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Soil organic carbon (SOC) and rainfall are generally positively related, whereas a negative relationship between soil inorganic carbon (SIC) and rainfall with some exception is observed. Land use pattern in black soil region (BSR) of the semi-arid tropical (SAT) India, consists of 80% under agriculture, followed by forest, horticulture, wasteland and permanent fallow. For sustainable agriculture on these soils, there is a concern about their low OC status, which warrants fresh initiatives to enhance their OC status by suitable management interventions. In the BSR region, cotton, soybean and cereal-based systems dominate but it is not yet clear as to which cropping system in the SAT black soils is most suitable for higher OC sequestration. Many short-term experiments on cotton or cereal-based systems clearly suggest that cotton or cereal-based cropping systems including leguminous crops perform better in terms of SOC sequestration whereas soybean–legume combination do not add any substantial amount of OC. In sub-humid bioclimatic zones (1053–1209 mm mean annual rainfall), soybean is grown successfully with wheat or fallowing, and SOC concentration is maintained at 0.75% in the 0.30 m soil layer under integrated nutrient management. In view of enhancement and maintenance of OC in many shortterm experiments conducted in various agro-climate zones of SAT, it is realized that OC accumulation in soils of the semi-arid ecosystem with suitable cropping and management practices could be substantial especially in cotton–pigeon pea rotation, and thus the discussed crop rotations in each major bio-climatic zone stand for wide acceptance by the SAT farmers.

Associated red and black soils are common in the Deccan plateau and the Indian peninsula. The red soils are formed due to the progressive landscape reduction process and black soils due to the aggradation processes; and they are often spatially associated maintaining their typical characteristics over the years. These soils are subject to changes due to age-long management practices and the other factors like climate change. To maintain soil quality, it is essential to monitor changes in soil properties preferably using benchmark (BM) soil sites. One such example lies at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) farm in Patancheru, India where red (Patancheru) and black (Kasireddipalli) soils co-exist in close association under almost similar topographical condition, which also represents very commonly occurring spatially associated soils. The database generated over the years for these two dominant soils that are under cultural practices for the last 2–3 decades, helps us understand the relative changes in properties over a time scale. To do this exercise, we revisited the BM spots as the data on the original characterization of these soils since the development of the farm, are available, for comparative evaluation. We also attempted to make prediction of future changes in properties for these two important and representative black and red soils of the ICRISAT farm in Patancheru, India.

Soil health diagnosis in nearly 100,000 farmers’ fields under ‘Bhoochetana’ initiative in Karnataka showed widespread soil degradation. Soil mapping-based fertilizer management was an effective entry-point intervention to take most farmers on-board to initiate the process of upgrading agriculture. Soils of the farmers’ fields showed low levels of micro- and secondary nutrients such as zinc (Zn) (55%), boron (B) (62%) and sulphur (S) (52%) in addition to that of phosphorus (P) (41%), potassium (K) (23%) and soil organic carbon (C) (52%). Soil mapping-based fertilizer management recorded significant productivity benefits that varied from 25% to 47% in cereals, 28% to 37% in pulses and 22% to 48% in oilseed crops. In terms of economics, a rupee spent on soil test-based fertility management brought returns of Rs 3 to Rs 15. Similarly, the participatory trials showed that the use of high yielding varieties of sorghum, pearl millet, finger millet, groundnut, soybean, castor, pigeonpea and chickpea enhanced productivity by 30% to 123%. The tangible benefits through soil mapping and variety based interventions have enhanced the risk-taking ability of farmers to invest in technologies based on use of soil testing and use of improved cultivars of crops. The adoption of simple knowledge-based technologies as entry point interventions along with policy reorientation to ensure knowledge sharing and availability of needed inputs at village level, enabled in a period of four years (2009–2013) to outreach more than 5 million families in Karnataka to transfer improved technologies in more than 7 million ha area. The study indicates that knowledge-based entry point interventions like soil mapping and improved varieties targeted at providing simple solutions are the best options for quick benefits and rapportbuilding with the majority farmers to initiate a collective action for technological upgradation of dry land agriculture.

The semi-arid tropical (SAT) regions are notably characterized by low rainfall and high temperatures, and hence low natural primary productivity and soil fertility. However, to adequately respond to the title of our article as to how fertile are SAT soils, there is a need to critically review the current literature on the fertility status of SAT soils. Little attention has been paid in the past to determining the fertility status of SAT soils supporting rainfed production systems despite the fact that the SAT soils are relatively fragile than their irrigated counterparts; and this is due to their widespread degradation and lack of investment in building up the fertility. However, as in the case of other agroecosystems, the soils in the SAT regions vary widely in various fertility parameters. For example, the results of survey of large numbers of farmers’ fields in the SAT regions of India, by the ICRISAT and its partners, showed that they vary widely in soil pH, salts (electrical conductivity, EC), organic C (an index of available N) and major (N and P), secondary (S) and micronutrients (B and Zn) although the soils were low in organic C with widespread deficiencies of these nutrients. From the results discussed in this article, it is concluded that in general, the soils in the SAT regions are low in fertility; however, they vary widely in various fertility parameters.

Soils in the semi-arid tropics (SAT) are subject to chemical degradation mostly due to climatic reasons which make the pedo-environment hostile to form calcium carbonate. This triggers an overall deterioration of soil properties affecting its physical and chemical parameters. Such soils require management interventions which may include chemical and other phytoremediation process. The present paper details this process of degradation in light of resilience of these soils of SAT.

Diffuse reflectance spectroscopy (DRS) operating in wavelength range of 350-2500 nm is emerging as a rapid and non-invasive approach for estimating soil nutrient content. The success of the DRS approach relies on the ability of the data mining algorithms to extract appropriate spectral features while accounting for non-linearity and complexity of the reflectance spectra. There is no comparative assessment of spectral algorithms for estimating nutrient content of Indian soils. We compare the performance of partialleast- squares regression (PLSR), support vector regression (SVR), discrete wavelet transformation (DWT) and their combinations (DWT-PLSR and DWT-SVR) to estimate soil nutrient content. The DRS models were generated for extractable phosphorus (P), potassium (K), sulphur (S), boron (B), zinc (Zn), iron (Fe) and aluminium (Al) content in Vertisols and Alfisols and were compared using residual prediction deviation (RPD) of validation dataset. The best DRS models yielded accurate predictions for P (RPD = 2.27), Fe (RPD = 2.91) in Vertisols and Fe (RPD = 2.43) in Alfisols, while B (RPD = 1.63), Zn (RPD = 1.49) in Vertisols and K (RPD = 1.89), Zn (RPD = 1.41) in Alfisols were predicted with moderate accuracy. The DWT-SVR outperformed all other approaches in case of P, K and Fe in Vertisols and P, K and Zn in Alfisols; whereas, the PLSR approach was better for B, Zn and Al in Vertisols and B, Fe and Al in Alfisols. The DWT-SVR approach yielded parsimonious DRS models with similar or better prediction accuracy than PLSR approach. Hence, the DWT-SVR may be considered as a suitable data mining approach for estimating soil nutrients in Alfisols and Vertisols of India.