Anirban Nandy and Piyush Kumar Singh
Data envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production…
Abstract
Purpose
Data envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production, impreciseness and uncertainty in data are common. As a result, the data obtained from farmers vary. This impreciseness in crisp data can be represented in fuzzy sets. This paper aims to employ a combination of fuzzy data envelopment analysis (FDEA) approach to yield crisp DEA efficiency values by converting the fuzzy DEA model into a linear programming problem and machine learning algorithms for better evaluation and prediction of the variables affecting the farm efficiency.
Design/methodology/approach
DEA applications are focused on the use of a common two-step approach to find crucial factors that affect efficiency. It is important to identify impactful variables for minimizing production adversities. In this study, first, FDEA was applied for efficiency estimation and ranking of the paddy growers. Second, the support vector machine (SVM) and random forest (RF) were used for identifying the key leading factors in efficiency prediction.
Findings
The proposed research was conducted with 450 paddy growers. In comparison to the general DEA approach, the FDEA model evaluates fuzzy DEA efficiency giving the user the flexibility to measure the performance at different possibility levels.
Originality/value
The use of machine learning applications introduces advanced strategies and important factors influencing agricultural production, which may help future research in farms' performance.
Details
Keywords
Saroni Biswas, Anirban Biswas, Arabinda Das and Saon Banerjee
This study aims to assess the biodiversity of the study area and estimate the carbon stock of two dry deciduous forest ranges of Banka Forest Division, Bihar, India.
Abstract
Purpose
This study aims to assess the biodiversity of the study area and estimate the carbon stock of two dry deciduous forest ranges of Banka Forest Division, Bihar, India.
Design/methodology/approach
The phytosociological analysis was performed and C stock estimation based on volume determination through nondestructive methods was done.
Findings
Phytosociological analysis found total 18,888 [14,893 < 10 cm (diameter at breast height) dbh] and 2,855 (1,783 < 10 cm dbh) individuals at Banka and Bounsi range with basal area of 181,035.00 cm2 and 32,743.76 cm2, respectively. Importance value index was highest for Shorea robusta in both the ranges. Species diversity index and dominance index, 1.89 and 1.017 at Banka and 1.99 and 5.600 at Bounsi indicated the prevalence of biotic pressure. Decreased dbh and tree height resulted in a lowered growing stock volume as 59,140.40 cm3 ha−1 (Banka) and 71,306.37 cm3 ha−1 (Bounsi). Total C stock at Banka and Bounsi range was 51.8 t ha-1 and 12.56 t ha−1, respectively where the highest C stock is recorded for Shorea robusta in both the ranges (9.8 t ha−1 and 2.54 t ha-1, respectively). A positive correlation between volume, total biomass and basal area of tree species with C stock was observed. R2 value for Banka range was 0.9269 (volume-C stock), 1 (total biomass-C stock) and 0.647 (basal area-C stock). Strong positive correlation was also established at Bounsi range with R2 value of 1. Considering the total forest area enumerated, C sequestration potential was about 194.25 t CO2 (Banka) and 45.9 t CO2 (Bounsi). The valuation of C stock was therefore US$2,525.25 (Banka) and US$596.70 (Bounsi).
Practical implications
The research found the potentiality of the study area to sequester carbon. However, for future, the degraded areas would require intervention of management strategies for restoration of degraded lands and protection of planted trees to increase the carbon sequestration potential of the area.
Originality/value
Present study is the first attempt to assess the phytosociology and estimate the regulatory services of forest with respect to biomass and carbon stock estimation for the Banka forest division of Bihar.