It is of great importance to study the changes in reference evapotranspiration (ET₀) and the factors that influence it to ensure sustainable and efficient water resource utilization. Daily ET₀ data calculated using the Penman–Monteith method from 37 meteorological stations located within Guangdong Province in the humid zone of southern China from 1960 to 2020 were analyzed. The trend analysis and Mann–Kendall test were used to analyze the time series changes in ET₀ and major climatic factors (air temperature (T), relative humidity (RH), sunshine duration (SD), and wind speed (u₂)) for over 61 years. Sensitivity and contribution analyses were used to evaluate the driving factors of ET₀. The main findings of the study are as follows: (1) the trend in average annual ET₀ time series in Guangdong slightly increased at a trend rate of 1.61 mm/10a over the past 61 years, with most stations experiencing an increase in ET₀. During the same period, air temperature significantly increased, while RH and SD decreased; u₂ also decreased. (2) Sensitivity analysis showed that ET₀ was more sensitive to RH and T than SD and u₂, with ET₀ being most sensitive to RH in spring and winter and T in summer and autumn. (3) The contribution analysis showed that T was the dominant factor for ET₀ variation in Guangdong, followed by SD. SD was found to be the dominant factor in ET₀ changes in areas where the “evaporation paradox” occurred, as well as in spring and summer. The study concludes that the climate in Guangdong became warmer and drier over the past 61 years, and if the current global warming trend continues, it will lead to higher evapotranspiration and drought occurrence in the future.

Sugarcane is the major sugar-producing crop worldwide, and hybrid F₁ populations are the primary populations used in breeding. Challenged by the sugarcane genome’s complexity and the sucrose yield’s quantitative nature, phenotypic selection is still the most commonly used approach for high-sucrose yield sugarcane breeding. In this study, a hybrid F₁ population containing 135 hybrids was constructed and evaluated for 11 traits (sucrose yield (SY) and its related traits) in a randomized complete-block design during two consecutive growing seasons. The results revealed that all the traits exhibited distinct variation, with the coefficient of variation (CV) ranging from 0.09 to 0.35, the Shannon-Wiener diversity index (H′) ranging between 2.64 and 2.98, and the broad-sense heritability ranging from 0.75 to 0.84. Correlation analysis revealed complex correlations between the traits, with 30 trait pairs being significantly correlated. Eight traits, including stalk number (SN), stalk diameter (SD), internode length (IL), stalk height (SH), stalk weight (SW), Brix (B), sucrose content (SC), and yield (Y), were significantly positively correlated with sucrose yield (SY). Cluster analysis based on the 11 traits divided the 135 F₁ hybrids into three groups, with 55 hybrids in Group I, 69 hybrids in Group II, and 11 hybrids in Group III. The principal component analysis indicated that the values of the first four major components’ vectors were greater than 1 and the cumulative contribution rate reached 80.93%. Based on the main component values of all samples, 24 F₁ genotypes had greater values than the high-yielding parent ‘ROC22’ and were selected for the next breeding stage. A rapid sucrose yield estimation equation was established using four easily measured sucrose yield-related traits through multivariable linear stepwise regression. The model was subsequently confirmed using 26 sugarcane cultivars and 24 F₁ hybrids. This study concludes that the sugarcane F₁ population holds great genetic diversity in sucrose yield-related traits. The sucrose yield estimation model, $y_{SY}=2.01x_{SN}+8.32x_{SD}+0.79x_B+3.44x_{SH}-47.64$, can aid to breed sugarcane varieties with high sucrose yield.

Selections of drought-tolerant cultivars and drought-stress diagnosis are important for sugarcane production under seasonal drought, which becomes a crucial factor causing sugarcane yield reduction. The main objective of this study was to investigate the differential drought-response strategies of drought-resistant (‘ROC22’) and -susceptible (‘ROC16’) sugarcane cultivars via photosynthetic quantum efficiency (Φ) simulation and analyze photosystem energy distribution. Five experiments were conducted to measure chlorophyll fluorescence parameters under different photothermal and natural drought conditions. The response model of Φ to photosynthetically active radiation (PAR), temperature (T), and the relative water content of the substrate (rSWC) was established for both cultivars. The results showed that the decreasing rate of Φ was higher at lower temperatures than at higher temperatures, with increasing PAR under well-watered conditions. The drought-stress indexes (ε_D) of both cultivars increased after rSWC decreased to the critical values of 40% and 29% for ‘ROC22’ and ‘ROC16’, respectively, indicating that the photosystem of ‘ROC22’ reacted more quickly than that of ‘ROC16’ to water deficit. An earlier response and higher capability of nonphotochemical quenching (NPQ) accompanied the slower and slighter increments of the yield for other energy losses (Φ_NO) for ‘ROC22’ (at day5, with a rSWC of 40%) compared with ‘ROC16’ (at day3, with a rSWC of 56%), indicating that a rapid decrease in water consumption and an increase in energy dissipation involved in delaying the photosystem injury could contribute to drought tolerance for sugarcane. In addition, the rSWC of ‘ROC16’ was lower than that of ‘ROC22’ throughout the drought treatment, suggesting that high water consumption might be adverse to drought tolerance of sugarcane. This model could be applied for drought-tolerance assessment or drought-stress diagnosis for sugarcane cultivars.

The production and breeding of peanuts was restricted by the frequently extreme climatic conditions in Guangdong province, China. To understand the influence of drought and pluvial climates on peanut traits and yield, a phenotypic investigation of seventy peanut cultivars was conducted from 2018 to 2022; comprehensive field meteorological data collection, and typical drought (2021) and pluvial (2022) climates were recorded. The results revealed that the cultivars achieved the highest single plant pod weight (SPPW) and single plant seed weight (SPSW) of 61.03 g and 45.84 g, respectively, in drought conditions, followed by the control, and finally the pluvial. The SPPW, SPSW and eight agronomy traits exhibited significant differences across the different climatic conditions. Correlation analysis revealed the yield traits and key yield-related traits were positively or negatively correlated with soil water content (SWC), total global radiation (TGR), total precipitation (TP) and total net radiation (TNR). The intermediate and Spanish type cultivars were more stable and productive than the other botanical types of cultivars, commercial varieties exhibited better performance than landraces, and seven cultivars were identified with good production potential, under drought and pluvial conditions. Our study showed that pluvial climate was detrimental to peanut yield, and the SPPW and SPSW were significantly influenced by climates with genotype differences.

Surface energy partitioning governs canopy thermal conditions and water use by determining how available energy is dissipated as latent versus sensible heat. In tropical and subtropical croplands, compound heat–drought events increase atmospheric evaporative demand, yet crassulacean acid metabolism (CAM) crops may respond differently from C ₃ /C ₄ systems because daytime stomatal regulation constrains transpiration. Here we quantify subdaily energy partitioning in a subtropical CAM pineapple field in southern China using Bowen-ratio energy balance observations. Net radiation ( R _n ), soil heat flux ( G ), and vertical gradients of temperature and vapor pressure were used to estimate sensible ( H ) and latent ( LE ) heat fluxes and to compute available energy ( A = R _n − G ). To diagnose the coupling relationship between atmospheric demand and water supply, hourly data were classified into four weather types (WT4) using median thresholds of R _n and vapor pressure deficit (VPD): LR _n –LVPD (low R _n , low VPD), LR _n –HVPD (low R _n , high VPD), HR _n –LVPD (high R _n , low VPD), and HR _n –HVPD (high R _n , high VPD). Soil water content (SWC) at a depth of 20 cm was further classified into three soil moisture states (SWC3) using percentiles (Dry, Normal, and Wet). Scenario medians and valid-hour counts were used to summarize LE/A, H/A, and G/Rn, complemented by Bowen ratio ( β = H/LE ) as an integrative indicator of sensible versus latent heat partitioning. The results showed that energy partitioning was dominated by compensation between LE / A and H / A , while G / R _n remained small. LE / A was consistently lower under HR _n –HVPD than under LR _n –LVPD across soil-moisture states. Under LR _n –LVPD, LE / A was 0.47 in Dry and Normal and increased to 0.56 in Wet; under HR _n –HVPD it ranged from 0.26 (Dry) to 0.37 (Wet). Moisture effects were demand dependent: within HR _n –HVPD, LE / A increased by 0.11 from Dry to Wet, whereas the LR _n –LVPD Dry-to-Wet increase was 0.09. β responses reinforced this interaction. Under Dry conditions, β increased with VPD and remained high at high VPD, whereas under wet soils β was lower and tended to level off. Under HR _n –HVPD, β declined steeply as SWC increased over 0.23–0.27 m ³ m ^-3 , then approached a plateau near 1.7; under non-HR _n –HVPD conditions β showed weaker dependence and plateaued near 2.0. Composite daytime patterns further showed sustained H dominance under HR _n –HVPD–Dry, while HR _n –HVPD–Wet shifted partitioning toward higher LE . These results demonstrate that atmospheric demand sets a strong constraint on daytime evaporative cooling in this CAM pineapple system, and that soil water supply enhances latent heat dissipation most effectively under high-demand conditions, thereby informing model parameterization and targeted water management.