A Cluster Analysis on the Energy Use Indicators and Carbon Footprint of Irrigated Wheat Cropping Systems

Abstract

The objective of this study is to analyze the energy use efficiency and carbon footprint of irrigated wheat systems in different Iranian provinces. The authors resort to the k-means clustering technique to fulfil the said objective. The empirical results reveal that the average total input energy (59.5 GJ ha−1) is higher than the average energy output (45.82 GJ ha−1) from wheat production, resulting in an average energy efficiency of 0.77, thus rendering the production of irrigated wheat in Iran energy-inefficient on average. Among the thirty wheat-producing Iranian provinces considered in this analysis, only six—East Azerbaijan, Golestan, Ardabil, Kohgiluyeh and Boyer-Ahmad, Alborz, and West Azerbaijan—register an energy use efficiency greater than unity. The average total of greenhouse gas (GHG) emissions from irrigated wheat is 2243.54 kg CO2-eq ha−1 (with electricity and diesel fuel contributing 52.4% and 29.4%, respectively). The authors categorize the clusters into five groups ranging from sustainable to unsustainable. Five of the six provinces referred to earlier fall into the ‘sustainable’ category, with Bushehr being the sixth. The wheat production units in the ‘sustainable’ category can serve as a benchmark for the clusters in the other categories, which can move up the ladder of sustainability. The authors also recommend measures that policymakers can undertake to ensure the sustainable development of wheat production in Iran, fulfilling the social imperative of food self-sufficiency while truncating the environmental footprint and ensuring economic feasibility.

Implementation of K-means Clustering Algorithm for the Indonesian Stock Exchange

“…Researchers use advanced data preprocessing techniques to handle missing values, normalize data, and select relevant features for clustering [5]. This ensures that the input data fed into the K-means algorithm is clean, standardized, and conducive to meaningful clustering [6]. To maximize the effectiveness of the K-means algorithm, this research explores various parameter settings and optimization strategies [7].…”

Eco-Efficiency Analysis to Improve Environmental Performance of Wheat Production

“…Irrigated fields span 6.9 million ha, and dryland fields encompass 5.1 million ha of cropping area. These are, respectively, 38% and 62% of the total arable Agriculture 2022, 12, 1031 2 of 16 land in the country [4]. The mechanisation and technology level for wheat cultivation is high in Iran, and an efficiency of 84% has been reported by Lak [5].…”