Sugarcane Yield Research Articles

Sugarcane Yield Estimation Using UAV-Based RGB Images and Allometric Equations

Accurately estimating pre-harvest sugarcane yield has long been a challenge. There are many methods for predicting sugarcane yield, ranging from simple empirical equations to complex physiological models. This paper reports a study on a method for predicting sugarcane yield using allometric equations combined with UAV-based RGB images (UAVI). UAVI were used for the estimation of the sugarcane height, which is in the form of the sugarcane height model (HM). Sugarcane height is one of the key factors in calculating sugarcane yield in the allometric equation. The results showed that the HM could be used in the allometric equation. There was only a slight discrepancy compared to measurement with a tape measure in the field. In developing the allometric equation, the authors created regression models to estimate aboveground biomass weight in leaf bush (Wl) and millable stalk (Wms) based on sugarcane height (H) and diameter measured from the first segment of sugarcane aboveground (Dfs). The model estimated aboveground biomass weight sufficiently for all stages of cultivation. Based on this model, the authors developed two general equations: Y = 0.0842 H * Dfs0.9827; R2 = 0.93 (used for leaf bush), and Y = 0.1254 H * Dfs1.3926; R2 = 0.93 (used for millable stalk). The decision correlation coefficient (R2) was 80% reliable. The HM models were slightly different from field measurements with a tape measure. Also, there was a little inaccuracy in the root-mean-square error (RMSE) between the sugarcane heights analyzed from UAVI and field measurements using tape measure. The RMSE values, arranged from highest to lowest according to the sugarcane growth stage were: 0.35 m (tillering phase, TP), 0.25 m (grand growth phase, GP), and 0.24 m (ripening phase, RP). Using the HM value in the allometric equation effectively estimated the sugarcane yield at different growth stages. Sugarcane growth at TP and GP phases gave the highest sugarcane yield at 200 cm of the HM value, with total yields of 11.49 and 16.75 ton/hectare, respectively. Whereas, RP gave the highest sugarcane yield at 350 cm of the HM value (total yield at 42.97 ton/hectare). Overall, an accurate estimation of the aboveground biomass of leaf bush and millable stalk can be obtained using these equations. The authors believe that the research methods presented here can help sugarcane farmers to better estimate yield prior to harvest.

Dual-modal improved biosensing platform for sugarcane smut pathogen based on biological enzyme-Mg2+ DNAzyme coupled with DNA transporter cascading hybridization chain reaction

Sugarcane smut is a major disease affecting the yield and quality of sugarcane, and its early detection is crucial for the healthy development of sugarcane industry. In this work, a dual-modal biosensing platform is designed based on Au-V-MOF and 3D DNA walker for highly sensitive and precise detection of the sugarcane smut pathogen. This detection system utilizes the catalytic properties of biocatalysts and the precise cleavage of DNAzymes, along with 3D DNA walker nanotechnology and a designed “walking track”, to achieve amplified detection signals and accurate target recognition. The detection platform utilizes catalytic hairpin assembly for target recycling. Output strand T1 interacts with DNAzyme via a 3D transporter, cleaving S1 in Mg2+ presence. This triggers cascading hybridization chain reaction to form long double-stranded DNA structures that absorb substantial methylene blue (MB). This amplifies the electrical signal and causes a proportional color change due to the redox reaction of MB, which enables electrochemical and colorimetric detection of the target. The method shows a linear response range from 0.0001 to 10,000 pM with a detection limit of 56.76 aM (S/N = 3). It features high sensitivity, specificity, and accuracy, which offers significant potential for early warning and precise detection of sugarcane smut.

Advancing Sugarcane Farm Management Through NDVI-Based Color Mapping and Drone Imaging

Precision agriculture has emerged as a key strategy for boosting crop productivity and optimizing resource use. This study leverages advanced imaging and machine learning to enhance the management of sugarcane farms. Using drones, high-resolution RGB images of sugarcane fields are captured and transformed into multispectral images through a Generative Adversarial Network (GAN), revealing critical spectral data for plant health assessment. The Normalized Difference Vegetation Index (NDVI) is derived from these multispectral images and serves as a vital measure of vegetation health. This NDVI data, combined with farmer-reported yield information, creates a comprehensive dataset linking NDVI values to actual crop yields. To predict sugarcane yield from NDVI values, we trained a feedforward neural network on this integrated dataset. The proposed method not only enhances prediction accuracy but also provides valuable insights into the connection between NDVI metrics and crop performance. The model was validated using individual field images, enabling precise yield predictions for different field sections. This study highlights the effectiveness of integrating drone imagery, machine learning, and remote sensing in precision agriculture. The combination of NDVI data with yield information provides a robust tool for optimizing sugarcane production, improving farm management decisions, and advancing agricultural sustainability.

EFFECTIVENESS OF TRICHODERMA SPECIES IN THE MANAGEMENT OF SUGARCANE WILT (FUSARIUM SACCHARI)

Sugarcane is a major cash crop in Pakistan. It has a great contribution in world’s economy. Many diseases cause many losses in yield of sugarcane. Fungi are considered as abundant traitorous pathogens that obstruct the viable growth of sugarcane crop. Wilt disease caused by fungal pathogen Fusarium sacchari caused many losses in sugarcane production in Pakistan. Fusarium sacchari is a causative fungus of wilt in sugarcane. Biocontrol agent Trichoderma spp. used in the management of sugarcane wilt. These bio‐agents help in diseases management and play important role in increasing the crop yield. For this reason, these bio‐agents are used for biological maintaenace of crop diseases and research globally. The use of PDA medium in vitro revealed antagonistic activity of various Trichoderma isolates against the sugarcane wilt pathogen Pathogenicity test also executed to check the most aggressiveness strain of Fusarium spp. to cause disease in sugarcane plant. In vivo, Trichoderma multiply on different substrates and corn Cobbs is good byproduct Trichoderma multiply on it and mix in soil of pots. Pot experiment performed with different treatments to control wilt disease by using of antagonist’s to check disease incidence and disease reduction.

Effects of Potassium Fertilizer on Sugarcane Yields and Plant and Soil Potassium Levels in Louisiana

Effects of Potassium Fertilizer on Sugarcane Yields and Plant and Soil Potassium Levels in Louisiana

Close correlation between sugarcane ratoon decline and rhizosphere ecological factors

Rhizosphere ecological factors that affect sugarcane ratoons are crucial components in the feedback mechanisms between the sugarcane plant and soil environment. However, systematic investigations on these dynamics are lacking. Therefore, this study investigated the relationship between sugarcane ratoon decline and rhizosphere ecological factors. In first-year sugarcane ratoons, ecological factors such as soil available potassium content, soil nitrogen fixation, and soil peroxidase activity were significantly positively correlated with sugarcane growth (P < 0.05) compared to that of third-year sugarcane ratoons. Significant intergroup disparities in the rhizosphere soil microbial community structure were observed based on different ratoon ages (P < 0.01), while highly significant intergroup differences in endophytic microbial community structure were observed based on a Jaccard distance analysis (P < 0.01). Generalised additive model analysis revealed a significant positive correlation (P < 0.05) between sugarcane growth properties and the alpha diversity of rhizosphere soil bacteria and endophytic bacteria but a predominantly negative correlation (P > 0.05) between the alpha diversity of endophytic fungi and key sugarcane growth indicators. The deterioration of mainly non-microbial ecological factors in rhizosphere soil (P < 0.05) with increasing ratoon age may represent a significant factor contributing to sugarcane ratoon decline. The fungal community significantly impacted soil enzyme activity, while the microbial community indirectly influenced sugarcane yield through its effect on soil enzyme activity. Therefore, endophytic fungi, particularly Ascomycota species, may play a crucial role in sugarcane diseases.

Economic Effects of Fertilizer Subsidy on Major Crops Productivity in Pakistan

Based on time series data set (1990-2022) this study was conducted to estimate the economic effects of fertilizer subsidies on major crops productivity in Pakistan. Majority (90%) of the farmers having small land holding size are not in a position to apply inputs like fertilizer which incurred 15-20% of total cost of production. Three types of analysis were employed i.e., Trend analysis, Correlation analysis and Regression analysis. The trends in growth rate of fertilizer use along with trends in growth rate of respective crop yield have been sketched with different trends. The correlation analysis between fertilizer subsidy and yield (kg ha-1) of major crops i.e. wheat, rice, sugarcane, cotton and maize has been calculated with positive correlation coefficient values as 0.459, 0.468, 0.351, 0.224 and 0.551 respectively. The simple linear regression analysis depicted that a rupee of one billion PKR subsidies is significantly increased the crop fertilizer usage (000 tons nutrients) of wheat (37.10), rice (14.97), sugarcane (13.60) and cotton (40.12) as well as increased the crop yield (mound acre-1) of wheat (0.26), rice (2.04), sugarcane (32.93), maize (62.17) and cotton (0.19) respectively which indicated that the yield of the crops is also positively affected by fertilizer use and fertilizer subsidy. The elasticity of yield with respect to fertilizer subsidy also confirmed the regression analysis results. Although yield is inelastic to subsidies; however, one % increase in fertilizer subsidy resulted in 0.043, 0.061, 0.044, 0.022 and 0.207 (%) increased in yield of wheat, rice, sugarcane, cotton and maize respectively. Based on positive values of coefficients, it is concluded that the fertilizer subsidies should be distributed more efficiently to enhance the productivity of crops.

Changes in the population and diversity of plant parasitic nematodes and their effects on sugarcane growth at Wonji‐Shoa Sugar Estate, Ethiopia

AbstractIn Wonji‐Shoa Sugar Estate (WSSE), sugarcane (Saccharum spp. hybrid) yields have declined by about 48% over the last 70 years. One of the causes for the decline is assumed to be the long‐term monoculture production system that results in the buildup of plant parasitic nematodes (PPNs). Therefore, the population and diversity of PPNs were investigated by conducting soil sampling using a biosequential method (simultaneous sampling of the soils of adjacent cultivated land [CL] and uncultivated land [UL]) and a chronosequential method (taking soil samples at different times from the same site). The samples were subjected to analysis using standard procedures to determine the change in the population, and identify the genera of PPNs. Additionally, a pot experiment that involved fumigation was conducted on top soils sampled from the CL and UL of the plantation. The results revealed that about 10 genera of PPNs (Meloidogyne, Helicotylenchus, Hoplolaimus, Rotylenchulus, Hemicycliophora, Discriconemella, Xhiphinema, Pratylenchus, Tylenchorhynchus, and Scutellonema) were detected, of which the first four were newly identified. The population density and the number of genera of PPNs found in the CL were 36‐fold and 4.5‐fold higher than those found in the UL, respectively. Furthermore, fumigation reduced the population of the PPNs by 61% and increased production of cane biomass by 63%. It is concluded that the soils of the WSSE are infested by PPNs, which consequently have detrimental effects on sugarcane growth. While amending soil fertility is crucial, reversing the decline in sugarcane yields also necessitates implementing an integrated soil management system that includes PPNs.

Cloning and expression study of sugarcane (Saccharum sp.) sucrose transporter gene (SoSUT4)

Sugarcane (Saccharum sp.) is a vital commodity for global sugar production and biomass generation, with sucrose being the primary sugar accumulated predominantly in the stem. The sucrose transporter protein is essential in facilitating sucrose transport across cells and over long distances within plants, from source to sink tissues. This study focused on the cloning and expression analysis of the SoSUT4 gene in the Bululawang sugarcane variety. A partial coding sequence of SoSUT4, comprising 802 nucleotides and encoding a 267-amino acid protein, was successfully cloned and sequenced. Sequence analysis revealed that the SoSUT4 protein shares high similarity with other SUT4 proteins in monocotyledonous plants, particularly with Saccharum spontaneum and Saccharum hybrid. Bioinformatics predictions indicated that the SoSUT4 protein is localized to the plasma membrane and contains six transmembrane helices. Gene expression analysis further demonstrated that SoSUT4 expression was significantly higher in the middle internodes of the stem compared to the youngest midsection of the leaves. This expression pattern correlates with higher sucrose accumulation in the stem, as reflected by elevated Brix levels in the stem (19.61%) compared to the leaves (19.48%). This finding suggests that SoSUT4 is essential for sucrose translocation to the stem, which serves as the primary storage site for sugar. The study provides valuable insights into the SoSUT gene family in sugarcane, particularly highlighting the role of SoSUT4 in sugar transport and accumulation. Future research should further investigate the underlying mechanisms of SoSUT4 and related genes to enhance our understanding of their impact on sugarcane yield, with potential applications for genetic engineering aimed at improving crop productivity. [Keywords: brix, relative expression, SoSUT4]

Simulation of Intra-seasonal Climatic Variability, Potential Yield and Yield Gap of Sugarcane for the South Gujarat Region, India

The validated CANEGRO (DSSAT v4.7) model was used to simulate the intra-seasonal climatic variation viz. temperature (-3oC to +3oC) and rainfall (-25% to +25%) variability in sugarcane yield and quantifying the yield gap of sugarcane at Navsari, Bharuch, Surat and Valsad districts of south Gujarat region under the various management options included dates of planting, irrigations and fertilizers application and compared with the reported yield of the districts. The cane yield increased with an increase in rainfall and a decrease in temperature. In contrast, the cane yield decreased with a decrease in rainfall and an increase in temperature. The extent of effect was found to vary with crop growth stages. The potential yield of sugarcane simulated by the model in different districts was found to vary between 107.0 to 114.7 t ha-1, while the reported yield in these districts varied between 68.1 to 72.0 t ha-1. This resulted in a total yield gap between 38.9 to 45.5 t ha-1 in different districts. The highest yield gap was in Navsari district while the lowest yield gap was found in Bharuch district.

Effect of planting densities by the practice of twin rows on the agronomic and technological parameters of sugar cane in rainfed cultivation

With the aim of improving sugar cane productivity under rainfed conditions, a study of the effect of planting densities using paired rows on sugar cane yield parameters was carried out at the CNRA Ferkéssédougou station in northern Côte d'Ivoire. The experimental design used was a Fischer block, comprising three repetitions of six treatments, designated T1 to T6. The results revealed that treatments T1 and T2 improved cane yields, reaching 149±18.04 and 157±44.55 t/ha, respectively. Similarly, an increase in the number of usable stems per hectare of 207,726 ± 13144.44 and 216,468 ± 70412.15 was noted for treatments T1 and T2 respectively. Furthermore, the T6 treatment improved the technological parameters (Brix (22.4 ± 0.86 %); Fibre content (16.8 ± 0.11 %); Pol (19.4 ± 0.81 %) ; Purity of juice (86.7 ± 1.09 %) ; Saccharin content (14.9 ± 0.62 %); Extractable sugar (10.5 ± 0.52 %)). The study also identified three promising planting densities for village cane :1.1m and 1.3m row spacing at 0.4m and 1.3m row spacing at 0.5m. In conclusion, the cultural practice of density in twin rows in sugar cane plantations in rainfed conditions allows an increase in agronomic and technological parameters. This cultivation practice could contribute to an increase in yield or even a substantial increase in sugar production.

Mapping sugarcane globally at 10 m resolution using Global Ecosystem Dynamics Investigation (GEDI) and Sentinel-2

Abstract. Sugarcane is an important source of food, biofuel, and farmer income in many countries. At the same time, sugarcane is implicated in many social and environmental challenges, including water scarcity and nutrient pollution. Currently, few of the top sugar-producing countries generate reliable maps of where sugarcane is cultivated. To fill this gap, we introduce a dataset of detailed sugarcane maps for the top 13 producing countries in the world, comprising nearly 90 % of global production. Maps were generated for the 2019–2022 period by combining data from Global Ecosystem Dynamics Investigation (GEDI) and Sentinel-2 (S2). GEDI data were used to provide training data on where tall and short crops were growing each month, while S2 features were used to map tall crops for all cropland pixels each month. Sugarcane was then identified by leveraging the fact that, among all non-tree species grown in cropland areas, sugarcane is typically tall for the largest fraction of time. Comparisons with field data, pre-existing maps, and official government statistics all indicated high precision and high recall of our maps. Agreement with field data at the pixel level exceeded 80 % in most countries, and subnational sugarcane areas from our maps were consistent with government statistics. Exceptions appeared mainly due to problems in underlying cropland masks or due to under-reporting of sugarcane area by governments. The final maps should be useful in studying the various impacts of sugarcane cultivation and producing maps of related outcomes such as sugarcane yields. The dataset is available on Zenodo at https://doi.org/10.5281/zenodo.10871164 (Di Tommaso et al., 2024a).

Sugarcane Yellow Leaf Virus – A Silent Threat?

Abstract Sugarcane yellow leaf virus (SCYLV) is the causal agent of yellow leaf disease, a significant threat to global sugarcane production. SCYLV is disseminated via infected planting material and transmitted by aphids, primarily by Melanaphis sacchari (Zehntner). The disease’s impact varies depending on the sugarcane cultivar, with some varieties showing little to no foliar symptoms, yet experiencing severe yield losses. Reliable diagnostic methods, including serological and molecular techniques, are crucial for accurate detection, though these methods vary in sensitivity. Advances in molecular techniques have revealed ten major SCYLV genotypes grouped into three phylogroups, further complicating detection efforts. Improved understanding of SCYLV’s distribution within the plant and its seasonal variability are yet to be understood. Management strategies focus on breeding SCYLV-resistant varieties, but this is challenging due to the virus’s variable impact on yield and the often asymptomatic nature of epidemics. Efforts to develop SCYLV-free propagative material have been implemented, but the virus can still spread via aphid vectors from neighbouring fields. Ongoing research aims to identify resistant cultivars, optimize diagnostic techniques, and better understand the epidemiology of SCYLV to mitigate its impact on sugarcane yield and quality. Information © The Authors 2024

Effect of postharvest sugarcane straw amount and herbicides on Digitaria spp. control and green cane yield

Abstract New agronomic practices are emerging in the green cane system to utilize sugarcane (Saccharum officinarum L.) straw for energy cogeneration, which necessitates its removal from the soil surface. This study has three main objectives: (1) evaluate the population dynamics and composition of Jamaican crabgrass (Digitaria horizontalis Willd.) and large crabgrass [Digitaria sanguinalis (L.) Scop.] under different sugarcane straw amounts, with and without herbicide treatment; (2) assess the development of sugarcane under different straw amounts; and (3) determine the amount of sugarcane straw that should be kept on the soil surface after harvest to ensure that it does not compromise the chemical control for Digitaria spp. in ratoon cane in a green cane system. We conducted this research at two experimental sites, one at the beginning and the other during the middle of the harvest season, over a span of 2 yr. Our primary treatments consisted of different amounts of sugarcane straw after harvest on the soil surface (0, 5, 10, and 15 Mg ha−1), while secondary treatments included the herbicide application (sulfentrazone + tebuthiuron for the beginning of harvest season and isoxaflutole + tebuthiuron for the middle of harvest season). The Digitaria spp. exhibited higher density (four times more) and dry matter (two times more) in scenarios with a lower sugarcane straw amount (5 Mg ha−1) on the soil surface and no herbicide application. However, a higher straw amount (15 Mg ha−1) contributed to reduced Digitaria spp. infestation and to improved sugarcane yield. According to this research, it is essential to maintain at least 10 Mg ha−1 of sugarcane straw on the soil surface and remove only 5 Mg ha−1 for energy cogeneration.

Coexpression Regulation of New and Ancient Genes in the Dynamic Transcriptome Landscape of Stem and Rhizome Development in "Bainianzhe"-An Ancient Chinese Sugarcane Variety Ratooned for Nearly 300 Years.

The sucrose yield in sugarcane largely depends on stem morphology, including length, diameter and sugar content, making sugarcane stem a key trait in breeding. The "Bainianzhe" variety from Songxi County, Fujian Province, possesses both aerial stems and rhizomes, providing a unique model for studying stem development. We performed a spatiotemporal transcriptomic analysis of the base, middle and apical sections of both aerial stems and rhizomes. The analysis categorized transcriptomes by developmental stage-base, middle and apical-rather than environmental differences. Apical segments were enriched with genes related to cell proliferation, while base segments were linked to senescence and fibrosis. Gene regulatory networks revealed key TFs involved in stem development. Orphan genes may be involved in rhizome development through coexpression networks. Plant hormones, especially genes involved in ABA and GAs synthesis, were highly expressed in rhizomes. Thiamine-related genes were also more prevalent in rhizomes. Furthermore, the apical segments of rhizomes enriched in photosynthesis-related genes suggest adaptations to light exposure. Low average temperatures in Songxi have led to unique cold acclimation in Bainianzhe, with rhizomes showing higher expression of genes linked to unsaturated fatty acid synthesis and cold-responsive calcium signalling. This indicates that rhizomes may have enhanced cold tolerance, aiding in the plant's overwintering success.

Forecast of Sugarcane Yield in Chongzuo, Guangxi—LSTM Model Based on Fusion of Trend Yield and Meteorological Yield

Purpose: This paper develops a high-precision yield fusion prediction model for the sugarcane industry in Chongzuo, Guangxi, based on the trend yield and meteorological yield using the long short-term memory (LSTM) model to cope with the multiple factors affecting sugarcane production. Decision support is provided to agricultural producers, policymakers, and supply chain managers so that they can plan resource allocation, market strategies, and policy directions more effectively. Methods: The paper modeled trend yield and weather yield separately to explore the complex relationship between the two in influencing sugarcane production. Trend yields were predicted using the exponential smoothing and multilayer perceptron (MLP) models, while meteorological yields were modeled using stepwise regression. The predicted yields were used again as input variables into the LSTM deep learning network to fit the nonlinear relationship between the two yields. Results: The results showed that (1) the fusion strategy of meteorological yield and MLP trend yield adopted by the model was superior to the fusion strategy of meteorological yield and exponentially smoothed trend yield, achieving a very low mean square error (MSE) of 0.011 and a goodness of fit as high as 0.979, which indicated that the model prediction was highly in agreement with the actual yield, confirming the validity of the method. (2) The prediction curve is basically consistent with the trend of actual sugarcane yield, which predicts that the sugarcane yield in Chongzuo, Guangxi, is expected to maintain a stable and small growth trend in the next eight years. (3) The fusion prediction model proposed in this study provides an accurate and practical solution for sugarcane yield prediction in Chongzuo, Guangxi, with the unique advantage of effectively analyzing and integrating the natural and socio-economic factors affecting the yield, which is of significant reference value for the prediction of sugarcane yield in the local area and even in similar ecoregions.

Correlation among Yield, Quality and Mechanization Amicable Traits in Sugarcane Clones

The objective of this study was to identify superior clones suitable for mechanical harvesting, which is essential to improve the production efficiency, cost effectiveness, cane loading efficiency infield losses and also to investigate the relationships among the yield and quality parameters with cane yield and sugar yield in sugarcane. This experiment was conducted at Regional sugarcane and Rice Research Station, Rudrur, Nizamabad district, Telangana state in Randomized Block Design (RBD) with three replications. The analysis of variance revealed significant differences among genotypes for fifteen yield, quality and mechanization amicable characters. Correlation coefficient results indicated that cane yield was positively correlated with commercial cane sugar, number of tillers at 120 days after planting, cane height, cane girth, single cane weight. So, selection for cane yield alone will also increase the other characters because these traits are positively correlated with cane yield. The Angle of inclination is negatively correlated with cane yield and positively correlated with ratio of crown weight to cane weight, brix%, sucrose%, purity% and CCS%. Results indicate that the genotypes should be selected on the basis of number of millable canes, cane length, cane girth and single cane weight for getting higher sugarcane yield. Furthermore, mechanization amicable genotypes can be selected which are near to erect nature and also having less crown weight.

Elucidating the G X E Interaction Using AMMI, AMMI Stability Parameters and GGE for Cane Yield and Quality in Sugarcane

Elucidating the G X E Interaction Using AMMI, AMMI Stability Parameters and GGE for Cane Yield and Quality in Sugarcane

Design of a portable bioassay system based on highly efficent nanozyme and Au-DNA nanocluster: Toward current/colorimetric dual-signal detection of sugarcane smut

Sugarcane smut is a major agricultural pest affecting sugarcane yield and quality, posing a significant threat to the sustainable and healthy development of the global sugar industry. The best strategy for controlling Sugarcane smut is early and precise diagnosis. An intelligent mobile bio-platform is constructed based on Au-Co/Zn ZIF nanozymes and Au-DNA nanoclusters for current/colorimetric dual signal detection of the sugarcane smut pathogen. Efficient and specific cycling of the specific gene fragment (bE4′) for Sugarcane smut is achieved by strand displacement reaction. The output strand then forms Au-DNA nanoclusters with AuNPs-DNA, and the bioconjugate is captured by H2 probe, which results in the formation of more double-stranded structures, causing methylene blue (MB) to adsorb on electrode. The anodic nanozyme efficiently catalyzes the oxidation of glucose, generating a large number of electrons, and MB in the system is therefore reduced to MBH, causing a color change. This results in distinct current/colorimetric dual output signals, significantly enhancing the accuracy. A capacitor is further coupled with the system to improve the sensitivity. The detection signals are read in real-time by a smartphone. The developed method for sugarcane smut genes shows good linearity within a concentration range of 0.0001–10000 pM, with a detection limit as low as 23.59 aM (S/N = 3). This work integrates advanced technologies from various fields to create a portable sensing device with extremely high sensitivity and precision for detecting sugarcane smut. It provides a reliable new option for early and precise diagnosis of the disease and offers valuable theoretical and technical insights for early prevention, intelligent detection, and real-time monitoring of other plant diseases.

Marker trait association and candidate gene identification for brown rust disease in sugarcane

AbstractBrown rust (caused by Puccinia melanocephala H. &amp; P. Sydow) is one of the most devastating diseases in commercial sugarcane production. It could reduce sugarcane yield by up to 50% depending on the susceptibility levels of cultivars. Breeding disease‐resistant cultivars is the most effective, economical, and environmentally friendly option to control brown rust. A genome‐wide association study was conducted on a field trial using 432 sugarcane clones following an augmented design with two replications. Brown rust was screened using the whorl inoculation method over two crop cycles. The genotype data were obtained through target enrichment sequencing technologies. The gene actions considering six different models and marker dosage effects were included during the marker‐trait analysis. A total of seven, nine, and seven nonredundant marker‐trait associations were identified for plant cane, first ratoon, and across two crop cycles, respectively. The most significant (p‐value 6.17E−20) marker (chr01p59833543) has the additive effect of −0.63 for the diplo‐additive model and reduced disease severity the most (41.35%) due to heterozygote (AG) over homozygote allele (AA) combination in the tested clones. Gene annotation of the monoploid sugarcane genome R570 suggested that six putative candidate genes were co‐located with significant markers associated with brown rust resistance in sugarcane. The putative candidate genes regulated the formation of a cell wall barrier that plays a crucial role in controlling brown rust pathogen infection. The results of this study will open the path to exploiting new resistance sources for brown rust resistance in commercial sugarcane.