Precision Farming at the Nexus of Agricultural Production and the Environment

Abstract

Precision farming enables agricultural management decisions to be tailored spatially and temporally. Site-specific sensing, sampling, and managing allow farmers to treat a field as a heterogeneous entity. Through targeted use of inputs, precision farming reduces waste, thereby cutting both private variable costs and the environmental costs such as those of agrichemical residuals. At present, large farms in developed countries are the main adopters of precision farming. But its potential environmental benefits can justify greater public and private sector incentives to encourage adoption, including in small-scale farming systems in developing countries. Technological developments and big data advances continue to make precision farming tools more connected, accurate, efficient, and widely applicable. Improvements in the technical infrastructure and the legal framework can expand access to precision farming and thereby its overall societal benefits.

Exploring Options for Improving Potato Productivity through Reducing Crop Yield Gap in Loess Plateau of China Based on Grey Correlation Analysis

“…The research scales of crop yield gap are divided into global scale, regional scale and field scale [8]. Previous studies on potato yield potential and the factors affecting yield difference have mainly explored these issues with respect to supplying water and fertilizer and agricultural measures [9][10][11]. Zhang et al conducted the coupling effect of water and fertilizer on potato plants in the Loess Plateau and obtained the average yield of 53,628 kg/ha [12].…”

Precision Agriculture for Smallholder Nitrogen Management

“…8 Precision agriculture (PA) has the potential to play a key role in the implementation of Climate Smart Agriculture by aiding farmers in tailoring their N management (in addition to other key inputs, such as water) to site-specific conditions. 9 As a whole, PA is a management strategy that gathers, processes, and analyzes site-specific temporal and spatial field data for management decision support. In particular, PA is being increasingly leveraged in industrial systems to mitigate seasonal variability and improve resource-use efficiency, productivity, and quality and the profitability of agricultural production.…”

“…The former include techniques such as remote sensing, GPS mapping, soil sampling, sensors, and robotics-all of which monitor and sample across various scales to provide farmers with data on variables ranging from N nutri-tion status and plant biomass to soil moisture. 9 The information generated from these tools can then be used to inform management techniques such as variable-rate technologies, which can adapt to the heterogeneities of a farming system and thus enable more site-specific management. For example, developing sitespecific management zones for N on the basis of yield history, aerial photographs of soil color, soil sampling, topography, and farmer experiences has been shown to increase yields significantly without a concomitant increase in the rates of N application.…”

“…11 Adoption in smallholder systems is extremely low because of the high capital requirements, paucity of extension services and information dissemination, and the economies of scale required for most PA approaches to be cost effective. 9 In short, PA has been targeted toward and mostly adopted by systems that are already highly mechanized and resource efficient.…”

“…A Nigerian company, Hello Tractor, connects farmers with tractor services via apps and text messaging. 9 And Digital Green produces locally tailored videos, data platforms, and training courseware in India and Ethiopia to connect farmers with extension experts. 16 Barriers to Implementation Despite the potential benefits of PA for improved N management, there are several barriers to implementation.…”