Thirty genotypes of runner-type peanut seeds were used in this study (Table 1). These genotypes were derived from nine crosses with considerable variations of oleic acid content. Seeds were provided by the peanut breeding program at USDA-ARS National Peanut Research Laboratory and were harvested in fall 2007 either in Headland, AL or Brownfield, TX. High oleic content lines among 30 genotypes were contributed by five high oleic donor parents: ‘F435’, ‘Sunoleic 95R’, ‘AT108-HO’, ‘AT-50-1114’, and ‘GK-7-HO’ (Table 1). All seeds were dried to a safe moisture level of ≤ 10.5%, wet basis (USDA, 2000). Petroleum ether (Fisher Chemicals, USA) was used for oil extraction. Cyclohexane, acetone and sodium methoxide (Sigma-Aldrich, St. Louis, MO, USA) were used to prepare oil samples for fatty acid analysis using gas chromatography, to develop fatty acid reference values ( Sundaram et al., 2010a).

A Soxtec ³ semi automatic method was used to extract the total oil from peanut samples with petroleum ether. Well-developed and intact kernels were selected from the different cultivars of the peanuts for the measurements. Kernel samples were frozen before grinding to avoid loss of any oil while grinding. About one gram of homogeneously ground fine peanut meal was weighed and placed in a cellulose thimble. The thimble was covered using a thin layer of defatted cotton, to avoid any spilling of petroleum ether. The thimble was fixed on to a metal ring through which the thimble could be attached to the Soxtec extractor. Metal cups were placed below each of the thimble to collect the extracted oil from a sample. Weights of the empty cups were recorded and the cups were placed on the metal plate. About 90 ml of petroleum ether was added to each thimble from the top. Thimbles were heated to boil the petroleum ether. While boiling, the petroleum ether extracted oil contained in the peanut meal. Temperature was maintained at 135°C ± 2°C during boiling, for 45 minutes. By end of the boiling time, petroleum ether and oil mixture was collected in the metal cups placed below the thimbles. Heating the collection cups was continued for another 45 minutes at 135°C ± 2°C to evaporate the petroleum ether from the mixture. The cups were cooled for 15 minutes. During the cooling process, evaporated petroleum ether that had condensed was collected separately. The collecting cups were removed and kept in a hot-air oven at 40°C for 30 minutes to drive out any traces of petroleum ether. From the weights of, empty collecting cups, cups with oil, and initial ground peanut kernel meal, the total oil percentage was calculated. The measurements were done in triplicate for each cultivar ( Sundaram et al., 2010a).

Fatty acids present in the peanut samples were analyzed using Gas Chromatography (GC) (Agilent Technologies, 6890N Network GC). Oils extracted from each peanut group, using the method described above, were used for fatty acid analysis. About 10–12 mg of the extracted peanut oil was reacted with 0.2 ml of sodium methoxide to convert the fatty acids into corresponding esters. To complete this process, the oil and sodium methoxide mixture was heated to 50°C, and thoroughly mixed using a sonicator until it was derivatized completely. About 0.5 ml of cyclohexane was then added to the mixture to recover the derivatized esters and the whole mixture was sonicated for about 10–15 minutes and allowed to undergo phase separation. From the upper phase, 10–20 µl was withdrawn and diluted using one ml of acetone. This mixture was taken in a glass vial and analyzed using a GC fitted with a SP 2380 fatty acid column. The oven temperature in GC was maintained at 185°C. Hydrogen, air, and helium gas flow rates were 40, 450 and 0.6 ml/minute respectively. One µl of the sample was injected for each measurement. Total run time was 20 minutes. Within 20 minutes, esters of all major fatty acids namely oleic, linoleic and palmitic acids were separated and well-identified. Before running the oil samples, a fatty acid methyl ester (FAME) standards were run by diluting FAME in acetone. Based on the FAME peak references peanut fatty acid peaks were identified.

The peanut seed samples were separated into calibration and validation groups. NIRS measurements were made using a scanning monochromator (Model 6500, FOSS NIRSystems, Silver Springs, MD, USA). Spectral data were collected using Vision software (Version 1.0, FOSS NIRSystems, Silver Springs, MD, USA). Each replicate sample consisted of 100–200 g of peanut seeds depending on the amount required to adequately fill the sample holder. The room temperature during the measurements varied from 21°C to 23°C. NIR light passed through the bottom of the sample holder and was incident on the in-shell peanuts. The transmitted and reflected energy spectrum over the wavelengths of 400 nm to 2500 nm that carried absorption information of the samples was collected. This spectral data was collected for 30 replicates of each peanut cultivar.

NIRS data were analyzed using multivariate data analysis software (Unscrambler Version 9.7 CAMO ASA, USA). Reflectance spectra between 400–2500 nm with 0.5 nm intervals were taken as independent variables. Fatty acid concentration was the dependent variable in the analysis. Using the spectral data from the calibration dataset, partial least square (PLS) regression analysis was conducted to develop an empirical equation to estimate the concentrations of oleic, linoleic and palmitic acids. Before analysis, raw data often needs mathematical pretreatments to remove any defects in the spectra. Before applying the PLS analysis, absorption spectral data were converted in to reflectance spectral data. The derivatives of the absorption and reflection spectral data with respect to wavelength were computed. The derivative computation was used to remove any baseline shifting that may have occurred and to avoid overlapping of peaks. The fatty acids constitute a small fraction (less than 5%) of the mass index of total oil and moisture contents in the samples, and their spectral characteristics could be easily overshadowed by the total oil and moisture contents. By applying the derivative treatment, the modified wavelength spectrum showed more details by diminishing the influence of the lower frequencies, which hides the clarity of the spectral signatures and enhances the higher frequencies to show the spectral signature of fatty acids clearly. However, the derivative treatment was limited to second order because at higher orders excessive smoothing may take place that would diminish the contributions of the characteristic peaks.