利用从属函数分析和机器学习评估石榴栽培品种的耐盐性

IF 1.3 4区农林科学 Q3 AGRONOMY

Communications in Soil Science and Plant Analysis Pub Date : 2024-07-21 DOI:10.1080/00103624.2024.2380498

Shashi Pathania, Baljit Singh, Ajmer Singh Brar, Sukhpreet Singh, Amit Bajaj

引用次数: 0

摘要

机器学习在耐盐性评估研究中的应用还很有限。为弥补这一不足，旁遮普农业大学对六个石榴栽培品种进行了盆栽培养实验，结果表明，这些栽培品种的耐盐碱能力都很强。

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Evaluating Salinity Tolerance of Pomegranate Cultivars Using Subordinate Function Analysis and Machine Learning

The application of machine learning in salinity tolerance evaluation studies is limited. To address this gap, a pot culture experiment was conducted with six pomegranate cultivars at Punjab Agricul...

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来源期刊

Communications in Soil Science and Plant Analysis 农林科学-分析化学

CiteScore

3.30

自引率

5.60%

发文量

276

审稿时长

9.9 months

期刊介绍： International in coverage, Communications in Soil Science and Plant Analysis presents recent advances in plant and soil science, emphasizing on methods of analysis and interpretation of elemental content of soils and plants and plant nutrition. The Journal emphasizes agronomic and plantation crops with topics ranging from nutrition and methodology to precision agriculture, sustainable use of land and water resources, and increasing yield. Additional topics that are also covered in Communications in Soil Science and Plant Analysis : adverse growing conditions dealing with salinity and drought tolerance and their effects on crop yields soil chemistry; mineralogy; fertility and testing of soils; soil-crop nutrition; plant analysis; interpretation and correlation of soil tests and plant analyses; liming and fertilization of soils; and techniques for correcting deficiencies. Scientists and crop consultants around the world benefit from the research published in Communications in Soil Science and Plant Analysis . The research can be utilized to further educational research programs and may also be applied to field operations, which are continuously changing and expanding based upon the peer reviewed research conducted and published in the journal.