Keiichi Nakayama

Root water uptake and profile soil water as affected by vertical root distribution

Water uptake by plant roots is a main process controlling water balance in field profiles and vital for agro-ecosystem management. Based on the sap flow measurements for maize plants (Zea mays L.) in a field under natural wet- and dry-soil conditions, we studied the effect of vertical root distribution on root water uptake and the resulted changes of profile soil water. The observations indicate that depth of the most densely rooted soil layer was more important than the maximum rooting depth for increasing the ability of plants to cope with the shortage of water. Occurrence of the most densely rooted layer at or below 30-cm soil depth was very conducive to maintaining plant water supply under the dry-soil conditions. In the soil layers colonized most densely by roots, daytime effective soil water saturation (Se) always dropped dramatically due to the high-efficient local water depletion. Restriction of the rooting depth markedly increased the difference of Se between the individual soil layers particularly under the dry-soil conditions due likely to the physical non-equilibrium of water flow between the layers. This study highlights the importance of root distribution and pattern in regulating soil water use and thereby improving endurance of plants to seasonal droughts for sustainable agricultural productivity.

A proposal for universal formulas for estimating leaf water status of herbaceous and woody plants based on spectral reflectance properties

The present study deals with the relationships between water status parameters of plant leaves and reflectances (Rλ) at characteristic wavelengths, between 522 and 2450 nm, as well as reflectance ratios, Rλ/R1430, Rλ/R1650, Rλ/R1850, Rλ/R1920, and Rλ/R1950, based on the air-drying experimental results of soybean (Glycine max Merr.), maize (Zea mays L.), tuliptree (Liriodendron tulipifera L.) and viburnum (Viburnum awabuki K. Koch.) plants. The water status parameters include leaf water content per unit leaf area (LWC), specific leaf water content (SWC), leaf moisture percentage of fresh weight (LMP), relative leaf water content (RWC) and relative leaf moisture percentage on fresh weight basis (RMP). Effective spectral reflectances and reflectance ratios for estimating the LWC, SWC, LMP, RWC and RMP were identified. With these spectral indices, approaches to estimating LWC, RWC and RMP were discussed. Eventually, an attempt on universal formulas was made for estimating the leaf moisture conditions of both herbaceous and woody plants as mentioned above. Moreover, applicability of these formulas was checked with the field experimental results of soybean and maize grown under water and nutrient stresses.

Predicting unsaturated hydraulic conductivity of soil based on some basic soil properties

Soil hydraulic conductivity is a crucial parameter in modeling Row process in soils and deciding water management. In this study, by combining the non-similar media concept (NSMC) to the one-parameter model of Brooks and Corey, a new NSMC-based model for estimating unsaturated hydraulic conductivity of various soils was presented. The main inputs are soil bulk density, particle-size distribution. soil water retention characteristic and saturated hydraulic conductivity of soil. The results indicated that the NSMC-based model could generally more accurately predict unsaturated hydraulic conductivity of soils, as compared to four one-parameter models and van Genuchten-Mualem model. This study. by introducing NSMC, provided a new way to incorporate soil physical heterogeneity into soil hydraulic simulation, and hence NSMC-based approach is expected to improve efficiency of the existing models in the simulation of soil water flow.

Estimation of root water uptake of maize: an ecophysiological perspective

An understanding of movement and distribution of soil water has been long known essential to the optimization of plant biomass productivity. This study provides an ecophysiologically based analytic model for estimating root water uptake rate of maize (Zea mays L.). The model can be run with readily available inputs, such as water potentials of leaf, soil and air, solar radiation, potential evapotranspiration, root length, and some soil physical properties, such as bulk density and particle-size distribution. Comparison with measured data showed that the model described root water extraction with acceptable accuracy. Analysis of the response of the model to changes in the input parameters revealed that the model is most sensitive to leaf water potential and root length. Examination of the model response also showed that the model could be improved with more information about the root hydraulic conductance and effective root length responsible for water extraction.

A combination model for estimating stomatal conductance of maize (Zea mays L.) leaves over a long term

Abstract In this study, an environmental variable model for estimating stomatal conductance of maize (Zea mays L.) leaves over a long term is developed, based on research results concerning responses of stomatal conductance to environmental variables. This model is actually a combination of optimized formulae for potential stomatal conductance during daytime, PSC, and for the relative degree of stomatal opening during daytime, RDO, with a basic form expressed as a multiplication of inter-day and intra-day factors. We call this environmental variable model as the combination model. Compared with other models presented in the past, this combination model is convenient in practical use because it can estimate not only maximum and average values but also instantaneous values of stomatal conductance during daytime. Also, the theoretical description of this model has been clarified by introducing into it the concept of environmental stress. As compared with Jarvis-type multiplication environmental variable models, we think this combination model is a refinement and development of the Jarvis-type models.

Scaling of root length density of maize in the field profile

Root length density is an important parameter in crop growth simulation and in evaluating consequences of root pattern on crop water and nutrient uptake. In this study, a scaling model was presented for estimating the profile distribution of root length density of maize (Zea mays L.). The model inputs are root length data of a reference profile and bulk densities of soil layers, as well as root length data in the first soil layer of a field profile to be investigated. Using the root length data of 10 soil profiles investigated over 2 years, the model was examined. The results show that the proposed scaling approach is effective in estimating the root length density of each layer of soil in the field profile. The relative root mean square error (RRMSE) of the developed scaling model was 25.28%, while that of the traditional exponential model was 39.53%. The scaling approach would facilitate determination of heterogeneous distributions of root length densities in the field.