Critical Growth Stages Research Articles

Prolonged alkali water irrigation: impacts of treatment strategies on soil health and microbial dynamics

BackgroundThe extent of natural salt-laden groundwaters used for irrigation is increasing worldwide, which is a fast-emerging threat to agroecosystems and global food security. The salt buildup in the soil is linked to deteriorated soil chemical, physical, and biological health and decreased land productivity. Alkali waters with high residual sodium carbonate (RSC) is one of the severe poor-quality waters that deteriorate soil. We evaluated soil microbial dynamics and soil health at critical growth stages of rice crop receiving two-decade-long irrigation with three levels of alkali water and two reclamation strategies. These included good-quality water (GQW), alkali water (ALKW) with an RSC concentration of 5 me L⁻1 (ALKW1), ALKW with an RSC concentration of 10 me L⁻1 (ALKW2), ALKW2 treated to neutralize RSC to 5 me L⁻1 using gypsum (CaSO4·2H2O; ALKW2 + GYP), and ALKW2 treated with sulfuric acid (H2SO4; ALKW2 + SA). Eleven microbial parameters were used to develop a soil microbial activity index (SMAI), and eight soil health indicators were correlated with changes in SMAI and crop productivity.ResultsThe SMAI peaked under good-quality water (GQW) conditions (0.84–0.89), while the lowest values were recorded under ALKW2 (0.06–0.18). Neutralized alkali waters, ALKW2 + SA and ALKW2 + GYP, significantly improved SMAI with corresponding values of 0.25–0.35 and 0.13–0.32, respectively. SMAI across all stages correlated positively (R2 = 0.91–0.98) with rice yield. Microbial activity varied with the crop growth stage, peaking at tillering. Gypsum application alone, aimed at neutralizing alkalinity from an RSC of 10 to 5 me L⁻1, proved insufficient in bringing the SMAI up to the ALKW1 (RSC level of 5 me L⁻1).ConclusionsThe application of dilute sulfuric acid demonstrated better results in restoring the soil microbial activity index than gypsum amendment; however, sulfuric acid treatment depends on native calcium carbonate (CaCO3) dissolution for its effectiveness. It may not suffice for soil stability improvement in the long term, especially when native CaCO3 is low. Therefore, integrating gypsum and dilute sulfuric acid for RSC neutralization is worthwhile; however, further assessment is needed to confirm their combined impact on soil biochemical and physical properties.

Effects of Phenology on Plant Community Assembly and Structure

Phenology—the timing of critical stages of growth and reproduction and the transitions between them—determines environmental conditions and biotic interactions. Hence, phenology is a key functional trait influencing organisms’ survival and fitness; however, the role of phenology in community assembly processes has been less considered. Here we review the importance of phenology in environmental and biotic filtering, structuring priority effects, and species coexistence in the context of the assembly of native communities, as well as in invasions and restoration. We highlight the complexity of the life-history aspect of phenology, which makes simple trade-offs—such as between growth timing and competitive ability—part of larger plant strategies shaped by a framework of risk, reward, and investment over multiple timescales. Embracing this complexity could yield insights into how phenology shapes communities.

Detecting Water Stress in Winter Wheat Based on Multifeature Fusion from UAV Remote Sensing and Stacking Ensemble Learning Method

The integration of remote sensing technology and machine learning algorithms represents a new research direction for the rapid and large-scale detection of water stress in modern agricultural crops. However, in solving practical agricultural problems, single machine learning algorithms cannot fully explore the potential information within the data, lacking stability and accuracy. Stacking ensemble learning (SEL) can combine the advantages of multiple single machine learning algorithms to construct more stable predictive models. In this study, threshold values of stomatal conductance (gs) under different soil water stress indices (SWSIs) were proposed to assist managers in irrigation scheduling. In the present study, six irrigation treatments were established for winter wheat to simulate various soil moisture supply conditions. During the critical growth stages, gs was measured and the SWSI was calculated. A spectral camera mounted on an unmanned aerial vehicle (UAV) captured reflectance images in five bands, from which vegetation indices and texture information were extracted. The results indicated that gs at different growth stages of winter wheat was sensitive to soil moisture supply conditions. The correlation between the gs value and SWSI value was high (R2 > 0.79). Therefore, the gs value threshold can reflect the current soil water stress level. Compared with individual machine learning models, the SEL model exhibited higher prediction accuracy, with R2 increasing by 6.67–17.14%. Using a reserved test set, the SEL model demonstrated excellent performance in various evaluation metrics across different growth stages (R2: 0.69–0.87, RMSE: 0.04–0.08 mol m−2 s−1; NRMSE: 12.3–23.6%, MAE: 0.03–0.06 mol m−2 s−1) and exhibited excellent stability and accuracy. This research can play a significant role in achieving large-scale monitoring of crop growth status through UAV, enabling the real-time capture of winter wheat water deficit changes, and providing technical support for precision irrigation.

AtZAT10/STZ1 improves drought tolerance and increases fiber yield in cotton.

Drought poses a significant challenge to global crop productivity, necessitating innovative approaches to bolster plant resilience. Leveraging transgenic technology to bolster drought tolerance in crops emerges as a promising strategy for addressing the demands of a rapidly growing global populace. AtZAT10/STZ1, a C2H2-type zinc finger protein transcription factor has shown to significantly improve Arabidopsis' tolerance to various abiotic stresses. In this study, we reports that AtSTZ1 confers notable drought resistance in upland cotton (Gossypium hirsutum), amplifying cotton fiber yield under varying conditions, including irrigated and water-limited environments, in field trials. Notably, AtSTZ1-overexpressing transgenic cotton showcases enhanced drought resilience across critical growth stages, including seed germination, seedling establishment, and reproductive phases. Morphological analysis reveals an expanded root system characterized by an elongated taproot system, increased lateral roots, augmented root biomass, and enlarged cell dimensions from transgenic cotton plants. Additionally, higher contents of proline, chlorophyll, soluble sugars, and enhanced ROS-scavenging enzyme activities are observed in leaves of transgenic plants subjected to drought, underscoring improved physiological adaptations. Furthermore, transgenic lines exhibit heightened photosynthetic rate, increased water use efficiency, and larger stomatal and epidermal cell sizes, coupled with a decline in leaf stomatal conductance and density, as well as diminished transpiration rates compared to the wild type counterparts. Transcriptome profiling unveils 106 differentially expressed genes in transgenic cotton leaves post-drought treatment, including protein kinases, transcription factors, aquaporins, and heat shock proteins, indicative of an orchestrated stress response. Collectively, these findings underscore the capacity of AtSTZ1 to augment the expression of abiotic stress-related genes in cotton following drought conditions, thus presenting a compelling candidate for genetic manipulation aimed at enhancing crop resilience.

Revealing the Feedback Loop: Comparing Satellite and Sensor-derived Meteorological Parameters in Groundnut Cultivation

Background: Studying soil moisture’s impact on groundnut, particularly under rainfed conditions, is crucial for improving quality and yield. This research explores soil moisture dynamics using satellite and in-situ sensor data to enhance water management and crop predictions, focusing on the feedback mechanisms between soil moisture and weather variables. Methods: The study was conducted at the Oil Seed Research Station (TNAU) in Tindivanam, Tamil Nadu, using the groundnut variety TMV 14. Soil moisture and weather parameters were monitored at critical crop growth stages, using an in-situ soil moisture sensor (Cr 300) and compared with satellite data from SMAP, ERA5 and Sentinel 1A with environmental factors. Statistical analysis was carried out using SAS JMP Pro and network analysis via Cytoscape 3.8.2 software. Result: Pre-monsoon soil moisture SMAP, SMAP-RZSM and sensor (VWC at 10cm) were found to increase in post-monsoon. Strong positive correlations were attained between SMAP-SM and SMAP-RZSM (r=0.94), indicating a reinforcing loop. Whereas, the negative feedback was observed between SMAP-SM and deeper soil temperatures (-0.91). It underscores the dynamic interplay between soil moisture and atmospheric conditions, essential for developing efficient water management strategies and enhancing crop resilience to climate variability.

Strategic cultivar and sowing time selection for weed management and higher redgram productivity in semi-arid Indian regions

IntroductionRedgram (Cajanus cajan L. Mill sp.), a leguminous crop commonly grown in tropical and subtropical climates, is highly valued for its high protein content (21%), which contributes significantly to food and nutritional security. However, its production faces challenges primarily due to terminal dryness experienced during critical growth stages because of changing rainfall patterns. To overcome this, adaptive techniques become imperative as the productivity of this crop is intricately linked to environmental factors and the crop’s growth cycle.MethodsHence, the field experiment was conducted at the National Pulses Research Centre, Vamban, Pudukkottai, Tamil Nadu, in South India under rainfed condition, during the kharif (monsoon) seasons of 2017–18 and 2018–19. The primary objectives were to determine the optimal sowing time and identify suitable redgram cultivars, especially in the context of the late onset of the monsoon in Tamil Nadu, a common issue under changing climate conditions. The experiments tested six different sowing dates with three redgram cultivars.Results and discussionThe findings highlighted the substantial influence of different redgram cultivars and sowing times on the crop’s growth characteristics and yield. Among the six sowing dates tested, planting in later half of June (S6) resulted in notably higher plant height (201 cm), a greater number of pods per plant (287), a seed yield of 1,112 kg ha−1, and a benefit-cost ratio of 2.61 Notably, this sowing period (S6) demonstrated comparable performance with the treatment of redgram sowing in the latter part of September (S4). CO 6 (V1) is the most productive of the three redgram cultivars, with the highest mean pant height (200 cm), number of pods per plant (237), grain yield (1,017 kg ha−1), and benefit cost ratio (2.38). Extended phenological phases along with extra days to reach phenological stages could account for the increased yield in comparison to the other cultivars. Among the two short-duration cultivars, VBN (Rg) 3 (V3) had a significantly higher mean grain yield of 958 kg ha−1 with the benefit-cost ratio of 2.24. Even though CO 6 (V1) obtained a higher yield due to its long duration nature, it matured in 187 days whereas VBN (Rg) 3 (V3) matured within 129 days. Consequently, the short-duration redgram cultivars emerge as highly suitable choices for integrating into crop sequences, thereby augmenting farm cropping intensity.

Quantifying the Impact of Nitrogen Concentration Variations on Quality Characteristics of Soilless Cultivated Cherry Tomato

Within the domain of macronutrients, nitrogen has garnered significant recognition as a pivotal element due to its profound influence on both the vegetative growth and quality attributes of a crop. An abundance of scientific research has consistently demonstrated that attaining optimal productivity necessitates the meticulous management of soil moisture availability, complemented by the timely provision of nitrogen during critical growth stage intervals. The study aimed to optimize the nitrogen concentration in a hydroponic solution by testing a range of concentrations. The objective was to systematically examine the effects of different nitrogen levels and determine the optimal concentration for the desired outcomes. The assessment was carried out in a meticulously controlled greenhouse environment from October 2019 to April 2021, with the primary objective of systematically investigating the impact on quality characteristics specific to the rosa variety of cherry tomato. To investigate the effects of different nitrogen concentrations, four distinct levels of 4 mM, 6 mM, 8 mM, and 10 mM per litre of nutrient solution were employed. The nitrogen source consisted of a combination of NO3- and NH4+, with a ratio of 40:60, respectively. The nutrient solution with an 8 mM nitrogen concentration exhibited a significantly augmented effect on increasing the equatorial and polar diameter of fruits, average fruit weight, pericarp thickness, as well as the accumulation of total chlorophyll, ascorbic acid, lycopene, β-carotene, and total soluble solids (TSS) content. These findings demonstrate the pronounced and positive influence of the 8 mM nitrogen concentration on the aforementioned quality characteristics.

Impact of Stage-Specific Irrigation on the Growth and Yield of Wheat

Stage-specific irrigation is essential for ensuring optimal water use at critical growth stages in wheat (Triticum aestivum), leading to increased yield and improved grain quality. Therefore, determining an appropriate irrigation schedule for wheat is crucial for enhancing productivity. Keeping this view in mind, an experiment was conducted at the farmer’s fields of Dinajpur Sadar Upazila, Dinajpur, Bangladesh from November 2020 to April 2021, aimed to evaluate the impact of irrigation schedules on the growth and yield of wheat (BARI Gom-33). A randomized complete block design (RCBD) with seven treatments and three replications was implemented. Treatments included varying irrigation timings: T0 (no irrigation), T1 (one irrigation at maximum tillering), T2 (one irrigation at booting), T3 (one irrigation at heading), T4 (two irrigations at maximum tillering and heading), T5 (milking dough), and T6(two irrigations at booting and milking dough). Key metrics assessed included plant height, leaf count, tiller number, dry matter, growth stages, grain number, thousand grain weight, and overall yield at different days’ intervals. Results indicated that irrigated treatments (T1-T6) significantly improved the parameters for growth and yield compared to the control (T0). Notably, T4, with two irrigations, yielded the highest grain production at 5.20 t/ha, followed closely by T6. These findings highlight the significance of proper irrigation scheduling for optimizing wheat yield, indicating that applying two irrigations at the maximum tillering and heading stages can significantly enhance agricultural productivity.

Effect of Irrigation and Nitrogen Application at Early Tillering, Panicle Initiation and Flowering Stages on the Yield and Yield Attributes of Boro Rice

The study aimed to evaluate the impact of irrigation scheduling and nitrogen splitting on the yield and yield attributes of boro rice, with particular emphasis on critical growth stages including early tillering, panicle initiation and flowering stages. The experiment was executed at the Agronomy Field Laboratory of the Department of Agronomy and Agricultural Extension, University of Rajshahi, from December 2022 to May 2023. The experiment setup was demonstrated using a split plot design, incorporating three replications. Two factors were determined for the experiment: the first included three different watering schedules aiming critical growth stages: early tillering (I1), early tillering and flowering (I2), and early tillering, panicle initiation and flowering panicle initiation (I3). The second factor was distinct nitrogen splitting techniques, which consisted of four levels: control (N0), 138 kg N ha-1 as basal (N1), 69 kg N ha-1 at early tillering and flowering stages (N2), and 46 kg N ha-1 at early tillering, panicle initiation and flowering stages (N3). The highest reading of chlorophyll content was noticed in I3 along with productive tillers (15.67), grains (115.25) and yield outcome (4.44 t ha-1). Regarding nitrogen application, the greatest chlorophyll content, number of functional tillers (13.32), productive grains (112.44) panicle-1 and grain yield (4.48 t ha-1) was recorded in treatment N3. Therefore, the research finding suggest that the application of water at early tillering, panicle initiation and flowering stages along with the application of 46 kg N ha-1 will be helpful to maximize the production of rice in drought prone areas. This approach not only maximizes yield but also helps to mitigate water wastages associated with excessive irrigation.

130 Meta-analysis of the impact of Quebracho and Chestnut tannin extract supplementation on the growth performance in growing and finishing beef cattle

Abstract Integrating tannin extracts (TE) into the diet of growing and finishing beef cattle has shown promise in optimizing protein utilization while potentially mitigating methane emissions. Despite these potential benefits, there is a notable gap in a comprehensive analysis of the influence of TE on growth rate. This study addressed this gap by collecting data on the supplementation of a blend of condensed (from Schinopsis spp.) and hydrolyzable (from Castanea spp.) tannins, which has about 70% total tannins, and its impact on critical metrics, such as average daily gain (ADG, kg/d), dry matter intake (DMI, kg/d), and feed efficiency ratio (FER, g/kg). Our objective was to conduct meta-regression analyses to understand better the nuanced effects of condensed tannin supplementation on the overall performance of beef cattle during the critical stages of growth and finishing. The dataset was constructed by collecting published studies that reported in vivo experimental data on growing and finishing beef cattle supplemented with different levels of TE. It contained 132 observations from 35 publications. The meta-analysis was conducted by linear regression with a mixed-effects model fitted by the restricted maximum likelihood method using the nlme package of R software (ver. 4.3.1). Studies were assumed as random variables, and their interaction with the intercept and slope were included in the regression. The number of animals per treatment was used as a study-specific weight. Studies accounted for 32%, 35%, or 27% of the total variance when regressing ADG, DMI, or FER, respectively, on TE (% DM). After adjusting for random effects, the ADG increased (P < 0.001) with increasing levels of dietary TE (P < 0.001): 1.344 (± 0.0071) + 0.240 (±0.0298) × TE (n = 99, r2 = 0.40). It was observed that as the dietary TE level increased, its impact on the ADG tended to decrease from 0.33 kgּ d-1ּ % TE-1 when fed up to 0.5% TE to 0.24 kgּ d-1ּ % TE-1 when fed up to 1.5% TE, suggesting a possible nonlinear relationship between these two variables. Similarly, DMI decreased slightly (P < 0.001) at 0.61 kg/d/% TE, but with a lower precision (n = 115, r2 = 0.14). Consequently, FER increased (P < 0.001) at 17 kgּ d-1ּ % TE-1 (n = 93, r2 = 0.34). Initial findings suggest that incorporating TE into the diet of growing and finishing cattle, up to a concentration of 0.5% DM, positively influences the growth rate and enhances FER while minimally affecting DMI. Subsequent research endeavors should delve into a more intricate examination of optimal TE inclusion levels and explore additional performance indicators for a comprehensive understanding of its impact.

Seed Priming and Biopriming in Two Squash Landraces (Cucurbita maxima Duchesne) from Tunisia: A Sustainable Strategy to Promote Germination and Alleviate Salt Stress.

In recent years, seed priming has gained interest, with researchers aiming to enhance seed germination and early growth, especially under abiotic stress conditions. In this study, seeds from two squash landraces (Cucurbita maxima Duchesne; i.e., Galaoui large seeds (Galaoui hereafter) and Batati green (Batati hereafter)) were subjected to different priming methods ((a) 0.3% and 0.4% KNO3 (halopriming); (b) 0.1% and 0.2% GA3 (hormopriming); (c) inoculation with Trichoderma spp. (T. harzianum, T. viride, and T. virens), Bacillus subtilis, and Pseudomonas fluorescens (biopriming) in order to promote germination parameters and seedling growth under salinity stress (0, 100, and 200 mM of NaCl). Our findings indicate the better performance of primed seeds compared to the untreated ones in terms of germination and seedling growth traits, although a varied response depending on the priming method and the landrace was observed. The highest germination percentage (GP) and the lowest mean germination time (MGT) were observed in 0.4% KNO3-primed seeds. The positive effects of 0.4% KNO3 were also depicted in all traits related to seedling growth and the seedling vigor index (SVI), indicating its effectiveness as a priming agent in squash seeds. Under salinity stress conditions, priming with 0.4% KNO3 significantly improved the germination and seedling growth traits for both landraces, while the application of 0.2% GA3 at high salinity significantly improved photosynthetic quantum yield (Fv/Fm ratio). Regarding the effects of biopriming in germination and seedling growth traits, our results indicate that T. harzianum and B. subtilis were the most effective bioagents in promoting germination and seedling growth in Galaoui and Batati seeds, respectively. In conclusion, our findings provide important information regarding the practice of using priming and biopriming agents to enhance the germination and seedling growth capacity of squash seeds, as well to mitigate the negative effects of salinity stress at the critical stages of germination and early growth.

Abscisic acid improves drought resilience, growth, physio-biochemical and quality attributes in wheat (Triticum aestivum L.) at critical growth stages

Wheat is an important staple crop not only in Pakistan but all over the globe. Although the area dedicated to wheat cultivation expands annually, the quantity of wheat harvested is declining due to various biotic and abiotic factors. Global wheat production and output have suffered as a result of the drought, which is largely driven by a lack of water and environmental factors. Organic fertilizers have been shown to reduce the severity of drought. The current research was conducted in semi-arid climates to mitigate the negative effects of drought on wheat during its critical tillering (DTS), flowering (DFS), and grain filling (DGFS) stages through the application of three different abscisic acid treatments: ABA0 (0 mgL−1) control, ABA1 (100 mgL−1) and ABA2 (200 mgL−1). Wheat growth and yield characteristics were severely harmed by drought stress across all critical development stages, with the DGFS stage being particularly vulnerable and leading to a considerable loss in yield. Plant height was increased by 24.25%, the number of fertile tillers by 25.66%, spike length by 17.24%, the number of spikelets per spike by 16.68%, grain count per spike by 11.98%, thousand-grain weight by 14.34%, grain yield by 26.93% and biological yield by 14.55% when abscisic acid (ABA) was applied instead of the control treatment. Moreover, ABA2 increased the more physiological indices (water use efficiency (36.12%), stomatal conductance (44.23%), chlorophyll a (24.5%), chlorophyll b (29.8%), transpiration rate (23.03%), photosynthetic rate (24.84%), electrolyte leakage (− 38.76%) hydrogen peroxide (− 18.09%) superoxide dismutase (15.3%), catalase (20.8%), peroxidase (− 18.09%), and malondialdehyde (− 13.7%)) of drought-stressed wheat as compared to other treatments. In the case of N, P, and K contents in grain were maximally improved with the application of ABA2. Through the use of principal component analysis, we were able to correlate our results across scales and provide an explanation for the observed effects of ABA on wheat growth and production under arid conditions. Overall, ABA application at a rate of 200 mgL−1 is an effective technique to boost wheat grain output by mitigating the negative effects of drought stress.

Plant stress index (PSI) based irrigation scheduling of wheat in Punjab, India

A field experiment was caried out over a period of two years (2022-23 and 2023-24) at Lovely Professional University, Phagwara, Punjab with eight irrigation treatments (based on PSI, soil moisture depletion & critical growth stages) and four replications in RBD Design. The different irrigation levels had an impact on plant growth, parameters contributing to yield, grain and straw production, as well as irrigation water use efficiency (IWUE). Among all the PSI based irrigation treatments, schedule irrigation at 0.50 PSI was found the best irrigation level for growing wheat with significant grain yield (5.67 t ha-1), IWUE (0.092 t ha-1 cm) and gave 11.16% water saving over I50% FC (irrigation as per farmer practices). To schedule irrigation as per the soil moisture depletion approach, irrigation levels I50% FC and I75% FC result in maximum grain yield over PSI & critical growth stage-based irrigation treatments, but this practice does not support sustainable wheat production in water-scarce regions. Therefore, irrigation can be tailored for wheat crops based on 0.5 PSI in water-scarce and water-abundant regions of Punjab.

Harnessing Virtual Insights: A Computational Study on the Molecular Characterization of a Drought‐Inducible RNA‐Binding Protein for Enhancing Drought Tolerance in Mungbean (Vigna radiata L.)

AbstractAbiotic stresses, particularly drought and salinity, significantly impact agricultural crop yields, with mung bean (Vigna radiata L.) being no exception. This annual green legume, vital to agricultural systems in Asia, is generally resilient to limited water supply; however, severe drought conditions at critical growth stages can drastically diminish both its quality and yield. Drought stress negatively affects various morpho‐physicochemical properties, impeding plant growth and highlighting the need for sustainable approaches to enhance mung bean's drought tolerance through improved farming practices. In this study, we focused on identifying and understanding the molecular mechanisms underlying drought tolerance in mung beans. We retrieved the target gene sequence from the NCBI database, but found no direct sequence similarity, which led to the use of homology modeling. The structure of a known protein (PDB ID: 5T9P) was identified as the most suitable template. Motif prediction using the Motif Search tool highlighted specific motifs relevant to drought stress responses. To investigate potential drought‐tolerance mechanisms, we screened ABA agonists using Density Functional Theory (DFT) analysis. Molecular docking and MD simulations revealed the interactions between these ligands and the modeled protein, shedding light on how they might influence drought tolerance. We performed molecular dynamics (MD) simulations to assess the stability and conformational dynamics of the modeled protein across different time scales. Our findings underscore the potential of ABA agonists to modulate physiological responses and enhance drought resistance. This research offers valuable insights into the conformational dynamics of drought‐related proteins in mung beans, elucidating the molecular underpinnings of drought response mechanisms. By advancing our understanding of these processes, our findings provide novel strategies for improving breeding approaches aimed at enhancing crop resilience against water scarcity and other abiotic stresses. This work promises to mitigate the detrimental effects of drought on mung bean yields and supports sustainable agricultural practices, thereby contributing to global food security.

SCREENING OF COTTON (GOSSYPIUM HIRSUTUM L.) GERMPLASM AGAINST COTTON LEAF CURL VIRUS (CLCUV)

Cotton Leaf Curl Virus (CLCuV) is a devastating disease affecting cotton production worldwide, particularly in South Asia and Africa transmitted by the whitefly (Bemisia tabaci). CLCuV infection leads to severe symptoms, including leaf curling, vein thickening, stunted growth, and significant yield losses. Developing resistant cotton varieties is the most suitable strategy for managing CLCuV, given the limitations and environmental concerns associated with chemical controls. This study aimed to evaluate the resistance and susceptibility of different cotton varieties to CLCuV under natural field conditions and artificially infected condition using a disease severity scale ranging from 0 (highly resistant) to 5 (susceptible). A total of five cotton varieties, were assessed at three critical growth stages: vegetative, flowering, and boll formation. Disease severity, and yield components were recorded to determine extent of resistance of each variety. The results indicated that genotypes and treatments had significant variation in control compared to T1. According to DSI, NIAB-852 was scored as resistant with 10% infected leaves. FH-142 and CIM-496 were scored as tolerant according to DSI with 10-25% infection in leaves. NIAB Karishma and CIM-448 were scored as moderately susceptible with 50-75% infection. All genotypes had significant reduction in number of bolls, boll weight and seed cotton yield in T1 than control. These findings provide valuable insights into the effectiveness of existing cotton germplasm against CLCuV and highlight the need for continuous evaluation and development of resistant varieties. The study highlights the importance of generating resistant cultivars, thereby ensuring sustainable cotton production.

Integrating genetic assortment and molecular insights for climate-resilient breeding to unravel drought tolerance in cotton

This study addresses the challenges posed by rainfall variability, leading to water deficits during critical stages of crop growth, resulting in a drastic reduction of cotton yield. In a comprehensive evaluation, thirty cotton genotypes, including five Gossypium arboreum (wild) and twenty-five Gossypium hirsutum (cultivated), were grown under rainfed and irrigated conditions. Drought tolerance indices (DTI) were evaluated, categorizing genotypes based on their resilience. Further, in-vitro screening at the seedling stage (20 days) under PEG-induced drought identified tolerant genotypes exhibiting elevated levels of free proline (19.07±5.31 mg.g−100fr.wt.), amino acids (34.59±6.51 mg.g−100fr.wt.), soluble proteins (13.73±2.65 mg.g−1fr.wt.), and glycine betaine (10.95±3.62 mg.g−100fr.wt.), in their leaves, positively correlating (p<0.001) with relative water content (87.70±3.45 %). Molecular analysis using drought-specific simple sequence repeats (SSR) markers revealed significant genetic variability in a cotton genotypes, with lower observed and higher expected heterozygosity. F statistics exposed a higher level of gene flow corresponding to low differentiation among populations. Among the genotypes group, wild GAM-67 and cultivated Deviraj emerged as the most potent, exhibiting the higher DTI and diverse gene pools. Study exhibited higher total gene diversity in drought-tolerant wild GAM-67 (0.8501) and greater expected heterozygosity (0.626) and gene flow (0.6731) in cultivated Deviraj, underlining their robust genetic adaptability to drought conditions. The integrated approach of field evaluations, in-vitro screening, and molecular analyses explained substantial genetic diversity, with the identification of promising genotypes displaying higher drought tolerance indices, elevated levels of stress-related biochemical osmolytes, and pronounced genetic adaptability, thereby contributing to the advancement of breeding initiatives for enhanced drought resilience in cotton.

Different supplemental irrigation methods result in discrepant water use efficiency and yield by changing steps of water use process in dryland wheat

Supplemental irrigation (SI) at critical growth stages is a practical way to mitigate water shortage of winter wheat in dryland. However, the yield performance after SI is unstable in different precipitation years. To obtain a better understanding about the applicability of SI in dryland, the utilization efficiency of precipitation and irrigation water (IUE) was divided into 5 sequential ratios: water storage ratio, water consumption ratio, water transpired ratio, transpiration efficiency and harvest index. In this study, those ratios were investigated under four SI methods: no irrigation (W0), SI once at jointing (Wj), SI once at booting (Wb) and SI twice at jointing and booting (Wj+b) throughout four years. Our results showed that water storage ratio was increased under all SI treatments, but water transpired ratio was only significantly increased under Wj and Wj+b, due to their greater development of plant population compared to W0. Thus, wheat yield was greatly improved by 7–12 % under Wj and Wj+b than that under W0 in dry and normal years. However, IUE was significantly decreased under Wj+b. Compared with W0, Wj+b had higher evaporation during the fallow period and lower water consumption ratio. Furthermore, 100–300 cm subsoil water utilization was decreased under Wj+b from jointing to harvest time due to the low root length density (RDL) in subsoil. Under Wj, evaporation, subsoil water utilization and RDL were not negatively affected and water use efficiency was increased compared to W0. Thus, SI once at jointing stage is a more suitable practice in dryland wheat farmland when considering the dual goal of effectively using water while increasing yields under worse precipitation year.

Strip Tillage Improves Productivity of Direct-Seeded Oilseed Rape (Brassica napus) in Rice–Oilseed Rape Rotation Systems

Oilseed rape (Brassica napus) is a crucial global oil crop. It is generally cultivated in rotation with rice in southern China’s Yangtze River Basin, where the wet soil and residue retention after rice harvest significantly hinder its seedling establishment. Hence, this study developed a strip-tillage seeder for oilseed rape seeding following rice harvest. Additionally, seedling establishment, soil infiltration and evaporation post-seeding, soil moisture change, oilseed yield, and weed occurrence under strip tillage (ST) were compared with conventional shallow rotary-tillage (SR) and deep rotary-tillage (DR) seeding practices. Compared to SR and DR, the results demonstrated that ST had a higher seeding efficiency and 53.8% and 80.2% lower energy consumption, respectively. ST also enhanced seedling growth and oilseed yield formation more effectively than the competitor tillage treatments, with an oilseed yield increase exceeding 6%. Additionally, ST improved water infiltration and reduced soil water evaporation, resulting in higher topsoil (0–20 cm) moisture during the critical growth stages. Furthermore, ST reduced soil disturbance, significantly decreasing the density of the dominant weed, Polypogon fugax. Overall, ST seeding technology has the potential to improve the productivity of oilseed rape in rice–oilseed rape rotation systems, and its yield superiority is mainly due to seedling establishment improvement and soil moisture adjustment.

Research on Drought Stress Monitoring of Winter Wheat during Critical Growth Stages Based on Improved DenseNet-121

Research on Drought Stress Monitoring of Winter Wheat during Critical Growth Stages Based on Improved DenseNet-121

Exploring the potential of multi-source satellite remote sensing in monitoring crop nutrient status: A multi-year case study of cranberries in Wisconsin, USA

A timing and precise diagnosis of crop nutrient status is essential for optimizing management practices that promote environmentally friendly and enhanced crop yields. Although plant tissue analysis has conventionally been employed to evaluate the nutritional status of crops, this method cannot capture the spatial variability of crop nutrients. In contrast, satellite-based remote sensing can monitor the nutrient status of crops across expansive areas. This study explored the capability of multi-source satellite images (PlanetScope-4: 3 m, 4 bands; PlanetScope-8: 3 m, 8 bands; Sentinel-2: 10–60 m, 13 bands; PRISMA: 30 m, 239 bands) in mapping 12 foliar nutrients in cranberries. Three machine learning approaches, including partial least squared regression (PLSR), support vector regression (SVR), random forest regression (RFR), were used to relate foliar nutrients to different types of satellite-derived features (SR: surface reflectance; VI: vegetation indices; TF: texture features) or their combinations (SR+VI, VI+TF and SR+VI+TF). Model performance was compared across different foliar nutrients, modelling approaches and combinations of model input features using R2 (the coefficient of determination) and RRMSE (relative root mean square error, = root mean square error/nutrient range × 100 %). Input features that were important to foliar nutrient modelling were identified. The model performance difference among nutrients was consistent between Planet-4 and Sentinel-2, as well as between Planet-8 and PRISMA. In the Planet-4 and Sentinel-2 derived models, N was best predicted (average R2 = 0.77, average RRMSE=15 %), followed by macronutrients S (0.60–0.63, 11 %), Mg (0.58–0.65, 10–11 %), Ca (0.49–0.51, 9 %), Na (0.69, 22 %), P (0.49, 9 %) and K (0.20, 8 %), and then by all micronutrients(i.e., Fe, Mn, B, Cu and Zn: R2 = 0.04–0.61; RRMSE=16–28 %). In the Planet-8 and PRISMA derived models, macronutrients (i.e., N, P, K, Mg, Ca, S and Na) had lower R2 and RRMSE (R2 = 0.06–0.59; RRMSE=7–57 %) than micronutrients (i.e., Fe, Mn, B, Cu and Zn: R2 = 0.18–0.60; RRMSE=19–66 %). The successful retrieval of foliar nutrients from satellite imagery was influenced by many factors, including the intercorrelation between nutrients and model input features, the data availability at critical growth stages, and satellite images characteristics (e.g., spatial and spectral resolutions). Except for foliar nitrogen, foliar nutrients typically do not exhibit distinct absorption features associated with C, H, N, or O molecular bonds in the 400–2500 nm range. Our results indicate that their successful retrieval can be primarily attributed to the association between foliar nutrients and other leaf components (e.g., pigments, water, and dry matter) that do display spectral features within this range. Our study demonstrated the potential of integrating multi-source satellite data for precise nutrient monitoring over large scales.