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The judicious use of different organic and inorganic nutrient sources is of prime importance for enhancing the productivity of long-duration and nutrient-exhaustive crops, including sugarcane. We aimed to assess the impact of optimum nutrient application through integration of bio-products and inorganic fertilizers on growth, yield of sugarcane, and N availability in sugarcane plant crops raised through bud chip settlings. The fifteen treatment combinations were replicated three times in randomized block design. Results revealed that 150% of RDF + 5 t vermicompost ha−1 + 25 kg ZnSO4 + Azotobacter + phosphate solubilizing bacteria recorded the highest growth in terms of plant population, drymatter production, cane diameter, millable canes and single cane weight; cane yield (138.7 t ha−1) and net returns (Rs. 2, 62, 600 ha−1) followed by 150% RDF + 5 t vermicompost + 25 kg ZnSO4 ha−1 in sugarcane. However, maximum benefit: cost ratio was evidenced with 150% RDF alone (1.80) and lowest in RDF + 5 t vermicompost ha−1 (0.78), respectively. NO3-N, exchangeable NH4+-N, hydrolyzable NH4+-N were found to represent about 20.5 to 30.9, 41.5 to 73.8, 55.8 to 76.8 mg kg−1, respectively. The relative contents of these fractions were in the order: non-hydrolysable > unidentified N > amino acid N > hydrolyzable NH4+-N > exchangeable NH4+-N > NO3-N > hexose amine N. Thus, the integration of organic sources with NPK holds great promise to increase cane yield and N availability in soil but with 150% RDF proved to be more remunerative and economically sound for the bud chip raised sugarcane. [ABSTRACT FROM AUTHOR]

The aim of this research is to find out what factors influence sugar cane farmers in making decisions to use the services of the financial institution KSP Mitra Usaha Mandiri Semboro. And to find out what factors are most dominant in sugar cane farmers' decision to use the services of the financial institution KSP Mitra Usaha Mandiri Semboro. The factors in this research are reduced from service quality items which consist of the dimensions of Reliability, Responsiveness, Assurance, Empathy and Physical Evidence. The type of research used in this research is explanatory research. This research uses a quantitative descriptive method approach. The sample in this study was sugar cane farmers who were partners with PG Semboro and also KSP Mitra Usaha Mandiri, totaling 89 respondents. The sampling technique used was purposive sampling. The results of the research show that the factors that influence sugar cane farmers in making decisions to use the services of the financial institution KSP Mitra Usaha Mandiri Semboro are responsiveness, guarantees, quality and service as well as attention or empathy. Responsiveness is the most dominant factor taken into consideration by farmers in deciding to use financial services from KSP Mitra Usaha Mandiri Semboro, Jember Regency. [ABSTRACT FROM AUTHOR]

This paper intends to introduce a novel sugarcane plant disease prediction. There are three stages to the projected method, namely: (i) Preprocessing, (ii) Feature extraction, and (iii) Disease detection phase. Initially, the input image is given to the pre-processing stage in which the grey transformation and bilinear interpolation are carried out. The grey transformation is undergone to improve the clarity of the picture and the bilinear interpolation is used as a re-sampling technique. The feature extraction step follows the pre-processed picture, where both texture and colour features are retrieved. More specifically, the texture features like GLCM and suggested Distance-based LBP (D-LBP) features will be extracted. Subsequently, the extracted features are subjected to the disease detection phase process, where a hybrid classifier is introduced. This hybrid classifier blends the concepts of 'Neural Network (NN) and Support Vector Machine (SVM)' for better prediction results. In order to verify the effectiveness of the work that is suggested, a comparison analysis is conducted comparing the suggested and current approaches. The proposed method achieves highest accuracy in 80% of learning which is 13.97%, 16.12%, 11.82%, and 12.9% better than the other methods such as SVM, DT, RF, and NN, respectively. [ABSTRACT FROM AUTHOR]

This study focuses on creating predictive models for sugarcane yield in Bihar, utilizing various biometrical characteristics. The research involved collecting observations on specific plant biometrical traits from 50 farmers' fields of Samastipur, West Champaran and East Champaran Districts of Bihar. Simple random sampling was employed for field selection. Various regression analyses were conducted to identify the optimal combination. The accuracy of the model was assessed by comparing the actual yield from 10% of the observations not used in model development with their predicted values. The results demonstrated a close resemblance, with a margin of error ranging from 5.91% to 8.36%. The forecasted sugarcane yield for Bihar, based on the proposed model, is 847.82 q/ha. [ABSTRACT FROM AUTHOR]

Organic production systems are increasingly gaining market share; however, there are still few studies on their influence on the activity of soil microorganisms in sugarcane. Arbuscular mycorrhizal fungi are extremely sensitive to environmental changes, and their activity can be used as a parameter of comparison and quality between organic and conventional systems. The objective of this work was to evaluate mycorrhizal activity in different varieties of sugarcane under two production systems. This work was carried out in a commercial plantation of the Jalles Machado plant in the municipality of Goianésia in Goiás, Brazil. The values of spore density in the soil, mycorrhizal colonization rate in the roots and easily extractable glomalin were evaluated, and the associated fungal species were identified. There was no effect of sugarcane variety on the number of spores or the glomalin content in the soil. The conventional system presented significantly lower mycorrhizal colonization rates than did the organic system. The varieties cultivated under the conventional planting system showed a greater diversity of arbuscular mycorrhizal fungi, where 12 of the 13 different species of mycorrhizal fungi found in both cultivation systems occurred. [ABSTRACT FROM AUTHOR]

Geographically Weighted Panel Regression (GWPR), a combination of panel regression and geographically weighted regression (GWR), is used to analyze panel data and capture diverse relationship between locations. GWPR was developed on data with panel-fixed effects and applied to modeling data with spatial heterogeneity and time series. One method for estimating parameters in the GWPR is weighted least squares (WLS), which are sensitive to outliers. The present study aimed to use the Mmethod to estimate GWPR model parameters in data containing outliers using fixed-effect GWPR modeling for the sugar cane yield in East Java of Indonesia from 2019 to 2021. Sugarcane yield data in East Java contained outliers in several areas, including Malang, Blitar, and Ngawi Districts. Because the data contains outliers, a robust method with the M estimator was applied. The results showed that plantation areas significantly affected production in all districts. The R2 of the model was 0.87, showing that GWPR model with M estimation was appropriate in predicting sugarcane yield. Based on the Akaike Information Criterion (AIC) value, the GWPR model with M estimation had better performance than GWPR model alone. [ABSTRACT FROM AUTHOR]

Background: The research is based on the fertility status of the soil being affected year by year so here is a strategy to save the soil fertility level or soil health by the use of a leguminous cropping system. Methods: A study was conducted during 2018-2021 in the Meerut district of western Uttar Pradesh to evaluate the soil characterization of the rice - pea- sugarcane cropping system. The soil samples were analyzed for various parameters in the laboratory. The status of available NPK in soils and other soil properties like pH, electrical conductivity (EC) and organic carbon (OC) content were assessed. Result: Results reveal that the soils of the study area were neutral to strongly alkaline in reaction and non-saline in nature. Nutrient status regarding to the available nutrient in the surface (0-15 cm) and subsurface (15-30 cm) depth of soil indicate that soils are low in available N and medium in available P and K in surface and subsurface. A positive and significant correlation of NPK with organic matter content was found while significant and negative correlations exist between the soil pH. [ABSTRACT FROM AUTHOR]

Sugarcane white leaf (SCWL) disease, caused by Candidatus Phytoplasma sacchari, results in the most damage to sugarcane plantations. Some SCWL canes can grow unnoticed through the maturation phase, subsequently resulting in an overall low sugar yield, or they can be used accidentally as seed canes. In this work, 12-month-old SCWL and asymptomatic canes growing in the same field were investigated. An abundance of phytoplasma in SCWL canes affected growth and sugar content as well as alterations of transcriptomic profiles corresponding to several pathways that responded to the infection. Suppression of photosynthesis, porphyrin and chlorophyll metabolism, coupled with an increase in the expression of chlorophyllase, contributed to the reduction in chlorophyll levels and photosynthesis. Blockage of sucrose transport plausibly occurred due to the expression of sugar transporters in leaves but suppression in stalks, resulting in low sugar content in canes. Increased expression of genes associated with MAPK cascades, plant hormone signaling transduction, callose plug formation, the phenylpropanoid pathway, and calcium cascades positively promoted defense mechanisms against phytoplasma colonization by an accumulation of lignin and calcium in response to plant immunity. Significant downregulation of CPK plausibly results in a reduction in antioxidant enzymes and likely facilitates pathogen invasion, while expression of sesquiterpene biosynthesis possibly attracts the insect vectors for transmission, thereby enabling the spread of phytoplasma. Moreover, downregulation of flavonoid biosynthesis potentially intensifies the symptoms of SCWL upon challenge by phytoplasma. These SCWL sugarcane transcriptomic profiles describe the first comprehensive sugarcane–phytoplasma interaction during the harvesting stage. Understanding molecular mechanisms will allow for sustainable management and the prevention of SCWL disease—a crucial benefit to the sugar industry. [ABSTRACT FROM AUTHOR]

Pre-harvest burning of sugarcane is a major management system globally and could have a significant effect on soil organic carbon (SOC) fractions, aggregates stability and nutrient cycling, while green cane harvest system can be more beneficial to soil quality and environmental sustainability. The current study examined the effects of sugarcane harvest systems on SOC fractions and aggregate stability of sandy loam Umbric Rhodic Ferralsols, with relatively high SOC. Soil aggregate stability was determined using the wet-sieving method. SOC fractions were determined using the physical and chemical separation method, thereafter the SOC content in different fractions was determined by the wet oxidation method. Pre-harvest burning reduced soil aggregate stability by >100 and 64.3% when compared to green cane in the top 0–5 and 5–10 cm depths, respectively. The carbon in the macro-aggregates fraction constituted more than 60% of total SOC, making it the primary C storage fraction for both green cane and pre-harvest burning. Pre-harvest burning had 20.4 and 45.2% lower SOC content in macro- and micro-aggregate fractions, respectively, when compared to green cane. Also, coarse particulate organic matter carbon and fine particulate organic matter carbon were lower in pre-harvest burning management after the dispersion of macro-aggregates when compared to green cane. Pre-harvest burning increased mineral-associated C in µSilt + µClay from bulk soil fractionation by 23.7% when compared to green cane. All the C fractions decreased with an increase in soil depth in both green cane and pre-harvest burning, except for the mineral-associated C. These findings demonstrate that green cane production increases aggregate stability and SOC storage in different soil fractions, with a potential reduction in greenhouse gas emission and sustainable sugarcane production when compared with the pre-harvest burning on sandy loam Umbric Rhodic Ferralsols. [ABSTRACT FROM AUTHOR]

A homeobox transcription factor is a conserved transcription factor, ubiquitous in eukaryotes, that regulates the tissue formation of structure, cell differentiation, proliferation, and cancer. This study identified the homeobox transcription factor family and its distribution in Phoma sorghina var. saccharum at the whole genome level. It elucidated the gene structures and evolutionary characteristics of this family. Additionally, knockout experiments were carried out and the preliminary function of these transcription factors was studied. Through bioinformatics approaches, nine homeobox transcription factors (PsHOX1–PsHOX9) were identified in P. sorghina var. saccharum, and these contained HOX-conserved domains and helix–turn–helix secondary structures. Nine homeobox gene deletion mutants were obtained using the homologous recombinant gene knockout technique. Protoplast transformation was mediated by polyethylene glycol (PEG) and the transformants were identified using PCR. The knockouts of PsHOX1, PsHOX2, PsHOX3, PsHOX4, PsHOX6, PsHOX8, and PsHOX9 genes resulted in a smaller growth diameter in P. sorghina var. saccharum. In contrast, the knockouts of the PsHOX3, PsHOX6, and PsHOX9 genes inhibited the formation of conidia and led to a significant decrease in the pathogenicity. This study's results will provide insights for understanding the growth and development of P. sorghina var. saccharum. The pathogenic mechanism of the affected sugarcane will provide an essential theoretical basis for preventing and controlling sugarcane twisted leaf disease. [ABSTRACT FROM AUTHOR]

Basic breeding efforts initiated at the USDA‐ARS in Houma, LA, in the late 1950s allowed Louisiana sugarcane breeders, once again, to cross with the wild germplasm of cultivated sugarcane, Sacharum spontaneum. 'LCP 85‐384' was the first success story from this effort and was quickly adopted by growers. It became clear that the cultivar would prove to be substantially impactful to the Louisiana sugar industry. Performing at unprecedented yields in ratoon crops, LCP 85‐384 changed how Louisiana growers would manage their crops. The variety proved to possess traits that fared well in the subtropical production zones of the state. Substantial stalk populations seemed to play a vital role in the necessary ratoon ability and consequent cold tolerance necessary for production in Louisiana. After significant disease pressure, the variety quickly declined in production acreage, but not in impact. It continued to provide sustained progress as a parent for years, contributing to most modern commercial cultivars in Louisiana. Today, LCP 85‐384 and its progeny are used in breeding and genetic research to usher in the next era of progress in the Louisiana sugar industry. Meanwhile, through cooperative efforts of breeding programs around the world, it is making its mark on the sugarcane industries of Argentina in much the same way as it did in Louisiana. In the future, it is expected that the progress made in the breeding program will continue by building upon the gains achieved from LCP 85‐384 and its progeny for the sustained success of the Louisiana sugarcane industry. Core Ideas: LCP 85‐384 has shaped the Louisiana sugar industry in ways that are unprecedented.Combined increases in cane yield, harvesting efficiency, and stand longevity boosted sugar yield by about 22%.Its release coincided with the widespread adoption of mechanical combine harvesters which improved harvesting efficiency.Crossing with LCP 85‐384 has led to the release of 13 cultivars in Louisiana.In Argentina, it received wide adoption as a cultivar and is the parent of a newly released cultivar. [ABSTRACT FROM AUTHOR]

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 the 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 sugar is typically the only tall crop growing for a substantial fraction of time during the study period. Comparisons with field data, pre-existing maps, and official government statistics all indicated high precision and recall of our maps. Agreement with field data at the pixel level exceeded 80 % in most countries, and sub-national sugarcane areas from our maps were consistent with government statistics. Exceptions appeared mainly due to problems in underlying cropland masks, or 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. [ABSTRACT FROM AUTHOR]

Burning biomass on sugarcane plantations can lead to pollution (CO2 emissions) and degradation in soil properties. Adopting non-burning technology can increase the value of biomass by applying it directly to the soil, although this may result in nutrient immobilization, which can hinder optimal plant growth due to high lignin and cellulose content or high CN ratio. On the contrary, composting waste with a decomposer will boost plant nutrient availability and enhance other soil characteristics. This research was aimed to assess the effect of several types of sugarcane organic matter on improving soil characteristics, growth of sugarcane and the CO2 emissions. The study was conducted using a Completely Randomized Factorial Design with two factors: type of organic matter (control, fresh litter and compost of sugarcane biomass) and level of drought stress (100, 75, 50 and 25%). Incubation occurred over 16 weeks, divided into two phases of 8 weeks each. The results showed that the application of organic materials in the form of compost could reduce water loss caused by environmental heat and sugarcane growing process. Furthermore, compost application improved soil chemical and biological properties by increasing soil pH, total nitrogen (N), total phosphate (P), total potassium (K), and the total microbial population, although differences were not significant compared to the control. Additionally, applying organic matter in the form of compost or litter helped suppress or reduce emissions, with compost treatment proving more effective than litter in reducing CO2 emissions. [ABSTRACT FROM AUTHOR]

BACKGROUND: The sugarcane billbug, Sphenophorus levis Vaurie 1978, is a key soil‐dwelling insect pest of sugarcane in Brazil and greatly affects plant development and yield. This insect presents an aggregated distribution pattern in production fields. The reasons for such behavior include intraspecific communication and attractivity due to the fermentation of sugar in stalk residues. During mechanized harvesting, part of the harvested material usually falls in the load transfer sites, becoming a potential source for increasing the infestation. We therefore evaluated whether producing areas near the harvest load transfer sites are more prone to S. levis injury. RESULTS: There are greater chances of finding billbug injury within a radius of 740 m from the harvest load transfer site. Additionally, injured areas are estimated to expand 11.96% each growing season. Our spatiotemporal models support higher injured areas surrounding the harvest load transfer site and show clear and significant signs of increased injury levels compared to the initial growing season surveyed. CONCLUSION: Our results reinforce the importance of harvest transfer sites in the dispersion and propagation of the sugarcane billbug. Based on this knowledge, sugarcane millers and growers can adopt preventive and remedial practices within the loading sites that can potentially contribute to the successful management of this insect pest. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

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Smallholders cultivated sugarcane for household consumption, immediate cash, and feeding livestock in Ethiopia. However, its production and productivity are constrained by a lack of improved varieties. Sugarcane germplasm was collected from Districts of West Gojjam, Ethiopia, to evaluate yield and its contributing characters and quantify the phenotypic diversity at Mankusa, Jabitehnan, Ethiopia. The experiment was conducted using a randomised complete block design with three replications for two crop cycles, from April 2020 to March 2023. Data were recorded for the number of tillers, internode length, sellable stalks, plant height, stalk diameter, cane yield and biomass yield from twelve genotypes collected. The data recorded were subjected to analysis of variance, and means were separated using the Duncan Multiple Range Test at a 5% significance level. Variance and multivariate analysis indicated the existence of high phenotypic diversity between genotypes in all quantitative traits studied. Acc 7/20 and Acc 5/20 genotypes produced the highest number of tillers and longest internodes, while Acc 6/20 produced the highest number of sellable stalks. The genotype Acc 4/20 was the longest, and the thickest genotype, which could be elite donors for it respected quality traits through crossing. The highest cane yield was recorded from Acc 4/20 (178.04 t/ha), Acc 7/20 (151.41 t/ha), Acc 8/20 (134.1 t/ha) and Acc 12/20 (132 t/ha), producing 58, 34, 19 and 17% advantageous from the overall genotypes mean, respectively. Cluster analysis grouped the twelve sugarcane genotypes into four clusters, indicating the possibility of broadening the genetic basis by crossing genotypes in the different clusters. It also indicated that a cross between cluster II and III genotypes could create the thickest canes with many sellable stalks. Therefore, genotypes Acc 04/20, Acc 07/20, Acc 8/20 and Acc 12/20 have been recommended and must be evaluated in other sugarcane growing areas to exploit their potential. [ABSTRACT FROM AUTHOR]

In the present study, Pleurotus tuber-regium (Rumph. ex Fr.) Singer collected from Keeriparai forest of Kanyakumari district, South India was cultivated using environmentally benign, low-cost agricultural waste residues (paddy straw, sugarcane bagasse, rice husk, and sawdust) as growth substrates. The main goal of this study was to assess the cultivation, yield, and nutritional value of P. tuber-regium fruiting bodies grown under different growth substrates. Spawn running time and time for primordia formation were found to be shorter in mushroom growing with paddy straw substrate compared to sawdust and sugarcane bagasse. A quick spawn run time was observed in paddy straw substrate (12 ± 1 day) followed by sugarcane bagasse (15 ± 1 day) and sawdust (23 ± 1 day). The primordia was well developed in the macrofungus grown with paddy straw substrate on 18 ± 1 day followed by sugarcane bagasse (22 ± 1 day) and sawdust (32 ± 1 day). Significantly higher yield of fruiting bodies with increased contents of protein and carbohydrate and low level of fat was obtained when P. tuber-regium was cultivated with paddy straw substrate. While, cultivation of P. tuber-regium in sawdust and sugarcane bagasse resulted in increased contents of K, Na, Ca, and Mg along with highest energy value. On the other hand, rice husk did not support the cultivation of this macrofungus. Therefore, it is of significant interest to initiate the commercial production of this macrofungus so as to fight against the problems of malnutrition found in few African and south Asian countries. [ABSTRACT FROM AUTHOR]

Sugarcane (Saccharum spp.), a major cash crop that is an important source of sugar and bioethanol, is strongly influenced by the impacts of biotic and abiotic stresses. The intricate polyploid and aneuploid genome of sugarcane has shown various limits for conventional breeding strategies. Nonetheless, biotechnological engineering currently offers the best chance of introducing commercially significant agronomic features. In this study, an efficient Agrobacterium-mediated transformation system that uses the herbicide-resistant CP4-EPSPS gene as a selection marker was developed. Notably, all of the plants that were identified by PCR as transformants showed significant herbicide resistance. Additionally, this transformation protocol also highlighted: (i) the high yield of transgenic lines from calli (each gram of calli generated six transgenic lines); (ii) improved selection; and (iii) a higher transformation efficiency. This protocol provides a reliable tool for a routine procedure for the generation of resilient sugarcane plants. [ABSTRACT FROM AUTHOR]

Introduction: Remorins (REMs) are plant-specific membrane-associated proteins that play important roles in plant-pathogen interactions and environmental adaptations. Group I REMs are extensively involved in virus infection. However, little is known about the REM gene family in sugarcane (Saccharum spp. hyrid), the most important sugar and energy crop around world. Methods: Comparative genomics were employed to analyze the REM gene family in Saccharum spontaneum. Transcriptomics or RT-qPCR were used to analyze their expression files in different development stages or tissues under different treatments. Yeast two hybrid, bimolecular fluorescence complementation and co-immunoprecipitation assays were applied to investigate the protein interaction. Results: In this study, 65 REMs were identified from Saccharum spontaneum genome and classified into six groups based on phylogenetic tree analysis. These REMs contain multiple cis-elements associated with growth, development, hormone and stress response. Expression profiling revealed that among different SsREMs with variable expression levels in different developmental stages or different tissues. A pair of alleles, ScREM1.5e-1/-2, were isolated from the sugarcane cultivar ROC22. ScREM1.5e-1/-2 were highly expressed in leaves, with the former expressed at significantly higher levels than the latter. Their expression was induced by treatment with H2O2, ABA, ethylene, brassinosteroid, SA or MeJA, and varied upon Sugarcane mosaic virus (SCMV) infection. ScREM1.5e-1 was localized to the plasma membrane (PM), while ScREM1.5e-2 was localized to the cytoplasm or nucleus. ScREM1.5e-1/-2 can self-interact and interact with each other, and interact with VPgs from SCMV, Sorghum mosaic virus, or Sugarcane streak mosaic virus. The interactions with VPgs relocated ScREM1.5e-1 from the PM to the cytoplasm. Discussion: These results reveal the origin, distribution and evolution of the REM gene family in sugarcane and may shed light on engineering sugarcane resistance against sugarcane mosaic pathogens. [ABSTRACT FROM AUTHOR]

In-field quality prediction in agricultural products is mainly based on near-infrared spectroscopy (NIR). However, initiatives applied to sugarcane quality are only observed under laboratory-controlled conditions. This study proposed a framework for NIR spectroscopy sensing to measure sugarcane quality during a real harvest operation. A platform was built to support the system composed of the NIR sensor and external lighting on the elevator of a sugarcane harvester. Real-time data were acquired in commercial fields. Georeferenced samples were collected for calibration, validation, and adjustment of the multivariate models by partial least squares (PLS) regression. In addition, subsamples of defibrated cane were NIR-acquired for the development of calibration transfer models by piecewise direct standardization (PDS). The method allowed the adjustment of the spectra collected in real time to predict the quality properties of soluble solids content (Brix), apparent sucrose in juice (Pol), fiber, cane Pol, and total recoverable sugar (TRS). The results of the relative mean square error of prediction (RRMSEP) were from 1.80 to 2.14%, and the ratio of interquartile performance (RPIQ) was from 1.79 to 2.46. The PLS-PDS models were applied to data acquired in real-time, allowing estimation of quality properties and identification of the existence of spatial variability in quality. The results showed that it is possible to monitor the spatial variability of quality properties in sugarcane in the field. Future studies with a broader range of quality attribute values and the evaluation of different configurations for sensing devices, calibration methods, and data processing are needed. The findings of this research will enable a valuable spatial information layer for the sugarcane industry, whether for agronomic decision-making, industrial operational planning, or financial management between sugar mills and suppliers. [ABSTRACT FROM AUTHOR]

The sugarcane crop has great socioeconomic relevance because of its use in the production of sugar, bioelectricity, and ethanol. Mainly cultivated in tropical and subtropical countries, such as Brazil, India, and China, this crop presented a global harvested area of 17.4 million hectares (Mha) in 2021. Thus, decision making in this activity needs reliable information. Obtaining accurate sugarcane yield estimates is challenging, and in this sense, it is important to reduce uncertainties. Currently, it can be estimated by empirical or mechanistic approaches. However, the model's peculiarities vary according to the availability of data and the spatial scale. Here, we present a systematic review to discuss state-of-the-art sugarcane yield estimation approaches using remote sensing and crop simulation models. We consulted 1398 papers, and we focused on 72 of them, published between January 2017 and June 2023 in the main scientific databases (e.g., AGORA-FAO, Google Scholar, Nature, MDPI, among others), using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. We observed how the models vary in space and time, presenting the potential, challenges, limitations, and outlooks for enhancing decision making in the sugarcane crop supply chain. We concluded that remote sensing data assimilation both in mechanistic and empirical models is promising and will be enhanced in the coming years, due to the increasing availability of free Earth observation data. [ABSTRACT FROM AUTHOR]

The precise estimation of sugarcane yield at the field scale is urgently required for harvest planning and policy-oriented management. Sugarcane yield estimation from satellite remote sensing is available, but satellite image acquisition is affected by adverse weather conditions, which limits the applicability at the field scale. Secondly, existing approaches from remote sensing data using vegetation parameters such as NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index) have several limitations. In the case of sugarcane, crop yield is actually the weight of crop stalks in a unit of acreage. However, NDVI's over-saturation during the vigorous growth period of crops results in significant limitations for sugarcane yield estimation using NDVI. A new sugarcane yield estimation is explored in this paper, which employs allometric variables indicating stalk magnitude (especially stalk height and density) rather than vegetation parameters indicating the leaf quantity of the crop. In this paper, UAV images with RGB bands were processed to create mosaic images of sugarcane fields and estimate allometric variables. Allometric equations were established using field sampling data to estimate sugarcane stalk height, diameter, and weight. Additionally, a stalk density estimation model at the pixel scale of the plot was created using visible light vegetation indices from the UAV images and ground survey data. The optimal stalk density estimation model was applied to estimate the number of plants at the pixel scale of the plot in this study. Then, the retrieved height, diameter, and density of sugarcane in the fields were combined with stalk weight data to create a model for estimating the sugarcane yield per plot. A separate dataset was used to validate the accuracy of the yield estimation. It was found that the approach presented in this study provided very accurate estimates of sugarcane yield. The average yield in the field was 93.83 Mg ha−1, slightly higher than the sampling yield. The root mean square error of the estimation was 6.63 Mg ha−1, which was 5.18% higher than the actual sampling yield. This study offers an alternative approach for precise sugarcane yield estimation at the field scale. [ABSTRACT FROM AUTHOR]

The impacts of sugarcane (Saccharum spp.) production include an extensive area of cultivation, high use of technology, and the generation of by‐products that must be utilized. Achieving higher productivity while reducing the expansion of cultivation is challenging. A potential strategy for increasing sugarcane yields and productivity is the foliar application of nutrients and biostimulants at different stages of sugarcane growth. The present study assessed the impact of the foliar application of nutrients (N, B, Cu, and Zn) and a growth regulator as biostimulant (indole butyric acid, gibberellic acid, and kinetin) on sugarcane metabolism, stalk and sugar production, and quality. Field experiments were performed at 17 sites during four growing seasons (2017–2018, 2018–2019, 2019–2020, and 2020–2021) using sugarcane with three harvest times (early, mid‐late, and late harvests). The treatments were as follows: (i) no foliar application of the biostimulant and nutrients (control), (ii) foliar application of the biostimulant and nutrients at the vegetative stage (VS) of sugarcane, (iii) foliar application of the biostimulant and nutrients at the maturation stage (MS) of sugarcane, and (iv) foliar application of the biostimulant and nutrients at both the vegetative and maturation stages (VMS). Foliar application did not increase ribulose 1,5‐bisphosphate carboxylase activity but increased phosphoenolpyruvate carboxylase activity and the activities of the antioxidant enzymes. Peroxidase and catalase activities were higher, >100% and 45%, respectively, in VMS, whereas superoxide dismutase activity increased by 54% in MS compared with control. Consistent with these results, sugarcane had low hydrogen peroxide and malondialdehyde contents in VMS. In addition, the plant biometric parameters were highest in VMS, which sugarcane produced 105, 92, and 86 Mg stalk h−1 in early, mid‐late, and late harvest seasons, respectively. In summary, the foliar application of the biostimulant and nutrients efficiently promoted the growth, productivity, and quality of early, mid‐late, and late harvest seasons. The positive effects of foliar application on the enzymatic and physiological responses of sugarcane can be achieved when applications are performed in both the VMS in all harvest seasons. Core Ideas: Biostimulants are precursors of plant hormone production and its enzymatic metabolism.Foliar application at vegetative and maturation stages effectively increased sugarcane yields in all harvests.Increases in sugarcane antioxidant activity and growth were obtained by foliar application. [ABSTRACT FROM AUTHOR]

The primary objective of sugarcane (Saccharum spp.) variety testing programs is to identify cultivars that have high cane yields and good ratooning ability (RA). The purpose of this study was to evaluate the usefulness of six RA indices to estimate RA among sugarcane varieties and to identify an index well suited to predict RA in long‐term ratoon crop cycles. The six indices were as follows: ratoon crops yield means, second ratoon to plant cane yield ratio, final ratoon crop to plant cane yield ratio, mean of ratoon crops to plant cane yield ratio (RP), linear regression, and quadratic regression. Data from four variety trials consisting of eight post‐release varieties plus a control, harvested early, mid, and late in the cropping season for over six crop cycles, were used to estimate the RA indices. To identify indices that can predict RA in long‐term ratoon crop cycles, simple linear regression analyses were used to compare the RA indices derived from 6‐year crop cycles and similar indices derived from data from 111 commercial fields harvested over 11 successive crops. Coefficient of determination (R2) values plotted against their respective ratoon crop numbers were used to determine the minimum number of ratoon crops required to accurately predict RA indices for the 11‐year crop cycle. The six indices varied in their rankings of the RA of varieties, emphasizing the importance of identifying the most appropriate indices for different ratooning practices. Based on its highest R2 value of 0.92, the RP index was identified as the most accurate index to predict RA in long‐term ratoon crop cycles requiring a minimum of five successive crops. Core Ideas: Harvest times had a larger impact on sugarcane varieties ratooning ability (RA) than variety and location effects.The "average of ratoon crops to plant cane yield ratios" index was identified as the most accurate to predict RA for long‐term ratoon cycles.The optimum number of test years required by this index to identify superior varieties is 5 years compared to six currently used. [ABSTRACT FROM AUTHOR]

A subsurface irrigation system "OPSIS" (optimized subsurface irrigation system) developed in Japan is expected to have high application efficiency because percolation water from irrigation pipes is restrained by an impervious liner sheet installed under the irrigation pipes, and non-consumptive irrigation water is circulated and reused as irrigation water. This study aimed to clarify the water-saving effects of OPSIS while maintaining crop yield. In this study, sugarcane was cultivated in fields where OPSIS was installed, and soil moisture was monitored using soil moisture sensors. The fields were located on Ishigaki Island, Japan, which occasionally experiences drought, mainly during the dry season (from July to August), with highest evapotranspiration and low precipitation. The results showed that soil moisture during the dry season was maintained above the soil water content of the primary wilting point by a lower irrigation water supply than the recommended rate provided by sprinklers on Ishigaki Island. The sugarcane yields were also higher than the average yield on Ishigaki Island. These results confirm that OPSIS contributes to higher crop production with less irrigation compared with sprinkler-based irrigation. [ABSTRACT FROM AUTHOR]

Sugarcane is one of the leading commercial crops grown in India. The prevailing weather during the various crop-growth stages significantly impacts sugarcane productivity and the quality of its juice. The objective of this study was to predict the yield of sugarcane during different growth periods using machine learning techniques viz., random forest (RF), support vector machine (SVM), stepwise multiple linear regression (SMLR) and artificial neural networks (ANN). The performance of different yield forecasting models was assessed based on the coefficient of determination (R2), root mean square error (RMSE), normalized root mean square error (nRMSE) and model efficiency (EF). Among the models, ANN model was able to predict the yield at different growth stages with higher R2 and lower nRMSE during both calibration and validation. The performance of models across the forecasts was ranked based on the model efficiency as ANN > RF > SVM > SMLR. This study demonstrated that the ANN model can be used for reliable yield forecasting of sugarcane at different growth stages. [ABSTRACT FROM AUTHOR]

Sugarcane is the most important cash crop for producing sugar and the most promising high-yield bioenergy crop in China. Lai-bin is a major sugarcane growing and karst area in the Guangxi Province of China. However, frequent droughts over the years have caused huge losses on sugarcane production in this region. Therefore, the daily quantitative response mechanisms of sugarcane growth to multiple meteorological drought scenarios were discovered in Lai-bin using the DSSAT−CANEGRO model. The daily Standardized Precipitation Evapotranspiration Index (SPEI) was developed to detect the possible scenarios of meteorological drought events over the sugarcane growth periods. The results indicate that, in general, the inhibitory effect on sugarcane growth is enhanced by the increase in the intensity and duration of meteorological drought, which involved cane yield (CY), stem height (SH), leaf area index (LAI), and evapotranspiration (ET). Additionally, a light drought at the seedling stage and a light, moderate, and severe drought at the maturity stage give a promotion effect on sugarcane growth, but its overall CY increase rate is less than 5%. The stem elongation stage is the most sensitive period of sugarcane growth to all scenarios of meteorological drought, and the CY reduction rates reached 7.12%, 16.48%, 18.80%, and 29.05%, when the plants suffered from light, moderate, severe, and extreme meteorological droughts, respectively. Alternate drought–flood scenarios presented a facilitating or an inhibiting effect on sugarcane growth during different periods, which cannot be ignored. In conclusion, the quantitative function relationships between meteorological drought and sugarcane growth are revealed by this study. [ABSTRACT FROM AUTHOR]

The total amount of sugarcane planting in China ranks third in the world, and Guangxi is the largest sugarcane planting base in China. In order to help the Guangxi government and industry better understand the annual planting distribution and scale of sugarcane in the whole region, it is convenient to optimize the planting structure and improve the efficiency of resource utilization, so as to ensure the stable development of Guangxi sugar industry. Based on the satellite-based hyperspectral image data of ' Zhuhai No.1 ', this paper carries out sugarcane recognition and area extraction, which fills the application gap of satellite-based hyperspectral image data in extracting sugarcane area in China. A globally optimized extended random walk model was used to identify and extract sugarcane by combining the spatial-spectral information of hyperspectral imagery. Firstly, the Initial probability estimation is performed using the LOR classifier, and then use the data after MNF dimensionality reduction to construct a weighted graph, and finally the probability optimization and recognition are carried out based on the extended random walk model. The results show that the spatial-spectral joint method based on extended random walk can effectively identify sugarcane, and the sugarcane recognition accuracy of 2021 year image can reach 91.4%, the misrecognition rate is 2.8%; the sugarcane recognition accuracy of 2020 year image can reach 90.5 %, the misrecognition rate is 3.1%. [ABSTRACT FROM AUTHOR]

Sugarcane is an annual or perennial persistent rooted tropical and subtropical herb that grows in tropical and subtropical regions. As China's production ranks among the world's leading, sugarcane industry is an important part of agricultural economy in China. As the largest sugarcane production center in China, Guangxi is one of the most suitable areas for sugarcane cultivation in China and even in the world. Sugarcane industry, as an agricultural advantageous industry in Guangxi, not only has a significant image to the national economy of the region, but also is closely related to the issue of security of national sugar supply. Continuous cropping of sugarcane is very common in Guangxi, which is very helpful for the concentration selection of sugarcane samples. The wide application of satellite remote sensing monitoring technology has become an indispensable means of natural resources monitoring. Using optical satellite remote sensing image to identify and extract sugarcane planting areas is of great significance to quickly and conveniently grasp the information of sugarcane distribution and yield. In this paper, the precision of sugarcane extraction from GF1 and GF2 satellite images is analyzed by using deeplab V3 + model, the effect of optical remote sensing images with different resolution on sugarcane extraction accuracy was studied to provide better data support for dynamic monitoring of sugarcane planting. [ABSTRACT FROM AUTHOR]

The sugar industry, which relates to people's livelihood, is strategic and fundamental in the development of agricultural economy. In China, sugar derived from sugarcane accounts for approximately 85% of total sugar production. Mechanization is the "flower" of sugarcane industry. As the saying goes "when there are blooming flowers, there will be sweet honey." However, due to limitations in land resources, technology, equipment, organization, and management, mechanization throughout the sugarcane production process has not yet brought about the economic benefits that a mechanized system should provide and has not reached an ideal yield through the integration of agricultural machinery and agronomic practice. This paper briefly describes how to initiate the mechanization of Chinese sugarcane production to promote the sound, healthy, and rapid development of the sugarcane industry, and how to ultimately achieve the transformation of sugarcane breeding in China and the modernization of the sugarcane industry from three perspectives, namely, requirements of mechanized production for sugarcane varieties, breeding strategies for selecting new sugarcane varieties suitable for mechanized production, and screening for sugarcane varieties that are suitable for mechanization and diversification in variety distribution or arrangement in China. We also highlight the current challenges surrounding this topic and look forward to its bright prospects. [ABSTRACT FROM AUTHOR]

Stability analysis is one of the most important steps that a breeder should use to release a new variety for a region. To identify and introduce the best sugarcane genotypes, an experiment with 26 promising Sugarcane genotypes along with four commercial varieties was planned and implemented during 2017–2019. This study aimed to determine a promising stable sugarcane genotype for the sugarcane-growing areas of Khuzestan Province in Iran. The effects of genotype × environment interactions on the sugar yield of 26 promising sugarcane genotypes and four standard varieties as controls were investigated for the new plant (P), first ratoon (R1), and second ratoon (R2) at three locations (Amir Kabir, Imam Khomeini, and Mianab) for three cropping seasons. For the final analysis every year, quantitative and qualitative characteristics were measured by sampling 10 stalks of each genotype in each replication and each experiment. A combined analysis was conducted with regard to the fixed effects of the genotype and environment and the random effect of the year. The sugar yield stability of the genotypes was evaluated based on nonparametric, ecovalence, Shukla, simultaneous selection, and AMMI statistical methods. According to the results, g 2 , g 4 , g 5 , g 7 , g 11 , g 12 , g 14 , g 16 , g 19 , g 20 , g 21 , g 23 , g 24 , g 26 , g 27 , g 28 , g 29 , and g 30 are the most stable genotypes based on statistical analyses. As these genotypes have general stability and can be cultivated in three crops, they are introduced for commercial cultivation. According to an AMMI biplot, genotype g 6 was considered to have special adaptation to the first location (Imam Khomeini), genotypes g 8 and g 15 were specifically adapted to the second location (Amir Kabir), and genotypes g 10 , g 17 , and g 22 showed special adaptation to the third location (Mianab). Therefore, these genotypes are introduced for commercial cultivation in the mentioned locations. [ABSTRACT FROM AUTHOR]

The World Collection of Sugarcane and Related Grasses, maintained at the USDA-ARS in Miami, FL, is one of the largest sugarcane germplasm repositories in the world. However, the genetic integrity of the Saccharum spp. germplasm in this collection has not been fully analyzed. In this study, we employed a single-dose SNP panel to genotype 901 sugarcane accessions, representing six Saccharum species and various hybrids. Our analysis uncovered a high rate of clone mislabeling in the collection. Specifically, we identified 86 groups of duplicates, characterized by identical SNP genotypes, which encompassed 211 accessions (23% of the total clones), while 135 groups, constituting 471 clones (52% of the total), exhibited near-identical genotypes. In addition, twenty-seven homonymous groups were detected, which shared the same clone name but differed in SNP genotypes. Hierarchical analysis of population structure partitioned the Saccharum germplasm into five clusters, corresponding to S. barberi, S. sinense, S. officinarum, S. spontaneum and S. robustum/S. edule. An assignment test, based on the five Saccharum species, enabled correcting 141 instances of mislabeled species memberships and inaccuracies. Moreover, we clarified the species membership and parentage of 298 clones that had ambiguous passport records (e.g., ‘Saccharum spp’, ‘unknown’, and ‘hybrid’). Population structure and genetic diversity in these five species were further supported by Principal Coordinate Analysis and neighbor- joining clustering analysis. Analysis of Molecular Variance revealed that within- species genetic variations accounted for 85% of the total molecular variance, with the remaining 15% attributed to among-species genetic variations. The single-dose SNP markers developed in this study offer a robust tool for characterizing sugarcane germplasm worldwide. These findings have important implications for sugarcane genebank management, germplasm exchange, and crop genetic improvement. [ABSTRACT FROM AUTHOR]

In a context of growing importance of alternative carbon-low hydrogen production methods, this review addresses aspects of fermentative biohydrogen (bioH 2) production from juice, molasses and vinasse, the primary substrates available in sugarcane biorefineries, following three primary fronts. The characterization of the main bioreactors utilized and the most frequent environmental and operating conditions are initially detailed. Performance results in terms of bioH 2 production, substrate conversion, soluble phase metabolites distribution and microbial community characterization are addressed in the sequence. Finally, some challenges and prospects are discussed. Thermophilic (55 °C) fixed-film and fluidized-bed reactors were identified as the primary systems used in bioH 2 production, with most common applied organic loading rates (OLR) varying within 50–90 and 30–120 kg COD m−3 d−1, respectively. Overall, hydrogen production rates of up to 10,000 NmL H 2 L−1 d−1 prevail, regardless of the substrate and reactor, whilst the hydrogen yield systematically decreases as the OLR is increased. Metabolic pathways involving lactic acid production and consumption seem to determine whether or not bioH 2 (almost always together with butyric acid) will be produced (mainly by Clostridium and Thermoanaerobacterium genera). Exploiting substrate co-fermentation, finding low-cost pH control approaches and better characterizing microbial metabolic functions were identified as key points to be addressed in future research. Identifying uses that energetically and economically justify producing fermentative bioH 2 from sugarcane-derived substrates also needs to be critically defined. Once these major challenges are solved, the scale-up of bioH 2 -producing systems has potential to be rationally implemented in sugarcane biorefineries. • The biohydrogen production potential of sugarcane-derived substrates was reviewed. • Thermophilic fixed- and fluidized-bed reactors are the main systems assessed. • Biohydrogen evolution largely depends on lactate-producing and consuming pathways. • Clostridium and Thermoanaerobacterium are the main biohydrogen-producing genera. • Defining techno-economically feasible uses for biohydrogen is highly necessary. [ABSTRACT FROM AUTHOR]

Sugar cane (Saccharum officinarum L.) are the main ingredient in sugar production. Sugarcane is widely cultivated in warm and tropical areas and used as a sweetener because it contains a lot of fructose and glucose. National sugar production shows a decline, caused mainly by pathogens, especially the fungus Bipolaris sp., which can produce up to 85% damage per ha if no control is applied. Biological control using Trichoderma spp. can control this pathogen and promote sugarcane growth. This study aimed to determine the effectiveness of Trichoderma spp. in controlling Bipolaris sp. in vitro. The method used is an antagonistic and volatile bioassay test. Testing was conducted in PDA medium and observed every day for 7 days. The results showed that isolates TD1, TD2, and TD3 could inhibit Bipolaris sp. antagonistically and volatilely; the antagonist test showed a result of 86% (TD1), while the volatile test was 65% (TD2). In conclusion, Trichoderma spp. can inhibit the growth of Bipolaris sp. on an in vitro scale. [ABSTRACT FROM AUTHOR]

Sugarcane (Saccharum hybrid) is an important cash crop grown in tropical and subtropical countries. Ratoon stunting disease (RSD), caused by a xylem-inhabiting bacterium, Leifsonia xyli subsp. xyli (Lxx) is one of the most economically significant diseases globally. RSD results in severe yield losses because its highly contagious nature and lack of visually identifiable symptoms make it harder to devise an effective management strategy. The efficacy of current management practices is hindered by implementation difficulties caused by lack of resources, high cost, and difficulties in monitoring. Rapid detection of the causal pathogen in vegetative planting material is crucial for sugarcane growers to manage this disease. Several microscopic, serological, and molecular-based methods have been developed and used for detecting the RSD pathogen. Although these methods have been used across the sugarcane industry worldwide to diagnose Lxx, some lack reliability or specificity, are expensive and time-consuming to apply, and most of all, are not suitable for on-farm diagnosis. In recent decades, there has been significant progress in the development of integrated isothermal amplification-based microdevices for accurate human and plant pathogen detection. There is a significant opportunity to develop a novel diagnostic method that integrates nanobiosensing with isothermal amplification within a microdevice format for accurate Lxx detection. In this review, we summarize (i) the historical background and current knowledge of sugarcane ratoon stunting disease, including some aspects related to transmission, pathosystem, and management practices; and (ii) the drawbacks of current diagnostic methods and the potential for application of advanced diagnostics to improve disease management. [ABSTRACT FROM AUTHOR]

Random roving survey was carried out for the incidence and relative abundance of different rice stem borers in three coastal districts viz., Vizianagaram, Srikakulam and Nellore of Andhra Pradesh, India during Kharif 2021. The damage was quantified through the dead hearts and white ears symptoms and species through a destructive sampling of the infested tillers. The survey revealed the occurrence of three different species of rice stem borers viz., Yellow stem borer (YSB), Scirpophaga incertulas (Walker), Pink stem borer (PSB), Sesamia inferens (Walker), and Gold fringed stem borer (GFSB) Chilo auricilius (Dudgeon). The damage by stem borers ranged from 10.91 to 14.70 per cent in the surveyed mandals of Srikakulam (Amadalavalasa, Srikakulam and Seethampeta), Vizianagarm (Merakamudidam, Therlam and Garividi) and Nellore (Venkatagiri, Nellore and Dakkili) districts of Andhra Pradesh. Among the stem borers, YSB was the most predominant species, with 84.26 per cent followed by GFSB with 12.41 per cent in Srikakulam and Vizianagaram districts. A high incidence of GFSB, Chilo auricilius (80 %) was noticed in Seethampeta mandal in Srikakulam district, which is a hilly area where sugarcane is grown predominantly. In Nellore district, yellow stem borer is the only species prevalent where mono-cropping and staggered planting of rice throughout the year is practiced where low PSB incidence (3.33 %) was recorded in Venkatagiri mandal of Nellore district. This study clearly brings out the variation in the abundance of rice stem borer complex prevailing in rice-based cropping systems in different districts of Andhra Pradesh. [ABSTRACT FROM AUTHOR]

One of the most important crops in the world, sugarcane, is constantly in danger from a number of diseases that can have a negative impact on the crop's productivity and quality. The cultivation of sugarcane is significantly hampered by one of these, Sugarcane Leaf Scald (SLSD). Effective SLSD management depends on early and precise illness identification. Due to their capacity to analyze enormous datasets and identify nuanced patterns, deep learning algorithms have recently come to be recognized as potent instruments for disease diagnosis in agricultural contexts. The diagnosis of diseases caused by Sugarcane Leaf Scald is presented in this research utilizing cutting-edge deep learning methods. We start by gathering a sizable dataset of photos of sugarcane leaves that spans several disease progression phases and includes both healthy and infected samples. Utilizing a Convolutional Neural Network (CNN) architecture, discriminative features are automatically discovered and extracted from these photos. Using methods like data augmentation and transfer learning, the deep learning model is trained on this dataset to improve its performance. The suggested deep learning-based approach's results show that it can correctly categorize sugarcane leaves as either healthy or SLSD-infected. The model may also determine the severity of the condition, which helps develop specialized disease management plans. High accuracy, precision, and recall rates are among the encouraging performance indicators the suggested system displays, indicating its potential as a dependable tool for early SLSD detection in sugarcane fields. The investigation shows how well deep learning algorithms work in diagnosing SLSD, which advances the field of agricultural disease management. The suggested method provides a non-invasive, affordable, and scalable answer for tracking and controlling sugarcane infections, thereby boosting crop output and the long-term viability of sugarcane farming. [ABSTRACT FROM AUTHOR]

Objective: To determine the economic threshold for Diatraea spp. in the Córdoba-Golfo sugarcane growing region in Veracruz, Mexico. Design/Methodology/Approach: During the 2020-2021 production cycle, we established 21 sampling plots to measure damage percentage due to borer larvae in sugarcane stalks. Based on these measurements, we calculated the economic damage level (EDL) and the economic threshold (ET) by regions and subregions. Results: The most affected subregion was Yanga, with an average annual damage of more than 5 % and a real economic threshold of 1.36. The average ET in the Córdoba-Golfo region was 2.76, which indicates that applying control strategies for Diatraea spp. enables the regulation of insect populations. Study limitations/Implications: Strategies to obtain reality-driven diagnoses are still necessary to design and apply assertive management procedures to control stalk borer populations in the field. Findings/Conclusions: We posit a suitably calculated ET for each studied subregion, considering updated parameters that include real crop losses per zone (field performance). This can provide the basis for a course of action with an effective management that will, in turn, increase field performance and sugarcane juice quality. [ABSTRACT FROM AUTHOR]

Sugarcane production benefitted from useful genes imparted from Saccharum spontaneum L. Interspecific hybrids were evaluated for sugar and biomass traits in three environments, including two plants and one ratoon crop. The objective was to estimate genetic parameters for traits in this population and to develop appropriate breeding strategies and germplasm for use in variety development in both the sugar and bioenergy industries. Heritability was highest with all three environments considered; however, the increase was minimal compared with estimates from the first ratoon crop, suggesting resources will be better spent selecting in the first ratoon crop. Significant differences (p < 0.05) found among families for sucrose content‐related traits warrant selecting first among families before selecting among genotypes within families for these traits. The same was not true for cane yield and its components. Heritability was low to moderate (> 0.3 < 0.47) for cane yield and its components and high (> 0.7) for all other traits, suggesting early selection in small plots could emphasize sucrose content‐related traits. Selecting intensely for a highly heritable trait in one stage can influence genetic variation of another trait in subsequent stages. Therefore, multivariate selection methods were employed that identified groups of genotypes with characteristics distinct to both industries. The S. spontaneum parents dominated trait variation in the hybrid population. Consequently, although genotypes with potential for the sugar industry would have to undergo rounds of backcrossing to recover good sugar characteristics, genotypes with immediate potential in the bioenergy industry were easily identified in this population. Core Ideas: Sugarcane production for the sugar industry has benefitted from useful genes imparted from Saccharum spontaneum L.There is interest in exploiting S. spontaneum L. to improve production in the sugar and energy (biomass) industries.The resourcefulness of an interspecific hybrid population to produce germplasm for both industries was evaluated.Genotypes with immediate potential in the bioenergy industry were easily identified in this population.Genotypes with potential for the sugar industry would have to undergo backcrossing to recover good sugar attributes. [ABSTRACT FROM AUTHOR]

Sugarcane is rich in dietary fibers and is known for its positive effects on the gastrointestinal tract. It offers a wide array of health benefits for mammals. The sugar industry generates substantial residue amounts. Fermenting sugarcane with probiotic strains positively impacted gut flora in all instances. Maintaining the viability of these probiotic microorganisms is crucial when creating functional food products. Several factors can reduce their effectiveness in the gut. Sugarcane juice contains high levels of nutrients, minerals, and polyphenolic compounds, devoid of allergens and easily accessible. Fruit juices serve as excellent carriers for probiotics. Creating probiotic beverages while preserving taste and appearance is an innovative approach. The combination of probiotics and other dietary substances is gaining interest in promoting gastrointestinal health. Sugarcane juice, rich in nutrients and beneficial properties, is an optimal vehicle for probiotic organisms, contributing to overall health. Consequently, selecting appropriate probiotics and ensuring their effective delivery poses a technological challenge. This paper offers an overview of research articles summarizing procedures and techniques for enhancing probiotic viability. It also discusses ongoing research and challenges while outlining future opportunities for researchers based on existing literature. [ABSTRACT FROM AUTHOR]

Sugarcane straw (Saccharum officinarum) is a valuable coproduct renowned for its abundant polyphenolic content. However, extracting these polyphenols for natural ingredients faces challenges due to their inherent variability, influenced by biotic stress factors and plant characteristics. We explored the impact of five crucial factors on sugarcane straw polyphenolic diversity: (i) production area (Guariba, Valparaíso), (ii) borer insect (Diatraea saccharalis) infestation, (iii) plant age (first to seventh harvest), (iv) harvest season, and (v) plant variety. Response surface methodology (RSM) and artificial neural networks (ANN) were used to optimize polyphenol extraction conditions. A second-order polynomial model guided us to predict ideal sugarcane straw harvesting conditions for polyphenol-rich extracts. The analysis identified CU0618-variety straw, harvested in Guariba during the dry season (October 2020), at the seventh harvest stage, with 13.81% borer insect infection, as the prime source for high hydroxybenzoic acid (1010 µg/g), hydroxycinnamic acid (3119 µg/g), and flavone (573 µg/g) content and consequently high antioxidant capacity. The ANN model surpasses the RSM model, demonstrating superior predictive capabilities with higher coefficients of determination and reduced mean absolute deviations for each polyphenol class. This underscores the potential of artificial neural networks in forecasting and enhancing polyphenol extraction conditions, setting the stage for AI-driven advancements in crop management. [ABSTRACT FROM AUTHOR]

Advancements in remote sensing techniques have greatly enhanced crop monitoring and yield estimation, with spectral vegetation indices (VIs) serving as a key component. Our study investigates the use of Sentinel-2 data, notable for its red-edge bands, in estimating sugarcane yield in Ethiopia's Awash Basin. Utilizing 22 VIs from S2 imagery, our approach combines Random Forest (RF) regression with the Recursive Feature Elimination (RFE) algorithm to improve the accuracy of sugarcane yield predictions. The results demonstrate the superior performance of the RF-RFE method over traditional RF with full datasets and Stepwise Multiple Regression (SMR). Particularly, VIs focusing on the red-edge spectral bands of S2 - such as NDVIre1n, NDVIre2n, NDVIre3n, NDRE1 and NDRE2 - were crucial in enhancing prediction precision. These indices from the red-edge and NIR narrow bands consistently influenced yield estimations in both the Wonji-Shoa and Metehara estates. The study underscores the critical role of the RFE algorithm in optimal variable selection, reinforcing earlier findings that precise variable choice can substantially boost model accuracy. The enhanced performance of the RF model when paired with the RFE algorithm was evident, emphasizing the importance of variable selection in accurate yield predictions. Employing the Out-of-Bag RMSE (OOB_RMSE) error estimate for evaluation, we observed variations in OOB_RMSE performance with different RF parameters, identifying the ntree value of 500 as optimal for the studied regions. The RF-RFE model's estimations showed lower errors and higher correlation coefficients, proving its efficacy over a full dataset approach, which faced challenges with traditional VIs' saturation. Our findings align with earlier studies, highlighting the efficiency of S2's red-edge bands in diverse estimation tasks and a shift towards using freely available broadband images like S2, over hyperspectral imagery, due to reduced data redundancy and processing costs. In conclusion, our findings reveal that RF regression, particularly when integrated with the RFE algorithm, is a powerful tool in remote sensing applications. The S2 imagery is optimal VIs, predominantly from the red-edge bands, exhibit significant potential for sugarcane yield estimations. The impressive results of the RF-RFE method, evident in metrics like MAE, MAPE, RMSE, Mean percentage, and R2, advocate its invaluable role in sugarcane yield prediction, highlighting its potential for optimizing irrigation management strategies and broad-spectrum agricultural planning. [ABSTRACT FROM AUTHOR]

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Soil salinity and saline irrigation water are major constraints in sugarcane affecting the production of cane and sugar yield. To understand the salinity induced responses and to identify novel genomic resources, integrated de novo transcriptome and small RNA sequencing in sugarcane wild relative, Erianthus arundinaceus salt tolerant accession IND 99-907 and salt-sensitive sugarcane genotype Co 97010 were performed. A total of 362 known miRNAs belonging to 62 families and 353 miRNAs belonging to 63 families were abundant in IND 99-907 and Co 97010 respectively. The miRNA families such as miR156, miR160, miR166, miR167, miR169, miR171, miR395, miR399, miR437 and miR5568 were the most abundant with more than ten members in both genotypes. The differential expression analysis of miRNA reveals that 221 known miRNAs belonging to 48 families and 130 known miRNAs belonging to 42 families were differentially expressed in IND 99-907 and Co 97010 respectively. A total of 12,693 and 7982 miRNA targets against the monoploid mosaic genome and a total of 15,031 and 12,152 miRNA targets against the de novo transcriptome were identified for differentially expressed known miRNAs of IND 99-907 and Co 97010 respectively. The gene ontology (GO) enrichment analysis of the miRNA targets revealed that 24, 12 and 14 enriched GO terms (FDR < 0.05) for biological process, molecular function and cellular component respectively. These miRNAs have many targets that associated in regulation of biotic and abiotic stresses. Thus, the genomic resources generated through this study are useful for sugarcane crop improvement through biotechnological and advanced breeding approaches. [ABSTRACT FROM AUTHOR]