Effects of arsenic-contaminated irrigation water on growth, yield, and nutrient concentration in rice

A study was undertaken to determine the effects of different concentrations of arsenic (As) in irrigation water on Boro (dry-season) rice (Oryza sativa) and their residual effects on the following Aman (wet-season) rice. There were six treatments, with 0, 0.1, 0.25, 0.5, 1, and 2 mg As L-1 applied as disodium hydrogen arsenate. All the growth and yield parameters of Boro rice responded positively at lower concentrations of up to 0.25 mg As L-1 in irrigation water but decreased sharply at concentrations more than 0.5 mg As L-1. Arsenic concentrations in grain and straw of Boro rice increased significantly with increasing concentration of As in irrigation water. The grain As concentration was in the range of 0.25 to 0.97 μg g-1 and its concentration in rice straw varied from 2.4 to 9.6 μg g-1 over the treatments. Residual As from previous Boro rice showed a very similar pattern in the following Aman rice, although As concentration in Aman rice grain and straw over the treatments was almost half of the As levels in Boro rice grain. Arsenic concentrations in both grain and straw of Boro and Aman rice were found to correlate with iron and be antagonistic with phosphorus. Copyright © Taylor & Francis Group, LLC.

Latent vs. Observed Variables: Analysis of Irrigation Water Efficiency Using SEM and SUR

In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equation modeling (SEM), in the latter by seemingly unrelated regression (SUR). We compare estimation results of the two approaches based on a dataset on single factor irrigation water use efficiency obtained from a survey of 360 farmers in the Guanzhong Plain, China. The main methodological findings are that SEM allows identification of the most important dimension of irrigation water efficiency (technical efficiency) via comparison of their factor scores and reliability. Moreover, it reduces multicollinearity and attenuation bias. It thus is preferable to SUR. The SEM estimates show that perception of water scarcity is the most important positive determinant of both types of efficiency, followed by irrigation infrastructure, income and water price. Furthermore, there is a strong negative reverse effect from efficiency on perception.

A decision support system for managing irrigation in agriculture

In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis of both soil measurements and climatic variables gathered by several autonomous nodes deployed in field. This enables a closed loop control scheme to adapt the decision support system to local perturbations and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in the South-East of Spain. Performance is tested against decisions taken by a human expert.

Adoption of farm-based irrigation water-saving techniques in the Guanzhong Plain, China

This article analyses adoption of farm-based irrigation water saving techniques, based on a cross-sectional data set of 357 farmers in the Guanzhong Plain, China. Approximately 83% of the farmers use at least one farm-based water-saving technique. However, the traditional, inefficient techniques border and furrow irrigation are still prevalent whereas the use of advanced, more efficient techniques is still rather rare. We develop and estimate an adoption model consisting of two stages: awareness of water scarcity and intensity of adoption. We find that awareness of water scarcity and financial status enhance adoption of more advanced techniques whereas access to better community-based irrigation infrastructure discourages it. We furthermore find both community-based irrigation infrastructure and farm-based irrigation water-saving techniques have mitigating effects on production risk. From the results it follows that adoption can be stimulated via financial support and via extension aimed at enhancing awareness of water scarcity.