein. The CsCl buoyant density of the virion is 1.39-1.42 g/cm3 and S20w is 115-127S. Genome: CLRDV shares genomic features with other poleroviruses; its genome consists of monopartite, single-stranded, positive-sense RNA, is approximately 5.7-5.8 kb in length, and is composed of seven open reading frames (ORFs) with an intergenic region between ORF2 and ORF3a. TRANSMISSION: CLRDV is transmitted efficiently by the cotton aphid (Aphis gossypii Glover) in a circulative and nonpropagative manner. Host: CLRDV has a limited host range. Cotton is the primary host, and it has also been detected in different weeds in and around commercial cotton fields in Georgia, USA. SYMPTOMS: Cotton plants infected early in the growth stage exhibit reddening or bronzing of foliage, maroon stems and petioles, and drooping. Plants infected in later growth stages exhibit intense green foliage with leaf rugosity, moderate to severe stunting, shortened internodes, and increased boll shedding/abortion, resulting in poor boll retention. These symptoms are variable and are probably influenced by the time of infection, plant growth stage, varieties, soil health, and geographical location. CLRDV is also often detected in symptomless plants. CONTROL: Vector management with the application of chemical insecticides is ineffective. Some host plant varieties grown in South America are resistant, but all varieties grown in the United States are susceptible. Integrated disease management strategies, including weed management and removal of volunteer stalks, could reduce the abundance of virus inoculum in the field.

Differential sensitivities of photosynthetic processes and carbon loss mechanisms govern N-induced variation in net carbon assimilation rate for field-grown cotton.

Nitrogen (N) deficiency limits the net carbon assimilation rate (AN), but the relative N sensitivities of photosynthetic component processes and carbon loss mechanisms remain relatively unexplored for field-grown cotton. Therefore, the objective of the current study was to define the relative sensitivity of individual physiological processes driving N deficiency-induced declines in AN for field-grown cotton. Among the potential diffusional limitations evaluated, mesophyll conductance was the only parameter substantially reduced by N deficiency, but this did not affect CO2 availability in the chloroplast. A number of metabolic processes were negatively impacted by N deficiency, and these effects were more pronounced at lower leaf positions in the cotton canopy. Ribulose bisphosphate (RuBP) regeneration and carboxylation, AN, and gross photosynthesis were the most sensitive metabolic processes to N deficiency, whereas photosynthetic electron transport processes, electron flux to photorespiration, and dark respiration exhibited intermediate sensitivity to N deficiency. Among thylakoid-specific processes, the quantum yield of PSI end electron acceptor reduction was the most sensitive process to N deficiency. It was concluded that AN is primarily limited by Rubisco carboxylation and RuBP regeneration under N deficiency in field-grown cotton, and the differential N sensitivities of the photosynthetic process and carbon loss mechanisms contributed significantly to photosynthetic declines.