A study to characterise the Crop Status Index (CSI) was performed on wheat crop grown under eight abiotic stress conditions categorised into four levels of stress intensity (No stress, single, double and triple stress). Twenty probable crop abiotic stress indicators were used to select minimum dataset (MDS) responsive of different intensities of abiotic stress conditions. Indices were determined by linear and nonlinear scoring, with weighted and additive methods of calculation. To determine the MDS principal component analysis (PCA) was applied on the total dataset of indicators that were sensitive to abiotic stress conditions. The objectives of this study are to identify suitable abiotic stress indicators, the best scoring technique (linear or nonlinear) and appropriate method (additive and weighted) to derive a CSI to characterise abiotic stress condition like moisture, temperature and nitrogen stress alone or in different (single, double or triple) combinations of theses stresses. Twenty Biophysical, Physiological and Biochemical stress indicators comprised the initial dataset, out of which Relative Water Content, Stomatal Conductance, Leaf Temperature, Chlorophyll, Root Length and Leaf Nitrogen were selected as MDS through PCA. The type of abiotic stress condition and stress intensity affected each indicator in different ways. CSI calculated by means of MDS and nonlinear weighted additive integration showed the best ability to distinguish different intensity of abiotic stress. In general the CSI values were lower under higher intensity of abiotic stress condition, and showed that abiotic stress effect was inclining towards a detrimental effect on crop status for wheat production under semi-arid condition. There was a clear indication that crop quality for wheat production was worsened by moisture and nitrogen stress under normal and high temperature stress conditions. The results revealed that increasing stress intensity might cause deterioration in crop status due to limitations in soil and environmental resources under future global warming scenarios. The indexing method used in this study offers a useful, time and cost efficient approach to quantify abiotic stress effects on crop status for wheat production in semi-arid condition.