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Remote sensing techniques, particularly LANDSAT data, were used to assess soil moisture stress through crop signature in southwestern Minnesota. Related objectives were: localization of droughty, well drained, and poorly drained soils; detection of stress from hail, wind, and disease damage; and the use of remote sensing data for agricultural management. Since the amount and distribution of precipitation were adequate during the 1977 and 1978 growing seasons, no significant stress occurred. Crop conditions were very favorable. As a result, crop signatures were too uniform to reflect soilscape variations and crop condition changes. In 1979 precipitation was again adequate to excess, particularly in June and August. In some cases, poorly drained sites especially, stress conditions developed as a result of excess of water and could be identified on color infrared photographs.
The results from the U.S. corn/soybeans exploratory experiment which was completed during FY 1980 are summarized. The experiment consisted of two parts: the classification procedures verification test and the simulated aggregation test. Evaluations of labeling, proportion estimation, and aggregation procedures are presented.
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Theory and experiments have shown that passive microwave radiometers can be used to measure soil moisture. However, the presence of a vegetative cover alters the measurement that might be obtained under bare conditions. Deterministically accounting for the effect of vegetation and developing algorithms for extracting soil moisture from observations of a vegetable-soil complex present significant obstacles to the practical use of this approach. The presence of a vegetation canopy reduces the sensitivity of passive microwave instruments to soil moisture variations. The reduction in sensitivity, as compared to a bare-soil relationship, increases as microwave frequency increases, implying that the longest wavelength sensors should provide the most information. Sensitivity also decreases as the amount of vegetative wet biomass increases for a given type of vegetation.
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The interdependence of root and shoot growth produces a functional equilibrium as described in quantitative terms by numerous authors. It was noted that bean seedlings grown in a constant environment tended to have a constant distribution pattern of dry matter between roots and leaves characteristic of the set of environmental conditions. Disturbing equilibrium resulted in a change in relative growth of roots and leaves until the original ratio was restored. To define a physiological basis for regulation of nitrogen uptake within the balance between root and shoot activities, the authors combined a partioning scheme and a utilization priority assumption in which: (1) all carbon enters the plant through photosynthesis in leaves and all nitrogen enters the plant through active uptake by roots, (2) nitrogen uptake by roots and secretion into the xylem for transport to the shoots are active processes, (3) availability of exogenous nitrogen determines concentration of soluble carbohydrates within the roots, (4) leaves are a source and a sink for carbohydrates, and (5) the requirement for nitrogen by leaf growth is proportionally greater during initiation and early expansion than during later expansion.
To address the questions of whether allocation of carbohydrates to roots is influenced by ionic form of nitrogen absorbed and whether allocation of carbohydrates to roots in turn influences proportionality between NH4+ and NO3- uptake from mixed sources, NH4+ and NO3- were supplied separately to halves of a split-root hydroponic system and were supplied in combination to a whole-root system. Dry matter accumulation in the split-root system was 18% less in the NH4(+)-fed axis than in the NO3(-)-fed axis. This, however, does not indicate that partitioning of carbohydrate between the two axes was different. Most of the reduction in dry matter accumulation in the NH4(+)-fed axis can be accounted for by the retransport of CH2O equivalents from the root back to the shoot with amino acids produced by NH4+ assimilation. Uptake of NH4+ or NO3- by the respective halves of the split-root system was proportional to the estimated allocation of carbohydrate to that half. When NH4+ and NO3- were supplied to separate halves of the split-root system, the cumulative NH4+ to NO3- uptake ratio was 0.81. When supplied in combination to the whole-root system, the cumulative NH4+ to NO3- uptake ratio was 1.67. Thus, while the shoot may affect total nitrogen uptake through the export of carbohydrates to roots, the shoot (common for halves of the split-root system) apparently does not exert a direct effect on proportionality of NH4+ and NO3- uptake by roots. For whole roots supplied with both NH4+ and NO3-, the restriction in uptake of NO3- may involve a stimulation of NO3- efflux rather than an inhibition of NO3- influx. While only the net uptake of NH4+ and NO3- was measured by ion chromatography, monitoring at approximately hourly intervals during the first 3 days of treatment revealed irregularly occurring intervals of both depletion (net influx) and enrichment (net efflux) in solutions. In the case of NH4+, numbers of net efflux events were similar (21 to 24 out of 65 sequential sampling intervals) whether NH4+ was supplied with NO3- to whole-root systems or separately to an axis of the split-root system. In the case of NO3-, however, the number of net efflux events increased from 8 when NO3- was supplied to a separate axis of the split-root system to between 19 and 24 when NO3- was supplied with NH4+ to whole-root systems.
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Recently, it was shown that the application of a method combining singular spectrum analysis (SSA) and the maximum entropy method to univariate indicators of the coupled ocean-atmosphere El Nino/Southern Oscillation (ENSO) phenomenon can be helpful in determining whether an El Nino (EN) or La Nina (LN) event will occur. SSA - a variant of principal component analysis applied in the time domain - filters out variability unrelated to ENSO and separates the quasi-biennial (QB), two-to-three year variability, from a lower-frequency (LF) four-to-six year EN-LN cycle; the total variance associated with ENSO combines the QB and LF modes. ENSO has been known to affect weather conditions over much of the globe. For example, EN events have been connected with unusually rainy weather over the Central and Western US, while the opposite phases of the oscillation (LN) have been plausibly associated with extreme dry conditions over much of the same geographical area...
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The laser-induced fluorescence (LIF) of green plants was evaluated as a means of remotely detecting plant stress and determining plant type. Corn and soybeans were used as representatives of monocots and dicots, respectively, in these studies. The fluorescence spectra of several plant pigments was excited with a nitrogen laser emitting at 337 nm. Intact leaves from corn and soybeans also fluoresced using the nitrogen laser. The two plant species exhibited fluorescence spectra which had three maxima in common at 440, 690, and 740 nm. However, the relative intensities of these maxima were distinctly different for the two species. Soybeans had an additional slight maxima at 525 nm. Potassium deficiency in corn caused an increase in fluorescence at 690 and 740 nm. Simulated water stress in soybeans resulted in increased fluorescence at 440, 525, 690, and 740 nm. The inhibition of photosynthesis in soybeans by 3-(3-4-dichlorophenyl)-1-1-dimethyl urea (DCMU) gave incresed fluorescence primarily at 690 and 740 nm. Chlorosis as occurring in senescent soybean leaves caused a decrease in fluorescence at 690 and 740 nm. These studies indicate that LIF measurements of plants offer the potential for remotely detecting certain types of stress condition and also for differentiating plant species.
Two Controlled Ecological Life Support System (CELSS) candidate crops, soybean (Glycine max) and potato (Solanum tuberosum), were grown hydroponically in controlled environments maintained at carbon dioxide (CO2) partial pressures ranging from 0.05 to 1.00 kPa (500 to 10,000 ppm at 101 kPa atmospheric pressure). Plants were harvested at maturity (90 days for soybean and 105 days for potato) and all tissues analyzed for proximate nutritional composition (i.e. protein, fat, carbohydrate, crude fiber, and ash content). Soybean seed ash and crude fiber were higher and carbohydrate was lower than values reported for field-grown seed. Potato tubers showed little difference from field-grown tubers. Crude fiber of soybean stems and leaves increased with increased CO2, as did soybean leaf protein (total nitrogen). Potato leaf and stem (combined) protein levels also increased with increased CO2, while leaf and stem carbohydrates decreased. Values for leaf and stem protein and ash were higher than values generally reported for field-grown plants for both species. Results suggest that CO2 partial pressure should have little influence on proximate composition of potato tubers or soybean seed, but that high ash and protein levels might be expected from leaves and stems of crops grown in controlled environments of a CELSS.
Increasing global demands for food and energy necessitate innovative land-use solutions. Agrivoltaics, colocating solar photovoltaics with agriculture, shows promise, but its widespread adoption faces complex biophysical and economic trade-offs in a changing climate. Here, we develop an integrated biophysical-economic modeling framework to quantify how agrivoltaics affect biophysical and economic impacts across the Midwestern United States under both current and project climate conditions. We find strong regional divergences driven by climate gradients. In the humid eastern Midwest, solar panel shading limits photosynthesis, leading to reduced yields (maize -24%; soybean -16%) and lower farmers' profitability (maize -16%; soybean -2%) compared to conventional agriculture. Conversely, in the semiarid western region, shading alleviates heat and water stress, moderating yield reductions for maize (-12%) and even boosting soybean yields (+6%), resulting in improved economic returns (-6% for maize; +9% for soybean), for a scenario with 33% photovoltaic ground coverage ratio. Although agrivoltaics generate substantial electrical energy across all regions, high upfront installation costs challenge solar developers compared to standalone solar photovoltaics. However, our analysis identifies “win-win” opportunities where soybean-based agrivoltaics in the semiarid region produce economic benefits for both farmers and solar developers, highlighting the necessity for region-specific designs tailored to local climate conditions. Critically, future climate projections indicate eastward expansion of semiarid conditions, broadening areas where agrivoltaics can mitigate crop yield penalties (even boosting yield) and improve overall profitability, especially under high-emission scenarios. The results provide a mechanistic and economically integrated understanding essential for developing evidence-based and region-specific strategies to scale agrivoltaics in a changing climate.
Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.
Red leaf blotch of soybean, caused by the fungus Coniothyrium glycines, is a foliar disease characterized by blotching, necrosis, and defoliation that has only been reported from Africa. The species is listed as a Select Agent by the Federal Select Agent Program due to its potentially devastating impacts to soybean production should it spread to the United States. Despite its potential import, very few isolates are available for study. Herein, we obtained 96 new C. glycines isolates from six soybean-producing countries throughout sub-Saharan Africa. Along with 12 previously collected ones, we sequenced each at the internal transcribed spacer (ITS) region. Between all isolates, we identified a total of 28 single-nucleotide polymorphisms and 23 haplotypes. One hypothesis to explain the tremendous diversity uncovered at the ITS—which is generally conserved within a species—is that our current species concept of C. glycines is too broad and that there may be multiple species that cause red leaf blotch. Zambia contained the highest haplotype diversity, a significant fraction of which remains unsampled. Most haplotypes were specific to a single country, except for two, which were found in Zambia and either neighboring Mozambique or Zimbabwe. This geographic specificity indicates that the ITS region may be useful for identifying source populations or routes of transmission should this pathogen spread beyond Africa. The observed geographic partitioning of this pathogen is likely the result of millions of years of replication on little-studied native hosts, given that soybean has only been cultivated in Africa since the early 1900s.