Cotton Phenology Research Articles

Fuzzy clustering for the within-season estimation of cotton phenology.

Crop phenology is crucial information for crop yield estimation and agricultural management. Traditionally, phenology has been observed from the ground; however Earth observation, weather and soil data have been used to capture the physiological growth of crops. In this work, we propose a new approach for the within-season phenology estimation for cotton at the field level. For this, we exploit a variety of Earth observation vegetation indices (derived from Sentinel-2) and numerical simulations of atmospheric and soil parameters. Our method is unsupervised to address the ever-present problem of sparse and scarce ground truth data that makes most supervised alternatives impractical in real-world scenarios. We applied fuzzy c-means clustering to identify the principal phenological stages of cotton and then used the cluster membership weights to further predict the transitional phases between adjacent stages. In order to evaluate our models, we collected 1,285 crop growth ground observations in Orchomenos, Greece. We introduced a new collection protocol, assigning up to two phenology labels that represent the primary and secondary growth stage in the field and thus indicate when stages are transitioning. Our model was tested against a baseline model that allowed to isolate the random agreement and evaluate its true competence. The results showed that our model considerably outperforms the baseline one, which is promising considering the unsupervised nature of the approach. The limitations and the relevant future work are thoroughly discussed. The ground observations are formatted in an ready-to-use dataset and will be available at https://github.com/Agri-Hub/cotton-phenology-dataset upon publication.

Evaluating Climate Change Impacts on Cotton Phenology and Yield Under Full and Deficit Irrigation Conditions in an Extremely Arid Oasis

Evaluating Climate Change Impacts on Cotton Phenology and Yield Under Full and Deficit Irrigation Conditions in an Extremely Arid Oasis

Cotton phenology and production response to sowing time, row orientation and plant spacing using CROPGRO-cotton model

The DSSAT module for cotton crop has been evaluated as a tool to predict the crop growth and yield response to microclimatic modifications. In this context, multi-location field experiments were laid out at Bathinda and Faridkot, districts of Punjab during Kharif 2018 with Bt-cotton hybrid RCH 773 BGII and sown at three times, i.e., April 30, May 15 and May 30 with two row orientations (North-South : N-S and East-West : E-W) and three plant spacing’s (67.5 cm × 45.0 cm, 67.5 cm × 60.0 cm and 67.5 cm × 75.0 cm) in factorial split plot design and replicated by three times. The model output in terms of simulated phenology showed close proximity over observed value having R2 of 0.51 and 0.61 at Bathinda and 0.43 and 0.87 at Faridkot anthesis and maturity, respectively. Among study locations, observed and simulated LAI ranged from 2.7 to 3.7 and 1.8 to 3.0. Simulated seed cotton yield was found significantly higher with the crop sown on 30th April (3053 and 3274 kg ha-1) than 30th May sowing (2392 and 2511 kg ha-1) at Bathinda and Faridkot, respectively, which was in good agreement with observed yield having higher value of d-stat (0.84 for Bathinda and 0.89 for Faridkot) and R2 (0.75 for Bathinda and 0.83 for Faridkot). Moreover, higher seed cotton yield was simulated under East-West row direction along with wider plant spacing (67.5 × 75 cm) at both locations. Overall, CROPGRO-cotton model can be used as research tool for the prediction of cotton phenology and yield and to explore site-specific adoption strategies such as appropriate sowing time, row orientation and plant spacing to sustain cotton productivity under changing climatic conditions.

Impact of climate change and crop management on cotton phenology based on statistical analysis in the main-cotton-planting areas of China

Phenology is one of the prominent indicators for studying the impact of climate change on crop production. Based on cotton phenology and meteorological data from 79 agricultural weather stations in China between 1981 and 2017, the Pearson correlation, multi-variate linear regression and path analysis are applied to investigate the spatial and temporal changes of cotton phenological indices and climate variables (precipitation (Pre), sunshine duration (Sun), average (Tave), minimum (Tmin) and maximum temperatures (Tmax), influence degrees of Pre, Sun, and Tave on phenology, and isolated effects of climate change and crop management on cotton phenology. The results showed that: (1) Emergence (Eme), squaring (Squ), flowering (Flo), and boll opening (Bol) dates of cotton advanced by 0.026–0.351 days year−1, respectively. The cotton sowing (Sow) and maturity (Mat) dates were delayed by 0.170 and 0.337 days year−1. The average phenological stages from Sow-Eme, Squ-Flo, and Flo-Bol were shortened about 0.19–0.30 days year−1, Eme-Squ, Bol-Mat and the Sow-Mat were delayed by 0.11, 0.77, and 0.082 days year−1, respectively. (2) Pre had a positive effect on most of the lengths phenological stages of cotton except during Bol-Mat. The effect of Sun on the length of the various phenological stages of cotton was the opposite of that of Pre. Tave, Tmin, and Tmax on the general negative effects on the length of the cotton phenological stages. (3) Pre, Sun, and Tave had different influence degrees on the cotton phenological stages because of different regional climate characteristics. (4) The impact of climate change on cotton phenology was weaker than crop management or combined effects of climate change and crop management. Under the combined impacts, and isolated impact of crop management, the lengths of the stages from Sow-Eme and Squ-Flo were shortened while other phenological stages were extended. The isolated impact of climate change shortened the lengths of stages from Sow-Eme, Eme-Squ, and Flo-Bol, extended Squ-Flo, Bol-Mat, and Sow-Mat, implying that the longer-duration cotton varieties in a changing climate might be a better choice for planting. This could be a viable strategy for adapting to climate change. In addition, the study found that Seed cotton yield (Scy) decreased with the delay of Sow, Eme, Squ, Flo and Bol dates, increased with the increase of the lengths of Sow-Eme, Flo-Bol, Bol-Mat and Sow-Mat. And the change trend of Scy affected by climate change was less than that affected by crop management or combined effects.

Colonization and Spatial Distribution of Boll Weevil in Commercial Cotton Fields.

The departure and arrival of boll weevil in cotton fields have fostered major control decisions against this pest over time. Field colonization and distribution of boll weevil were evaluated using cotton fields from 93.7 to 154ha each, located in Serra da Petrovina and Campo Verde, both in the Cerrado biome of Mato Grosso State, Brazil, as a function of cotton field bordering vegetation and crop phenology. The monitoring of adult weevils was carried out using traps containing sex and aggregation pheromone. The traps were set up considering the four coordinates of the field, bordering vegetation, and distances from the field margin. Six traps were set in each direction with three representing the field margin (0m, 60m, and 120m from the borderline) and the other three set up equidistant from the center of the field (> 200m). Traps were evaluated weekly beginning 10days after plant emergence (DAE) throughout the cotton phenology until harvesting. Boll weevils were caught in the first evaluation 10 DAE, irrespective of the vegetation bordering the cotton field and distance of trap from field margin. The average weevils per trap was relatively low throughout the crop development but increased significantly through the maturation and harvesting periods. Furthermore, the bordering vegetation was not the only determinant factor for boll weevil colonization and distribution throughout the cotton field. Based on these data, boll weevil exhibited early colonization, already occurring beyond the border of the field.

Modelling responses of cotton growth and yield to pre-planting soil moisture with the CROPGRO-Cotton model for a mulched drip irrigation system in the Tarim Basin

Pre-planting soil moisture plays an important role in regulating plant emergence rate and yield, yet there is a paucity of studies on the response of cotton growth and yield to pre-planting soil moisture in arid regions. In this study, the CROPGRO-Cotton model was used to simulate cotton growth and yield in a mulched drip irrigation system, with the interaction of different pre-planting soil water contents and irrigation levels during the cotton growing season. This was undertaken to determine the optimal pre-planting soil water contents and irrigation levels that would produce the highest cotton yield and biomass values in the model simulations. Experimental data of cotton phenology, and the biomass and yield at the maturing stage in 2017 and 2018 was used to calibrate and verify the DSSAT-CROPGRO-Cotton model outputs. Based on the calibrated CROPGRO-Cotton model, scenario simulation was performed using three irrigation levels (24 mm, 30 mm, 36 mm) and eight pre-planting soil water contents [1.2 θFC, 1.1 θFC, θFC (field water holding capacity), 0.9 θFC, 0.8 θFC, 0.7 θFC, 0.6 θFC, and 0.5 θFC]. The results showed that the simulated cotton phenology and seed cotton yield produced by the calibrated CROPGRO-Cotton model showed good fits with the observed values, thus, satisfying the accuracy requirement for large-scale, mulched, drip irrigated cotton field simulations. However, large deviations were observed between simulated and observed biomass values. According to the simulations, the maximum seed cotton yield and biomass can be obtained from a pre-planting soil water content of 0.8 θFC - θFC, and the maintenance of irrigation levels at 30–36 mm during the cotton growing season. These simulation results may serve as reference data for cotton crop production and irrigation management in the Tarim Basin.

Characterization of Intercrop Movement of <em>Lygus hesperus</em> between Cotton and Alfalfa

Lygus hesperus Knight (Miridae: Hemiptera), a key pest of cotton in the United States, is a highly polyphagous insect. Upland cotton (Gossypium hirsutum L. var. hirsutum) and alfalfa (Medicago sativa L.) are two major field crop hosts of Lygus hesperus in the Texas High Plains. While alfalfa is considered a source of Lygus in cotton, Lygus intercrop movement behavior has not been fully characterized in cotton-alfalfa systems. Understanding the intercrop movement behavior of Lygus may facilitate better decision-making for Lygus management in these crops. A series of studies including a mark-release-recapture study and season-long field monitoring of Lygus were conducted in the Texas High Plains, USA. Season-long field marking and monitoring of Lygus intercrop movement revealed bidirectional Lygus movement and confirmed that Lygus preferred alfalfa over cotton. Net movement of Lygus between cotton and alfalfa was influenced by cotton phenology. A “two-crop/two-marker” field-marking and monitoring approach was successfully applied in characterizing Lygus seasonal intercrop movement. This approach can be used to study the effect of various crop management practices on Lygus intercrop movement and is applicable to other pests and cropping systems.

Evaluating Optimal Spray Timing, Planting Date, and Current Thresholds for Lygus lineolaris (Hemiptera: Miridae) in Virginia and North Carolina Cotton.

Economically damaging infestations of Lygus lineolaris (Palisot de Beauvois) (Hemiptera: Miridae), the tarnished plant bug, have been increasing in North Carolina and Virginia cotton since 2009. We conducted experiments to compare prophylactically timed sprays based on cotton phenology and current action thresholds based on sweep net and drop cloth sampling. In the second year of the study, we included planting date as a factor, with early and late-planted cotton. We found L. lineolaris nymph densities were reduced by at least 60% in North Carolina and 74% in Virginia in threshold plots when compared with the untreated control. Protecting the crop from first square through the fourth week of bloom afforded at least 30% control across planting dates in Virginia and at least 40% control in North Carolina. Economic returns were two to three times greater in early-planted cotton than in late-planted cotton. Treating cotton at action threshold or using prophylactic sprays from first square until the sixth week of bloom in early-planted cotton yielded over $500/ha in net returns in both North Carolina and Virginia. This study supports previous research that shows controlling L. lineolaris infestations during squaring and early weeks of flowering is critical for maximizing yield potential. Our findings also suggest that prebloom and bloom thresholds based on adult and nymphal density devised in the Mid-South may need revision in North Carolina and Virginia.

Does the Introgression of Bt Gene Affect Physiological Cotton Response to Water Deficit?

ABSTRACT: Water deficit may affect the expression of lepidoptera-controlling proteins in cotton. However, it is unknown if there is a differential response of conventional and Bt cotton cultivars to water deficit, what could potentially affect the plant competition with weeds. The objective of this work was to investigate the response of Bt cotton cultivars to water deficit compared with their conventional near-isolines. The experiment was conducted in a greenhouse, where the cotton cultivars FMT 705, FMT 709 and IMACD 8276, with and without the Bt gene, were grown under two water regimens: 100% and 50% (moderate water deficit) of available soil water. Cotton phenology was severely affected by moderate water deficit, with a reduction in shoot and root dry matter production, root length and diameter, plant height and leaf area. No effect of the Bt gene was observed. Water deficit during cotton flowering decrease stomatal conductance, net assimilation of CO2 and transpiration rates. The leaf water potential is lower in plants exposed to a moderate water deficit compared with non-stressed plants. However, the introgression of the Bt gene does not modify cotton physiological and phenotypic response to water deficit.

Caractéristiques de l’évolution spatio-temporelle de Thaumatotibia leucotreta Meyrick (Lepidoptera : Tortricidae) dans les zones de production cotonnière de Côte d’Ivoire

In order to update knowledge on the spatio-temporal evolution of Thaumatotibia leucotreta, the geographical areas and seasons of predilection of adult and larval populations have been studied in the last six years from 2012 to 2017. Monitoring of natural adult populations revealed that populations were more abundant in the southern cotton production area as compared to the north. A Monitoring of larval infestations showed that infestations occurred on cotton at the end of august (0.10 larvae/100 bolls) and increased gradually during october-november (0.31 to 0.93 larvae/100 bolls), indicating a strong relationship between evolution of adult and larval populations and cotton phenology. Early sowings exhibited higher infestation levels (0.87 larvae/100 bolls). Annual variations of pest infestation levels increased from years to years, from 0.23 to 0.49 larvae/100 bolls over the study period. Mapping the geographic distribution of infestations showed highest pest densities in the southern zone, mostly in surrounding areas of Boron (1.52 larvae/100 bolls). With regard to the emerging status of T. leucotreta over recent years, the current pyrethroid resistance management strategy deserves to be improved on the basis of the pest geographic and seasonal profiles.

Response of cotton phenology to climate change on the North China Plain from 1981 to 2012

To identify countermeasures for the impacts of climate change on crop production, exploring the changes in crop phenology and their relationship to climate change is required. This study was based on cotton phenology and climate data collected from 13 agro-meteorological experimental stations and 13 meteorological stations on the North China Plain from 1981 to 2012. Spatiotemporal trends in the cotton phenology data, lengths of the different growing phases, mean temperatures, and rainfall were analyzed. These results indicated that warming accelerated cotton growth, advanced cotton phenology, and shortened the growing period of cotton. However, harvest dates were significantly delayed at 8 (61.5%) stations, the length of both the flowering-boll opening and boll opening-harvest periods increased at 10 (77.0%) stations, and a positive correlation was found between the mean temperature and the length of the whole growing period at 10 (77.0%) stations. Therefore, cotton practices and cultivars on the North China Plain should be adjusted accordingly. The response of cotton phenology to climate change, as shown here, can further guide the development of options for the adaptation of cotton production in the near future.

Quantification of Climate Warming and Crop Management Impacts on Cotton Phenology.

Understanding the impact of the warming trend on phenological stages and phases of cotton (Gossypium hirsutum L.) in central and lower Punjab, Pakistan, may assist in optimizing crop management practices to enhance production. This study determined the influence of the thermal trend on cotton phenology from 1980–2015 in 15 selected locations. The results demonstrated that observed phenological stages including sowing (S), emergence (E), anthesis (A) and physiological maturity (M) occurred earlier by, on average, 5.35, 5.08, 2.87 and 1.12 days decade−1, respectively. Phenological phases, sowing anthesis (S-A), anthesis to maturity (A-M) and sowing to maturity (S-M) were reduced by, on average, 2.45, 1.76 and 4.23 days decade−1, respectively. Observed sowing, emergence, anthesis and maturity were negatively correlated with air temperature by, on average, −2.03, −1.93, −1.09 and −0.42 days °C−1, respectively. Observed sowing-anthesis, anthesis to maturity and sowing-maturity were also negatively correlated with temperature by, on average, −0.94, −0.67 and −1.61 days °C−1, respectively. Applying the cropping system model CSM-CROPGRO-Cotton model using a standard variety in all locations indicated that the model-predicted phenology accelerated more due to warming trends than field-observed phenology. However, 30.21% of the harmful influence of the thermal trend was compensated as a result of introducing new cotton cultivars with higher growing degree day (thermal time) requirements. Therefore, new cotton cultivars which have higher thermal times and are high temperature tolerant should be evolved.

Seasonal and inter-annual variations in carbon fluxes and evapotranspiration over cotton field under drip irrigation with plastic mulch in an arid region of Northwest China

Xinjiang is the largest semi-arid and arid region in China, and drip irrigation under plastic mulch is widely used in this water-limited area. Quantifying carbon and water fluxes as well as investigating their environmental drivers over cotton fields is critical for understanding regional carbon and water budgets in Xinjiang, the largest cotton production basin of China. In this study, an eddy covariance (EC) technique was used to measure the carbon and water fluxes of cotton field under drip irrigation with plastic mulch in the growing seasons of 2009, 2010, 2012 and 2013 at Wulanwusu Agrometeorological Experiment Station, a representative oasis cropland in northern Xinjiang. The diurnal patterns of gross primary production (GPP), net ecosystem exchange (NEE) and evapotranspiration (ET) showed obviously sinusoidal variations from June to September, while the diurnal ecosystem respiration (Res) was stable between daytime and nighttime. The daytime hourly GPP and ET displayed asymptotic relationships with net solar radiation (Rnet), while showed concave patterns with raising vapor pressure deficit (VPD) and air temperature (Ta). The increases in hourly GPP and ET towards the maximum occurred over half ranges of VPD and Ta. The seasonal variations of GPP, NEE and ET were close to the cotton phenology, which almost reached the peak value in July. The cumulative GPP averaged 816.2±55.0 g C/m2 in the growing season (from April to October), and more than half of GPP was partitioned into NEE (mean value of −478.6±41.4 g C/m2). The mean seasonal ET was 501.3±13.9 mm, and the mean water use efficiency (WUE) was 1.0±0.1 (mg C/g H2O)/d. The agro-ecosystem behaved as a carbon sink from squaring to harvest period, while it acted as a carbon source before the squaring time as well as after the harvest time.

Prediction of cotton yield and water demand under climate change and future adaptation measures

Cotton is the main cultivated cash crop in Northwest China. This study is motivated by the challenge of economically growing cotton in the face of climate change, which could lead to changes in cotton variety, phenology, water demand, heat requirement and yield. The APSIM-OzCot crop growth model is used to simulate cotton cultivation at two sites with different climatic conditions (Shihezi and Alaer, Xinjiang Province). The model is fully calibrated and validated using observations. Simulations forced with future climate data downscaled from the HadCM3 Global Climate Model show that the response of cotton phenology, yield and water use to climate change is different for different cultivation, sites, greenhouse gas emission scenarios and time horizons. Under the SRES A1B and B1 emissions scenarios, cotton yield and water use are greater in the future than in the 1961–1990 period while the growing season is shorter. Under the SRES A2 emissions scenario, however, yields at cold sites drop after 2070 due mainly to the shortening of cotton growth periods. Thus, in the cold regions, varieties with short growth periods are replaced by those with long growth periods. The results show that, compared with current local varieties, cotton yields increase by 356kg/ha with the medium maturity variety “K7” and 473kg/ha with the late maturity variety “ZM49” under the A2 scenario by 2070. Total evapotranspiration correspondingly increases by 69mm (“K7”) and 92mm (“ZM49”). However, water use efficiency increases by 0.32kg/m3 to 0.34kg/m3 (6.3%) and 0.35kg/m3 (9.4%) for “K7” and “ZM49”, respectively. A reasonable adaptive strategy to maintain cotton yields in the future may be to decrease the area over which cotton is planted and raise water use efficiency.

Cotton crop phenology in a new temperature regime

The daily outputs of the CSIRO Conformal Cubic Atmospheric Model driven by four general circulation models (GCMs) were used by a stochastic weather generator, LARS-WG, to construct four local climate change scenarios (CCSs) at nine key cotton production areas in eastern Australia. These CCSs were then linked to daily temperature-driven models of cotton phenology to examine the magnitude of the effects of increased temperature on the initiation and duration of key crop phenophases and on the occurrence of heat stress and cold shocks during the growing season. The results show that when using 1st Oct. as sowing time (1) the timing of emergence, 1st square, 1st flower and 1st open boll advanced 1–9, 4–13, 5–14 and 8–16 days, respectively, for the period centred on 2030 compared to baseline; (2) when crops were planted 10 days earlier, the emergence stage occurred earlier in most of the locations while other phenological events changed slightly (∼1 day) in comparison with 1st Oct. sowing; when crops were planted 10 days later, all these events were generally delayed (∼1.5 days) in comparison with 1st Oct. sowing; (3) the timing of the last effective square, last effective flower and last harvestable boll were delayed 7–12, 6–9 and 3–9 days, respectively, across locations (except St George) and GCMs; (4) the fruit development period increased up to 2–3 weeks; (5) the number of hot days increased across all locations and growing season (GS) months except May with the warmer months (Dec., Jan. and Feb.) and locations increased more; and (6) the number of cold shocks decreased or remained the same across locations and GS months except Jan. and Feb. with cold months and places decreased more. The results show that there will be less impact of cold temperatures on earlier growth and potentially a longer growing season that can improve crop yield. However, there will be more incidences of hot days impacting growth, and more rapid crop development in late phenological stages (especially during boll filling) that may limit the opportunities associated with increases in growing season length without adjustments in management.

Cotton phenology parameters affected by wind

Abstract Cotton plant ( Gossypium hirsutum L.) phenology was observed in a sheltered environment for six different planting dates and compared to cotton grown in an unsheltered area to isolate the effects of wind movement on cotton phenology and plant stress. The shelters consisted of a snow fence which provided a 35% reduction in wind velocity 0.2 m above the crop for the season. Partially sheltering the cotton from wind resulted in increased plant height, earlier squaring, earlier boll set and more bolls and biomass when compared to the unsheltered cotton. The increase in biomass and plant growth for the sheltered cotton required more water as the season progressed than the unsheltered cotton produced without supplemental irrigation. The study shows that wind and water uptake should be considered in crop models.

Changes in growth and development in cotton associated with genes for frego bract and glabrous leaf

Changes to cotton morphology and phenology associated with the frego bract and glabrous leaf genes (singly and combined) were measured in a field experiment using four near isogenic lines. Factorial analysis showed that frego bract was associated with more changes than glabrous leaf and that there were few significant interactions. Frego bract plants were 7% taller than normal bract plants at maturity, exhibited a delay in fruit production, had a greater proportion of fruit on sympodia of monopodial branches, shed more squares and had a lower proportion of reproductive to nonreproductive tissue. Glabrous-leafed plants produced fruit slightly later than hairy-leafed plants and had a lower proportion of reproductive to non-reproductive tissue. Overall, the growth of frego bract and glabrous-leafed plants was not sufficiently different from that of normal plants to warrant changes to the simple fruit model in the commercially available SIRATAC pest management program.