Abstract
In recent years, agricultural growth in China has accelerated remarkably, but most of this growth has been driven by increased yield per unit area rather than by expansion of the cultivated area. Looking towards 2030, to meet the demand for grain and to feed a growing population on the available arable land, it is suggested that annual crop production should be increased to around 580 Mt and that yield should increase by at least 2% annually. Crop production will become more difficult with climate change, resource scarcity (e.g. land, water, energy, and nutrients) and environmental degradation (e.g. declining soil quality, increased greenhouse gas emissions, and surface water eutrophication). To pursue the fastest and most practical route to improved yield, the near-term strategy is application and extension of existing agricultural technologies. This would lead to substantial improvement in crop and soil management practices, which are currently suboptimal.
Two pivotal components are required if we are to follow new trajectories. First, the disciplines of soil management and agronomy need to be given increased emphasis in research and teaching, as part of a grand food security challenge. Second, continued genetic improvement in crop varieties will be vital. However, our view is that the biggest gains from improved technology will come most immediately from combinations of improved crops and improved agronomical practices. The objectives of this paper are to summarize the historical trend of crop production in China and to examine the main constraints to the further increase of crop productivity. The paper provides a perspective on the challenge faced by science and technology in agriculture which must be met both in terms of increased crop productivity but also in increased resource use efficiency and the protection of environmental quality.
INTRODUCTION
I
n terms of area under agricultural land use and numbers of people sustaining their livelihoods from farming, the vast majority of
smallholder farmers are found in tropical developing countries
,often characterised by unreliable rainfall, recurrent floods, droughts and dry spells
(Rockström, 2000)
. The small–holder sector as a whole is responsible for 80% of agricultural production in
developing countries,indicating its
key role in subsistence food supply and livelihood security (Rockstöm, 2000).
Per capita food availability in Sub–Saharan Africa (SSA) has declined over time, and the region suffers from the widespread food insecurity
(Beintema and Stads, 2006)
. In Kenya, several mechanisms have been put in place to ensure food self sufficiency
(Heidhues, 2004). However, these efforts have been hampered bys oil fertility related factors, low water availability caused by low and/or erratic rainfall,low soil water holding capacity, poor/lack of soil
moisture conservation measures, excess runoff
prolonged dry spells,
recurrent droughts and erratic rainfall occasioned by climate variability
.
1.1. Background to the Study
A host of management practices may be used to improve precipitation capture, reduce runoff and evaporation, and improve agricultural productivity (Evett and Tolk, 2009).
For example, mulch cover
reduces surface runoff and holds rainwater on the soil surface thereby giving it more time to infiltrate into the soil (Mupangwaet al., 2007). Minimum tillage has the potential to reduce structural degradation of soil, improved infil
tration of rainwater into the soil potentially increases water availability to plants, reduces surface runoff and improves groundwater recharge and has the potential to reduce soil erosion (Towery, 1998; Karunatilake and van Es,
These management practices that increase infiltration and soil water holding capacity, and/or improve the ability of roots to extract more water from the soil profile could all
potentially have positive impacts on agricultural water productivity. They also have a potential of
mitigating rainfall fluctuations, and thereby increasing overall yield levels,
stabilise yields over time and encourage the otherwise risk averse farmers to invest more in agricultur
e. The most common way to test such options is through field experimentation/trials. Besides being expensive and time consuming, field experimentation is usually faced with many challenges such as high number of
treatments, interaction effects and strong v
ariations in treatment effects on crop yield spatially and temporally as a result of agro
–climatic, field management and soil factors (Sinclair and Seligman, 1996). In order to identify the options that lead to improved crop productivity and hence high returns to the farmers under prevailing set of circumstances requires repetition of such trials over several years
/seasons or at several sites. This process is lengthy, time consuming and expensive. A less time and resource consuming alternative is the use of simulation models to predict the yield of different treatments for many growing seasons based on time series of meteorological data, soil physical and chemical properties and crop phenology and management characteristics (Boote et al., 1996)
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