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Abstract Sugarcane is a vital crop with significant economic and industrial value. However, the cultivated sugarcane’s ultra-complex genome still needs to be resolved due to its high ploidy and extensive recombination between the two subgenomes. Here, we generate a chromosomal-scale, haplotype-resolved genome assembly for a hybrid sugarcane cultivar ZZ1. This assembly contains 10.4 Gb genomic sequences and 68,509 annotated genes with defined alleles in two sub-genomes distributed in 99 original and 15 recombined chromosomes. RNA-seq data analysis shows that sugar accumulation-associated gene families have been primarily expanded from the ZZSO subgenome. However, genes responding to pokkah boeng disease susceptibility have been derived dominantly from the ZZSS subgenome. The region harboring the possible smut resistance genes has expanded significantly. Among them, the expansion of WAK and FLS2 families is proposed to have occurred during the breeding of ZZ1. Our findings provide insights into the complex genome of hybrid sugarcane cultivars and pave the way for future genomics and molecular breeding studies in sugarcane.

Abstract Crop divider toes are an essential device of sugarcane harvester. Moving forward against the ground is a critical way to improve the harvesting rate of lodged sugarcane. Height detection is the basis for precise control of crop divider toes moving forward against the ground. Due to the current problem of operating difficulties in manually adjusting the height of crop divider, a height detection system based on a millimeter wave radar sensor was designed to detect the height of crop divider toes from the ground. This paper proposed a height detection method of crop divider toes for sugarcane harvester based on Kalman adaptive adjustment. The data measured by the sensor was pretreated to determine whether the height had changed. Reset the Kalman filter and adjust the parameters when changes occur to improve the filter response speed and ranging accuracy. To adapt to the scenario of quickly adjusting the height of crop divider during the traveling process of sugarcane harvester. A one-way ANOVA test and a two-way ANOVA test were conducted on a simulated test platform. The results of the one-way ANOVA test showed that both forward speed and vegetation cover thickness had a significant effect on height detection accuracy. The results of the two-way ANOVA test showed that the interaction of forward speed and vegetation cover thickness did not have a significant effect on ranging accuracy. It was verified through experiments that both the ranging accuracy and the response speed of height change were significantly improved after the processing of the method in this paper. The mean square error after processing was lower than 2.5 cm. The feasibility of the height detection system was verified by field trials. The results of this study will provide a reference for the design of automatic elevation of crop divider.

IntroductionSugarcane stem node detection is one of the key functions of a small intelligent sugarcane harvesting robot, but the accuracy of sugarcane stem node detection is severely degraded in complex field environments when the sugarcane is in the shadow of confusing backgrounds and other objects.MethodsTo address the problem of low accuracy of sugarcane arise node detection in complex environments, this paper proposes an improved sugarcane stem node detection model based on YOLOv7. First, the SimAM (A Simple Parameter-Free Attention Module for Convolutional Neural Networks) attention mechanism is added to solve the problem of feature loss due to the loss of image global context information in the convolution process, which improves the detection accuracy of the model in the case of image blurring; Second, the Deformable convolution Network is used to replace some of the traditional convolution layers in the original YOLOv7. Finally, a new bounding box regression loss function WIoU Loss is introduced to solve the problem of unbalanced sample quality, improve the model robustness and generalization ability, and accelerate the convergence speed of the network.ResultsThe experimental results show that the mAP of the improved algorithm model is 94.53% and the F1 value is 92.41, which are 3.43% and 2.21 respectively compared with the YOLOv7 model, and compared with the mAP of the SOTA method which is 94.1%, an improvement of 0.43% is achieved, which effectively improves the detection performance of the target detection model.DiscussionThis study provides a theoretical basis and technical support for the development of a small intelligent sugarcane harvesting robot, and may also provide a reference for the detection of other types of crops in similar environments.

The article discusses a wavelet-based approach for recognizing sugarcane stem nodes in order to improve pre-cut sugarcane planting technology, beginning with sugarcane form characteristics that permit automated sugarcane seed production. The location signal is collected by the acceleration and thin-film piezoelectric sensors and then decomposed into the tenth, eleventh, and twelfth layers using the Daubechies tight-branch wavelet. After capturing the signal, it is reconstructed and superimposed to capture the stem node region’s features using the default threshold technique. A multi-sensor fusion approach is developed based on a weighted average and a Kalman filter to confirm the experiment’s validity. The weighted average process produces an average value that is 0.3512 mm off from the experimentally observed data average. The discrepancy between the Kalman filter method’s anticipated average value and the empirically determined average error is 0.5778 mm. To facilitate the investigation, 175 sugarcane samples with intermediate length processing are used. The detecting position system is determined experimentally after extensive experimental research and diligent examination. On average, the standard deviation is 0.494 mm, while the maximum value is 9.99 mm. 99.63 percent of cane seed samples are detected, with an error rate of 0.37 percent and a response time of 0.25 seconds. The proposed technology is conceptually feasible and achievable, and it can provide a reference for the development of automated cane seed pre-cutting machinery to give its contribution to agricultural production.

Citrus huanglongbing (HLB) is extremely difficult to control because the psyllid-transmitted bacterial pathogen resides inside the citrus phloem and the disease is systemic. In Florida, the nine billion dollar citrus industry has been significantly impacted by severe HLB epidemics. To combat citrus HLB, in this study we implemented an integrated strategy that includes chemotherapy, thermotherapy, and additional nutrition treatment in three different field trials over three consecutive years. In these trials, only trees already showing HLB symptoms with Ct values ranging from 25.1 to 27.7 were selected for treatments. To assess the complex interactions, we used several methods for evaluating the effectiveness of integrated management, including the slopes (b) of the Ct increase (dy/dt), the pathogenic index (PI) and the decline index (DI) from Ct value and tree scores, and the therapeutic efficacies from PI and DI. This comprehensive analysis showed that most of the tested chemicals were effective to some degree in killing or suppressing the Las bacterium, with higher therapeutic efficacies seen for Grove B, where citrus trees were severely affected by HLB, and it had a higher number of psyllids, relative to Grove E and P in the first 2 years. Trunk-injected penicillin G potassium was the most effective chemical treatment in all groves, followed by Oxytetracycline Calcium Complex, and Silver Nitrate delivered as foliar sprays. Although the steam heat treatment and additional nutrition did not eliminate or suppress Las over the long term, these treatments did positively affect tree growth and recovery in the short term. Overall, our results provide new insights into HLB control method and strategy for integrated management for HLB epidemic plantations.

Development of easily defoliating sugarcane varieties is urgently needed to facilitate efficient mechanical harvesting, reduce production costs, and increase sugar yield in China. In order to quantify the defoliation characteristics of sugarcane, we investigated eight traits in two field experiments with a range of sugarcane varieties at maturity. The length (LSR) and angle (ASR) of the sheath ruptured from the stalk, defoliation force (DF), and self-defoliation (SD) were the traits with the greatest contribution to the quantitative assessment of sugarcane defoliation based on a principal component analysis, which accounted for more than 75% of the cumulative variability. A small set of traits, namely SD, ASR, and DF measured at the 10th leaf were selected as predictors. Using these predictors, 37 out of 38 sugarcane cultivars were correctly classified into three groups (easy, difficult and intermediate in terms of ease of defoliation) that had been clustered based on six traits. These simplified measurements will be applied to screen new lines in the sugarcane breeding program in China.

To improve the automation of the whole stalk sugarcane combine harvester and reduce the work intensity of the driver of the sugarcane collection and transfer vehicle, a sugarcane field collection and transfer vehicle that follows a ranging system was independently designed in this article . Then, a data processing method that extracts the numerical mutation features and combines the sliding mean filtering of the fluctuation characteristics of the ranging data in rugged and hilly land was proposed. First, frequency modulated continuous wave (FMCW) radar was used to measure the distance between two vehicles. The effects of the travel speed and shaking angle on the ranging accuracy were analyzed according to the working environment. The results showed that they have significant effects on the ranging results. Second, the abnormal data were identified and replaced using numerical mutation features, and then sliding mean filtering was applied to the replaced overall data. Finally, the system was implemented in an experiment in the field, and the results showed that the ranging accuracy of the system was significantly improved. The average relative error was reduced from 0.12% to 0.05%, and the ranging stability was good. [ABSTRACT FROM AUTHOR]

To predict and assess production conditions of sugarcane in Guangxi in 2016, by using methods of field survey and data collection, the seedling situation, breed structure, planting area, planting period, plant diseases and insect pests of sugarcane in six major sugarcane producing cities of Guangxi were surveyed. The results show that the overall situation of sugarcane seedlings in Guangxi in 2016 became slightly worse than that in 2015, but there were enough good sugarcane seedlings in 2016. The dead heart rate of sugarcane decreased in most sugarcane regions from 2015 to 2016, that is, the comprehensive control of borers gave initial results; the smut infection rate of sugarcane rose from 2015 to 2016 and tended to increase. The situation of decrease in the planting area of sugarcane in three consecutive years was controlled, and the planting area of sugarcane increased slightly from 2015 to 2016. Due to the construction of "double high" bases, the breed variety of sugarcane in Guangxi was improved further in 2016. It is necessary to strengthen field management and conduct chemical weeding, prevention and control of borers and aphids in the later period in time. [ABSTRACT FROM AUTHOR]

Salinity is a major abiotic stress to barley ( Hordum vulgare L.) growth and yield. In the current study, quantitative trait loci (QTL) for yield and physiological components at the late growth stage under salt stress and non-stress environments were determined in barley using a double haploid population derived from a cross between CM72 (salt-tolerant) and Gairdner (salt-sensitive). A total of 30 QTLs for 10 traits, including tiller numbers (TN), plant height, spikes per line (SPL), spikes per plant (SPP), dry weight per plant, grains per plant, grain yield, shoot Na+ (NA) and K+ concentraitions (K) in shoot, and Na+/K+ ratio (NAK), were detected, with 17 and 13 QTLs under non-stress and salt stress, respectively. The phenotypic variation explained by individual QTL ranged from 3.25 to 29.81%. QTL flanked by markers bPb-1278 and bPb-8437 on chromosomes 4H was associated with TN, SPL, and SPP under salt stress. This locus may be useful in the breeding program of marker-assisted selection for improving salt tolerance of barley. However, QTLs associated with NA, K, and NAK differed greatly between non-stress and salt stress environments. It may be suggested that only the QTLs detected under salt stress are really associated with salt tolerance in barley. [ABSTRACT FROM AUTHOR]

The effect of salinity on some physiological parameters in 16 barley genotypes with different salt tolerance was investigated. The results showed 50 mM NaCl treatment increased Na + /K + ratio, malondialdehyde (MDA) and proline contents, and decreased cell membrane stability index (CMSI) and fresh shoot biomass (FSB) of all tested genotypes. Salt stress also resulted in a decreased chlorophyll (Chl) content and net photosynthesis (Pn) for most genotypes. Under higher salt stress (300 mM NaCl), the marked increase for Na + /K + , MDA, and proline content, and decrease for other parameters were found for all genotypes. The affected extent of these parameters by salt stress varied with genotypes. Proline accumulation in barley was associated with injured extent under salt stress, indicating it is not a defensive reaction to the stress. K + uptake was less affected, whereas Na + accumulation in plants was enhanced under high salt stress. The correlation analysis showed that MDA and proline content, Na + concentration and Na + /K + were negatively correlated with FSB, whereas other parameters examined in the study were positively correlated with FSB. [ABSTRACT FROM AUTHOR]

Sugarcane-duck symbiosis (SDS) is an ecological breeding production method wherein meat ducks are released in sugarcane (Saccharum officinarum L.) fields during the middle and late stages of sugarcane growth. The effects of SDS on sugarcane rhizobacterial diversity remain poorly understood. We conducted field experiments with sugarcane monoculture (SC) and SDS and performed genetic analyses on the rhizobacterial communities based on 16S rRNA across different growth stages of sugarcane. The effects of soil physicochemical factors on the bacterial community structure were analyzed via redundancy analysis. We found that soil organic matter (SOM), total N (TN), nitrate N (NN), and ammonium N (AN) contents of sugarcane rhizosphere soils increased during different growth periods in SDS. During the perennial root stages, the Shannon-, Ace-, and Chao1 indices increased, whereas the available P (AP) content decreased. The soil pH was more balanced and its effect on the soil bacterial community was insignificant. The dominant sugarcane rhizosphere flora were Actinobacteria, Proteobacteria, Chloroflexi, Acidobacteria, Firmicutes, norank_f__norank_o__Gaiellales, Sphingomonas, norank_f__Roseiflexaceae, Bacillus, and norank_f__Xanthobacteraceae, but with significant inter-annual variations. Redundancy analysis showed that SOM, TN, NN, AN, AP, catalase (CAT) and invertase (INV) activity were closely associated with the diversity of the soil bacterial communities, and TN and INV activity were the main drivers of sugarcane rhizobacterial communities in the SDS groups. In conclusion, SDS improves the fertilizer supply capacity and soil quality of sugarcane soils by regulating major soil nutrient content, available nutrients, and microbial diversity. This study provides a theoretical basis for scientifically managing SDS and the screening of biocontrol bacteria. [ABSTRACT FROM AUTHOR]