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Climate change and its impact on agriculture productivity vary among crops and regions. The southeastern United States (SE-US) is agro-ecologically diversified, economically dependent on agriculture, and mostly overlooked by agroclimatic researchers. The objective of this study was to compute the effect of climatic variables; daily maximum temperature (Tmax), daily minimum temperature (Tmin), and rainfall on the yield of major cereal crops i.e., corn (Zea mays L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) in SE-US. A fixed-effect model (panel data approach) was used by applying the production function on panel data from 1980 to 2020 from 11 SE-US states. An asymmetrical warming pattern was observed, where nocturnal warming was 105.90%, 106.30%, and 32.14%, higher than the diurnal warming during corn, rice, and wheat growing seasons, respectively. Additionally, a shift in rainfall was noticed ranging from 19.2 to 37.2 mm over different growing seasons. Rainfall significantly reduced wheat yield, while, it had no effect on corn and rice yields. The Tmax and Tmin had no significant effect on wheat yield. A 1 °C rise in Tmax significantly decreased corn (− 34%) and rice (− 8.30%) yield which was offset by a 1 °C increase in Tmin increasing corn (47%) and rice (22.40%) yield. Conclusively, overall temperature change of 1 °C in the SE-US significantly improved corn yield by 13%, rice yield by 14.10%, and had no effect on wheat yield.

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The present study was undertaken to measure and compare the relative efficiencies of selected Food Processing Companies in India. The relationship between firm performance and selected variables in food processing sector has also been studied. Set considered for analysis consisted of 20 food processing companies with period of analysis covering 8 years from 2005 to 2012. Efficiency status of the firm was regressed upon using capital to sales ratio, labor cost to sales ratio, raw material cost to sales ratio and energy cost to sales ratio as explanatory variable. Results indicate that except for labor cost to sales ratio all other variables were having significant negative impact on the efficiency of food processing companies.

Logistics plays an important role in determining the profits for a business enterprise through a dual influence on revenues and costs. Logistics are considered critical in the growth and performance of the food processing sector. The present study was undertaken to examine the relative performance of food processing units in India on the basis of logistics cost. Data Envelopment Analysis (DEA) was used to study the relative performance and the set considered for analysis consisted of 32 food processing units with the period of analysis covering 5 years from 2007-2011. Results indicate that no food processing unit was efficient throughout the period of analysis. Logistic regression results indicate that with a unit increase in logistics cost likelihood of the firm being efficient decreased 0.642 times. The results of the study underline the criticality of logistics management in the context of the food processing sector in India. For improving firm efficiency, it is imperative for Indian food processing companies to ensure efficiency in logistics operations.

Recognizing the crop and region-specific irreversible effects of climate change on agriculture is unavoidable. The Southeastern United States region (SE-US) contributes significantly to the United States (US) economy through its diverse agricultural productivity. Climatically, this region is more vulnerable than the rest of the country. This study was designed to quantify the effect of changing climate, i.e., daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation, on oats (Avena sativa L.) and sorghum (Sorghum bicolor L. Moench) in SE-US. The panel data approach with a fixed effects model was applied by creating a production function on a panel dataset (1980–2020) of climate and yield variables. The required diagnostic tests were used to statistically confirm that the dataset was free of multi-collinearity, stationarity, and auto-correlation issues. The results revealed asymmetric warmings (Tmin increase > Tmax increase) over the region. Tmax and Tmin significantly increased during the oats growing season (OGS) and sorghum growing season (SGS). Precipitation increased during OGS and decreased during SGS. The annual average values of Tmax, Tmin, and Tavg (daily average temperature) have shifted by 1.08°C (0.027°C/year), 1.32°C (0.033°C/year), and 1.20°C (0.030°C/year) in OGS and by 0.92°C (0.023°C/year), 1.32°C (0.033°C/year), and 1.12°C (0.028°C/year) in SGS. However, precipitation had shifted by 23.2 mm (0.58 mm/year) in OGS and shifted (decreased) by -5.2 mm (-0.13 mm/year) in SGS. Precipitation had a non-significant effect on oats and sorghum yields. With every 1°C increase in Tmin and Tmax, oats yield was reduced by (-5%) and (-4%), respectively, whereas sorghum yield was increased by (+ 13%) and decreased by (-7%), respectively. Taken together, a 1°C net rise in overall temperature reduced oats yield (-9%) while increased sorghum yield (+ 6%).

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