ABSTRACT (1) Soil alkalinization and salinization represent a growing global challenge. Maize ( Zea mays L.), with its relatively low tolerance to salt and alkali, is increasingly vulnerable to saline‐alkali stress. Identifying maize genotypes that can withstand salinity and alkalinity is crucial to broaden the base of salt‐alkali‐tolerant maize germplasm. (2) In this study, we screened 65 maize germplasm resources for alkali stress using a 60 mM NaHCO 3 solution. We measured fifteen morphological and physiological indices, including seedling height, stem thickness, and leaf area. Various analytical methods—correlation analysis, principal component analysis, subordinate function analysis, cluster analysis, stepwise discriminant analysis, and ridge regression analysis—were used to assess the seedling alkali tolerance of these maize germplasm resources. The physiological indices of six tested maize varieties were analyzed in greater detail. (3) The findings revealed complex correlations among traits, particularly strong negative associations between conductivity and root traits such as length, volume, surface area, diameter, and number of branches. The 15 evaluation indices were reduced to 7 principal components, explaining 77.89% of the variance. By applying affiliation functions and weights, we derived a comprehensive evaluation of maize seedling alkali tolerance. Notably, three germplasms—Liang Yu 99, Bi Xiang 638, and Gan Xin 2818—demonstrated significant comprehensive seedling alkali tolerance. Cluster analysis grouped the 65 maize germplasm resources into four distinct categories (I, II, III, and IV). The results of the cluster analysis were confirmed by multiclass stepwise discriminant analysis, which achieved a correct classification rate of 92.3% for 60 maize genotypes regarding alkalinity tolerance. Using principal component and ridge regression analyses, we formulated a regression equation for alkali tolerance: D ‐value = −1.369 + 0.002 * relative root volume + 0.003 * relative number of root forks + 0.006 * relative chlorophyll SPAD + 0.005 * relative stem thickness + 0.005 * relative plant height + 0.001 * relative conductivity + 0.002 * relative dry weight of underground parts. Under sodium bicarbonate stress, morphological indices and germination rates were significantly reduced, germination was inhibited, photosynthetic pigment levels in maize leaves decreased to varying degrees, and the activities of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT) significantly increased. Alkali stress markedly enhanced the antioxidant enzyme activities in maize varieties, with alkali‐resistant varieties exhibiting a greater increase in antioxidant enzyme activities than alkali‐sensitive varieties under such stress. (4) By screening for alkali tolerance in maize seedlings, the identified alkali‐tolerant genotypes can be further utilized as suitable donor parents, thereby enhancing the use of alkali‐tolerant germplasm resources and providing theoretical guidance for maize cultivation in saline‐alkaline environments.
Soil salinization is a widely recognized global environmental concern that has a significant impact on the sustainable development of agriculture at a global scale. Maize, a major crop that contributes to the global agricultural economy, is particularly vulnerable to the adverse effects of salt stress, which can hinder its growth and development from germination to the seedling stage. This study aimed to screen highly salt-tolerant maize varieties by using four NaCl concentrations of 0, 60, 120, and 180 mMol/L. Various agronomic traits and physiological and biochemical indices associated with salt tolerance were measured, and salt tolerance was evaluated using principal component analysis, membership function method, and GGE biplot analysis. A total of 41 local maize varieties were assessed based on their D values. The results show that stem thickness, germ length, radicle length, leaf area, germination rate, germination index, salt tolerance index, and seed vigor all decreased as salt concentration increased, while electrical conductivity and salt injury index increased with the concentration of saline solution. Under the stress of 120 mMol/L and 180 mMol/L NaCl, changes in antioxidant enzymes occurred, reflecting the physiological response mechanisms of maize under salt stress. Principal component analysis identified six major components including germination vigor, peroxidase (POD), plant height, embryo length, SPAD chlorophyll and proline (PRO) factors. After calculating the comprehensive index (D value) of each variety’s performance in different environments using principal component analysis and the membership function method, a GGE biplot analysis was conducted to identify maize varieties with good salt tolerance stability: Qun Ce 888, You Qi 909, Ping An 1523, Xin Nong 008, Xinyu 66, and Hong Xin 990, as well as varieties with poor salt tolerance: Feng Tian 14, Xi Meng 668, Ji Xing 218, Gan Xin 2818, Hu Xin 712, and Heng Yu 369. Furthermore, it was determined that a 120 mMol/L NaCl concentration was suitable for screening maize varieties during germination and seedling stages. This study further confirmed the reliability of GGE biplot analysis in germplasm selection, expanded the genetic resources of salt-tolerant maize, and provided theoretical references and germplasm utilization for the introduction of maize in saline-alkali areas. These research findings contribute to a better understanding of maize salt tolerance and promote its cultivation in challenging environments.
The design of LED planting system adopts artificial lighting to realize the changes of the light intensity of simulating sunlight in plant lighting, which is used to analyze the influence of light intensity on plant growth form, and design planting experiments. The results show that the system can improve the product quality of experimental crops, and the optical control strategy is feasible.
With the global increase in energy prices and the urgent need to reduce CO 2 emissions to the atmosphere, high energy usage is the main problem the greenhouse industry facing.Optimized control of supplemental lighting intensity and quality help to improve productivity and energy efficiency of greenhouse.In this paper,LED light source module is developed according to the design of light distribution of RRGB chip based on plants need for uniform lighting.Adaptive LED supplementary lighting system realize collection, storage and call of environmental data, and adaptive regulation of red, green, and blue light output based on combination of upper computer LabVIEW and controller STM32.PC based on LabVIEW monitor environmental parameters,and call or choose PPFD setting value of red, green, blue three bands of light based on expert database.The controller communicating with LabVIEW wirelessly through WiFi module, conducts real-time detection and adaptive regulation on photosynthetic photon flux density (PPFD) of red, green and blue bands according to PPFD setting value.This intelligent supplemental lighting system meets the requirement of plants for lighting environment and greatly saving energies through adaptive adjustment of PPFD of red, green and blue bands in environment according to the setting based on different supplemental lighting demands of different plants or the same plant in different growth stages for PPFD and light quality ratio.
In the period 2022–2023, an analysis of fourteen phenotypic traits was conducted across 192 maize accessions in the Aral region of Xinjiang. The Shannon–Wiener diversity index was employed to quantify the phenotypic diversity among the accessions. Subsequently, a comprehensive evaluation of the index was performed utilizing correlation analysis, principal component analysis (PCA) and cluster analysis. The results highlighted significant findings: (1) A pronounced diversity was evident across the 192 maize accessions, accompanied by complex interrelationships among the traits. (2) The 14 phenotypic traits were transformed into 3 independent indicators through principal component analysis: spike factor, leaf width factor, and number of spikes per plant. (3) The 192 materials were divided into three groups using cluster analysis. The phenotypes in Group III exhibited the best performance, followed by those in Group I, and finally Group II. The selection of the three groups can vary depending on the breeding objectives. This study analysed the diversity of phenotypic traits in maize germplasm resources. Maize germplasm was categorised based on similar phenotypes. These findings provide theoretical insights for the study of maize accessions under analogous climatic conditions in Alar City, which lay the groundwork for the efficient utilization of existing germplasm as well as the development and selection of new varieties.
To better understand the growth adaptability of various maize varieties to the climate of the Alar region in Southern Xinjiang Province, an experiment was conducted using seven distinct maize varieties as test materials. A one-way randomized block design was applied to both experimental groups. In 2021 and 2022, a total of 19 indicators were observed for comparative analysis, including antioxidant enzyme activities and agronomic traits. Principal component analysis and cluster analysis were used to evaluate the adaptability of the maize varieties. The findings revealed that: (1) All seven maize varieties exhibited robust growth, with notable differences in their respective trait profiles. Specifically, the yield traits of Jin’ai 588 and Denghai 3672 showed relatively consistent performance over the two-year period. (2) Five principal components (100-kernel weight, bald tip length, catalase (CAT), number of leaves, and angle of leaf pinch at the ear) were extracted from the 19 traits via principal component analysis, with a cumulative contribution rate of 84.689%. This represented the majority of the information regarding the seven maize varieties. After calculating the comprehensive index F value, the results indicated that Xinyu 66 and Denghai 3672 had high composite scores, suggesting high production potential and suitability for cultivation in this region. Conversely, Xinyu 24 showed the lowest composite score, indicating that it is not suitable for planting in this area. (3) Ultimately, the seven maize varieties were categorized into three groups through cluster analysis; this is the same as the result of principal component analysis. This classification provides a reference for the promotion and utilization of different varieties in the southern border region and aims to optimize the comprehensive trait selection of the varieties studied.
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