Search

Exploring the temporal evolution dynamics of different soil organic nitrogen (N) components under different water–N management practices is a useful approach to accurately assessing N supply and soil fertility. This information can provide a scientific basis for precise water and N management methods for greenhouse vegetable production. The objective of this study was to investigate the effects of optimized irrigation and nitrogen management on the dynamics of soil organic nitrogen fractions, soil properties, and crop growth. This research was conducted from 2017 to 2023 in a greenhouse vegetable field in North China. Four treatments were applied: (1) high chemical N application with furrow irrigation (farmers’ practice, FP); (2) no chemical N application with drip irrigation (DN0); (3) 50% N of FP with drip irrigation (DN1); and (4) 75% N of FP with drip irrigation (DN2). The volume in drip irrigation is 70% of that in furrow irrigation. The results showed that in 2023 (after seven years of field trials), compared with FP, the soil organic carbon (SOC), total N, and water use efficiency of the DN1 and DN2 treatments increased by 15.9%, 11.4%, and 11.3% and 7.7%, 47.2% and 44.6%, respectively. However, there was no significant difference in the total crop yield except in the DN0 treatment. Soil organic N was mostly in the form of acid-hydrolyzed N (AHN). After seven years of optimized irrigation and N management, the DN1 treatment significantly increased the content of ammonium N (AN) and amino sugar N (ASN) in AHN compared with the FP treatment. The results of further analysis demonstrated that SOC was the main factor in regulating AHN and non-hydrolyzable N (NHN), while the main regulatory factors for amino acid N (AAN) and ASN in the AHN component were dry biomass and water use efficiency, respectively. From a time scale perspective, optimization of the water and N scheduling, especially in DN1 (reducing the total irrigation volume by 30% and the amount of N applied by 50%), is crucial for the sustainable improvement of soil fertility and the maintenance of vegetable production.

IntroductionWater is one of the important factors affecting the yield of leafy vegetables. Lettuce, as a widely planted vegetable, requires frequent irrigation due to its shallow taproot and high leaf evaporation rate. Therefore, screening drought-resistant genotypes is of great significance for lettuce production.MethodsIn the present study, significant variations were observed among 13 morphological and physiological traits of 42 lettuce genotypes under normal irrigation and water-deficient conditions.ResultsFrequency analysis showed that soluble protein (SP) was evenly distributed across six intervals. Principal component analysis (PCA) was conducted to transform the 13 indexes into four independent comprehensive indicators with a cumulative contribution ratio of 94.83%. The stepwise regression analysis showed that root surface area (RSA), root volume (RV), belowground dry weight (BDW), soluble sugar (SS), SP, and leaf relative water content (RWC) could be used to evaluate and predict the drought resistance of lettuce genotypes. Furthermore, the drought resistance ranks of the genotypes were similar according to the drought resistance comprehensive evaluation value (D value), comprehensive drought resistance coefficient (CDC), and weight drought resistance coefficient (WDC). The cluster analysis enabled the division of the 42 genotypes into five drought resistance groups; among them, variety Yidali151 was divided into group I as a strongly drought-resistant variety, group II included 6 drought-resistant genotypes, group III included 16 moderately drought-resistant genotypes, group IV included 12 drought-sensitive genotypes, and group V included 7 highly drought-sensitive genotypes. Moreover, a representative lettuce variety was selected from each of the five groups to verify its water resistance ability under water deficit conditions. In the drought-resistant variety, it was observed that stomatal density, superoxide anion (O2.−wfi2) production rate, and malondialdehyde (MDA) content exhibited a low increase rate, while catalase (CAT), superoxide dismutase (SOD), and that peroxidase (POD) activity exhibited a higher increase than in the drought-sensitive variety.DiscussionIn summary, the identified genotypes are important because their drought-resistant traits can be used in future drought-resistant lettuce breeding programs and water-efficient cultivation.

In order to precisely obtain the impact of nutritional elements on lettuce yield and quality, in the present study, a nutrient solution formula suitable for lettuce hydroponic production was development using response surface methodology based on the determination for micro-elements in three growth stages and taking the interaction between elements into account. Then, the formula was optimized and validated, aiming for the goal of improving lettuce yield and quality. The results showed that 200 healthy lettuce leaves contained similar amounts of macro-elements, and there was no significant difference in the unit content of micro-elements among the seedling, rosette, and harvest stages. Quadratic regression models between shoot fresh weight, SPAD value, soluble sugar content, Vc content, and nutrient content were established (R2 = 0.91, 0.95, 0.98, and 0.81, respectively). The optimal concentrations of P, K, Ca, and Mg obtained by multi-objective optimization of the quadratic regression models for fresh weight, SPAD value, soluble sugar content, and Vc content were 2.71 mmol·L−1, 6.42 mmol·L−1, 5.58 mmol·L−1, and 7.11 mmol·L−1, respectively. The nutrient solution formula (T1) was found to be the optimal nutrient solution formula for improving lettuce growth and quality. Overall, we developed a specific and targeted nutrient solution formulation for lettuce; this formulation not only meets lettuce’s demand for nutrients, but also improves lettuce yield and quality, providing more choices for lettuce production in a region with high salts and high pH in the irrigation water.

Reduced available water resources have become the main limiting factor for the production of leafy vegetable, such as pakchoi, which can be effectively addressed by growing water-efficient varieties. Therefore, it is particularly important for evaluation and verification of drought tolerant varieties. In this study, 50 different varieties of pakchoi were detected for their morphological and physiological indicators under both normal-irrigated and water-deficiency environments. Based on systematic analysis of these evaluation indicators using different evaluation methods, the significant indicators were identified and the prediction model was established followed by validation of different drought tolerant of pakchoi varieties. The results showed that considerable differences were observed in all the indicators detected under conditions of water deprivation compared with normal irrigation. Frequency distribution revealed that the indictors sensitivity with significant changes to water-deficient conditions was ordered as follows: aboveground fresh and dry weight, followed by belowground fresh and dry weight, root volume, root length, root activity, and soluble sugar. Correlation analysis showed that each indicator was significantly or extremely significantly associated with other indices, indicating that there is a certain degree of association between the indices. Principal component analysis (PCA) turned 16 indicators into four independent components, with a cumulative contribution ratio of 80.147%. According to the results of drought tolerance comprehensive evaluation value (D-value) analysis and cluster analysis, 50 varieties were ranked in relation to drought tolerance and classified into five categories, among them Jinhui, Qingguan, Dongyue, Xiazhijiao, and Hanszifei, which were classified as highly drought-tolerant cultivars. Moreover, the stepwise regression model was established and demonstrated that soluble sugar, average root diameter, belowground fresh weight, root volume, and leaf number were selected as key indicators which can be used for screening and identifying drought-pakchoi varieties. Furthermore, the tolerance capacity of pakchoi varieties was further validated using one representative variety selected from five groups and treated with water-deficit stress. It was demonstrated that the established model was verified consistent with drought tolerance of pakchoi varieties, and tolerance capacity was closely related to increasing epidermal stomatal density, maintaining high photosynthesis, and increasing antioxidant enzyme activity to reduce damage (ROS). The results proposed the key drought tolerance indicators and evaluation methods, which provide the basis for the screening of leaf-vegetable varieties with different drought-tolerances, as well the identified varieties could be used for effective water-saving production.

The phenotypic parameters of crop plants can be evaluated accurately and quickly using an unmanned aerial vehicle (UAV) equipped with imaging equipment. In this study, hundreds of images of Chinese cabbage (Brassica rapa L. ssp. pekinensis) germplasm resources were collected with a low-cost UAV system and used to estimate cabbage width, length, and relative chlorophyll content (soil plant analysis development [SPAD] value). The super-resolution generative adversarial network (SRGAN) was used to improve the resolution of the original image, and the semantic segmentation network Unity Networking (UNet) was used to process images for the segmentation of each individual Chinese cabbage. Finally, the actual length and width were calculated on the basis of the pixel value of the individual cabbage and the ground sampling distance. The SPAD value of Chinese cabbage was also analyzed on the basis of an RGB image of a single cabbage after background removal. After comparison of various models, the model in which visible images were enhanced with SRGAN showed the best performance. With the validation set and the UNet model, the segmentation accuracy was 94.43%. For Chinese cabbage dimensions, the model was better at estimating length than width. The R2 of the visible-band model with images enhanced using SRGAN was greater than 0.84. For SPAD prediction, the R2 of the model with images enhanced with SRGAN was greater than 0.78. The root mean square errors of the 3 semantic segmentation network models were all less than 2.18. The results showed that the width, length, and SPAD value of Chinese cabbage predicted using UAV imaging were comparable to those obtained from manual measurements in the field. Overall, this research demonstrates not only that UAVs are useful for acquiring quantitative phenotypic data on Chinese cabbage but also that a regression model can provide reliable SPAD predictions. This approach offers a reliable and convenient phenotyping tool for the investigation of Chinese cabbage breeding traits.

Abstract Background Drought is one of the most serious factors limiting plant growth and production. Sheepgrass can adapt well to various adverse conditions, including drought. However, during germination, sheepgrass young seedlings are sensitive to these adverse conditions. Therefore, the adaptability of seedlings is very important for plant survival, especially in plants that inhabit grasslands or the construction of artificial grassland. Results In this study, we found a sheepgrass MYB-related transcription factor, LcMYB2 that is up-regulated by drought stress and returns to a basal level after rewatering. The expression of LcMYB2 was mainly induced by osmotic stress and was localized to the nucleus. Furthermore, we demonstrate that LcMYB2 promoted seed germination and root growth under drought and ABA treatments. Additionally, we confirmed that LcMYB2 can regulate LcDREB2 expression in sheepgrass by binding to its promoter, and it activates the expression of the osmotic stress marker genes AtDREB2A, AtLEA14 and AtP5CS1 by directly binding to their promoters in transgenic Arabidopsis. Conclusions Based on these results, we propose that LcMYB2 improves plant drought stress tolerance by increasing the accumulation of osmoprotectants and promoting root growth. Therefore, LcMYB2 plays pivotal roles in plant responses to drought stress and is an important candidate for genetic manipulation to create drought-resistant crops, especially during seed germination.

Sorghum is one of the most promising bioenergy crops. Stem juice yield, together with stem sugar concentration, determines sugar yield in sweet sorghum. Bulked segregant analysis (BSA) is a gene mapping technique for identifying genomic regions containing genetic loci affecting a trait of interest that when combined with deep sequencing could effectively accelerate the gene mapping process. In this study, a dry stem sorghum landrace was characterized and the stem water controlling locus, qSW6, was fine mapped using QTL analysis and the combined BSA and deep sequencing technologies. Results showed that: (i) In sorghum variety Jiliang 2, stem water content was around 80% before flowering stage. It dropped to 75% during grain filling with little difference between different internodes. In landrace G21, stem water content keeps dropping after the flag leaf stage. The drop from 71% at flowering time progressed to 60% at grain filling time. Large differences exist between different internodes with the lowest (51%) at the 7th and 8th internodes at dough stage. (ii) A quantitative trait locus (QTL) controlling stem water content mapped on chromosome 6 between SSR markers Ch6-2 and gpsb069 explained about 34.7-56.9% of the phenotypic variation for the 5th to 10th internodes, respectively. (iii) BSA and deep sequencing analysis narrowed the associated region to 339 kb containing 38 putative genes. The results could help reveal molecular mechanisms underlying juice yield of sorghum and thus to improve total sugar yield.

[Objective]This study was conducted to investigate the relationship between each of planting density and row spacing and plant productivity of forage sweet sorghum planted in autumn idle land. [ Methods] Using split-plot experiment design experiment method and LSD method of IBM. SPSS. Statistics. v22 statistics software, the effects of planting density and row spacing on plant productivity of forage sweet sorghum planted in autumn idle land were compared. [ Result] The results showed that the planting density and row spacing had important influences on plant productivity of forage sweet sorghum planted in autumn idle land. Moreover, the optimal combination of plant productivity for A, B, i. e., under the combination of the planting density of 7. 5 X 104 plants/hm2 and the row spacing of 40 cm, the fresh weight and dry weight per plant were 654.37 and 147.11 g/plant, respectively. [ Conclusion] The results provided a theoretical basis for the production of forage sweet sorghum in autumn idle land. [ABSTRACT FROM AUTHOR]

[ Objective] The aim was to optimize the configuration of seedling density and line spacing of forage sweet sorghum (Sorghum bicolor (L. ) Moench) and explore its high-yield cultivation techniques. [Methods] Effects of such two influencing factors as line spacing ad seedling density on the leaf-stem ratio, DW/FW ratio and grass yield of forage sweet sorghum were analyzed by using split-plot experiment design experiment method and LSD method of IBM. SPSS. Statistics. v22 statistics software. [ Results] Seedling density ad line spacing had no obvious effect on the lea-stem ratio and DW /FW ratio of forage sweet sorghum but had obvious influences on the grass yield. Moreover, the optimal combination of seedling density and line spacing for high yield of forage sweet sorghum was A2B4, that is, seedling density was 225 000 plants/hm², and line spacing was 40 cm. [ Conclusions] The results provided a theoretical basis and technical support for high-yield cullivation techniques of forage sweet sorghum. [ABSTRACT FROM AUTHOR]

The aim of this study is to standardize the planting technology of sweet sorghums for forage, to prepare? technical specifications for planting sweet sorghums for forage. Based on yeas of experiment, it is prepared according to the requirements of GB/1. 1 Standardization Guide Rule Part I: Standard Structure and Compilation. The results show that it defines the application scope, basic requirements, preparation before sowing, planting requirements, field management, harvesting requirements of the technical specifications for planting sweet sorghums for forages, and determines the specific measures and technical indicators of the technical specifications. This paper provides technical suppor for the standardization, industrialization and marketization of planting sweet sorghums for forage. [ABSTRACT FROM AUTHOR]

Background: Sorghum is mainly used as a human food and beverage source, playing an important role in the production of ethanol and other bio-industrial products. Thus it is regarded as a model crop for energy plants. Genetic map construction is the foundation for marker-assisted selection and gene cloning. So far several sorghum linkage maps have been reported using different kinds of molecular markers. However marker numbers and chromosome coverage are limited. As a result, it is difficult to get consistent results and the maps are hard to unify. In the present study, the genomes of 130 individuals consisting an F2 population together with their parents were surveyed using a high-throughput sequencing technique. A high-density linkage map was constructed using specific-locus amplified fragments (SLAF) markers. This map can provide information and serve as a reference for effective gene exploration, and for marker assisted-breeding program. Results: A high-throughput sequencing method was adopted to screen SLAF markers with 130 F2 individuals from a cross between a grain sorghum variety, J204, and a sweet sorghum variety, Keter. In the present study, 52,928 suitable SLAF markers out of 43,528,021 pair-end reads were chosen to conduct genetic map construction, 12.0% of which were polymorphic. Among the 6353 polymorphic SLAF markers, 5829 (91.8%) were successfully genotyped in the F2 mapping population. Finally 2246 SLAF markers were obtained to construct a high-density genetic linkage map. The total distance of linkage map covering all 10 chromosomes was 2158.1 cM. The largest gap on each chromosome was 10.2 cM on average. The proportion of gaps less than and/or equal to 5.0 cM was averagely 98.1%. The markers on each chromosome ranged from 123 (chromosome 9) to 315 (chromosome 4) with a mean value of 224.6, the distance between adjacent markers ranged from 0.6 (chromosome 10) to 1.3 cM (chromosome 9) with an average distance of only 0.98 cM. Conclusion: A high density sorghum genetic map was constructed in this study. The total length was 2158. 1 cM covering all 10 chromosomes with a total number of 2246 SLAF markers. The construction of this map can provide detailed information for accurate gene localization and cloning and application of marker-assisted breeding. [ABSTRACT FROM AUTHOR]

To study the influence of sowing rate, water and fertilizer (N, P and K) coupling on water use efficiency of fodder miilet grown in autumn fallow field, taking "Jigu 18" as the tested materal, a orhogonal rotation combination with five factor was designed in pot experment. Results showed that both water and phosphate fertilizer had important impacts on water use efficiency, in which water had the maximum impact, followed by phosphate fertilizer, and nitrogen ferilizer, potassium ferilizer and sowing rate a l had no obvious impact. Significant item of sowing rate, water and fertilizer coupling had the below sequence : potassium fertilizer + sowing rate > nitrogen fertilizer + phosphate fertilizer > water + phosphate ferilizer > water + sowing rate > water + potassium ferilizer, and other items had no obvious impact. Mathematical model was established: y = 44. 26 - 1. 311x1 - 2. 298x2 - 3. 682x3 - 6. 401x4 - 34. 540x5 + 0. 273x1x3 + 0. 118x1x4 + 0. 843x1x5 - 1 . 948x2x3 + 6. 631x4x5. The optimal scheme taking economic benefit as the examining index was cleared, that is, soil water content maintained 10%, and sowing rate of fodder miilet was 15 kg/hm². By the scheme, water use efficiency was 26.24g/kg, and hay yield was 13980.90 kg/hm², with economic benefit of 13830.90 yua/hm², which was 3063.73 yuan/hm² more than the optimized combination with the highest hay yield, with increase magnitude of 22.15%, and was 6215. 15 yuan/hm² more than the optimized combination with the highest water use efficiency, with increase manitude of 44.94% . The research could provide theoretic basis and technic! support for production practice of fodder miilet grown in autumn faUow field. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Science & Technology is the property of Hunan Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] The aim was to study the high-yield cultivation technique of fodder soybean(Glycine max (L.) Merr.) in autumn idle land. [Methods] Such five influencing factors as line spacing, planting density, nitrogen (N), phosphorus (P) and potassium (K) of fodder soybean seeding in autumn idle land were compared using orthogonal experiment method and LSD method of PASW 18 statistics software. [Results] The results showed that density, line spacing and K2O had important effects on biological yield of fodder soybean in autumn idle land. Moreover, the optimum proposal for high-yield matching cultivation technique of fodder soybean in autumn idle land was determined as follows: planting density was 75×104 plants/hm2; 300 kg/hm2 N, 112.5 kg/hm2 P2O5 and 375 kg/hm2 K2O were viewed as basic fertilizers; the seedling style was sowing in drill with the line spacing of 50 cm. In the proposal, fresh and hay grass yields were 6 661.67 and 2 723.64 kg/hm2, respectively, which increased by 24.17% and 27.63% respectively compared to the second fine combination. [Conclusions] The results provided a theoretical basis and technical support for the production of fodder soybean in autumn idle land. [ABSTRACT FROM AUTHOR]

China is rich in energy plant resources. In this article, 64 plant species are identified as potential energy plants in China. The energy plant species include 38 oilseed crops, 5 starch-producing crops, 3 sugar-producing crops and 18 species for lignocellulosic biomass. The species were evaluated on the basis of their production capacity and their resistance to salt, drought, and/or low temperature stress. Ten plant species have high production and/or stress resistance and can be potentially developed as the candidate energy plants. Of these, four species could be the primary energy plants in China: Barbados nut ( Jatropha curcas L.), Jerusalem artichoke ( Helianthus tuberosus L.), sweet sorghum ( Sorghum bicolor L.) and Chinese silvergrass ( Miscanthus sinensis Anderss.). We discuss the use of biotechnological techniques such as genome sequencing, molecular markers, and genetic transformation to improve energy plants. These techniques are being used to develop new cultivars and to analyze and manipulate genetic variation to improve attributes of energy plants in China. [ABSTRACT FROM AUTHOR]