Sixteen cotton cultivars widely planted in China were sowed under five different drought concentrations (0, 2.5, 5, 7.5, and 10%) using PEG₆₀₀₀ to screen the indices of drought resistance identification and explore the drought resistance of different cotton cultivars.  Eighteen physiological indices including root, stem, and leaf water contents (RWC, SWC, and LWC), net photosynthetic rate (P_n), the maximum photochemical quantum yield (F_v/F_m), the actual photochemical quantum yield (Φ_PSII), non-photochemical quenching coefficient (NPQ), leaf water potential (LWP), osmotic potential (Ψs), leaf relative conductivity (REC), leaf proline content (Pro), leaf and root soluble protein contents (LSPC and RSPC), leaf and root malondialdehyde (MDA) contents (LMDA and RMDA), root superoxide dismutase, peroxidase, and catalase activities (RSOD, RPOD, and RCAT) were measured.  Results indicated the 18 physiological indices can be converted into five or six independent comprehensive indices by principal component analysis, and nine typical indices (F_v/F_m, SWC, LWP, Pro, LMDA, RSPC, RMDA, RSOD, and RCAT) screened out by a stepwise regression method could be utilized to evaluate the drought resistance.  Moreover, the 16 cotton cultivars were divided into four types: drought sensitive, drought weak sensitive, moderate drought resistant, and drought resistant types.  The resistance ability of two selected cotton cultivars (drought resistant cultivar, Dexiamian 1; drought sensitive cultivar, Yuzaomian 9110) with contrasting drought sensitivities were further verified by pot experiment.  Results showed that the responses of final cotton biomass, yield, and yield composition to drought were significantly different between the two cultivars.  In conclusion, drought resistant cultivar Dexiamian 1 and drought sensitive cultivar Yuzaomian 9110 were screened through hydroponics experiment, which can be used as ideal experimental materials to study the mechanism of different cotton cultivars with contrasting drought sensitivities in response to drought stress.

 

Over the past five decades, increased pressure caused by the rapidly growing population has resulted in a reclamation of agricultural and urban buffer zones along China’s coastline.  However, information about the spatio–temporal variation of soil salinity in these reclaimed regions is limited.  As such, obtaining this information is crucial for mapping the variation in saline areas and to identify suitable salinity management strategies.  In this study, we employed EM38 data to conduct digital soil mapping of spatio–temporal variation and map these variations of different site-specific zones.  The results indicated that the distribution of soil salinity was heterogeneous in the middle of, and that the leaching of salts was significant at the edges of, the study field.  Afterwards, fuzzy-k means algorithm was used to divide the site-specific management zones within the time series apparent soil electrical conductivity (ECa) data and the spatial correlations of variation.  We concluded that two management zones are optimal to guide precision management.  Zone A had an average salinity level of about 165 mS m^–1, in which salt-tolerant crops, such as cotton and barley can grow normally, while crops such as soybean and cowpeas may be planted using leaching and increasing the mulching film methods to reduce the accumulation of salt in surface soil.  In Zone B, there was a low salinity level with a mean of 89 mS m^–1 for ECa, which allows for rice, wheat, and a wide range of vegetables to be grown normally.  In such situations, measures such as an optimized combination of irrigation and drainage, as well as soil amendment can be taken to adjust and control the salt content.  Particularly, flattening the land with a large-scale machine was used to improve the ability of micro-topography to influence salt migration; rice and other dry, land crops were planted in rotation in combination with utilizing salt-leaching multiple times to speed up desalinization.